Part 9 — Thompson & Thompson Genetics and Genomics in Medicine

Chapter 16: Cancer Genetics and Genomics

Ch16 · Pt1 chapter 16 Cancer Genetics and Genomics Michael F. Walsh Cancer is a common disease. Overall, there are 14 million new cases of cancer diagnosed each year and over 8 million deaths from the disease worldwide. In the United States, there are 250,000 cases each of breast and prostate cancer, 150,000 cases of colon cancer, and over 100,000 cases of lung cancer diagnosed each year. Although cancer is the most common cause of disease- related death in children, pediatric cancer itself is a rare disease in comparison to adult cancer, with 16,000 new cases diagnosed in the United States annually. National costs for cancer care in the United States were estimated to be $190.2 billion in 2015 and $208.9 billion in 2020 (https://progressreport.cancer.gov/after/economic_ burden). Identification of persons at increased risk for cancer before its development is an important objective of genetics research and clinical care. In the general population as well as in those with a heritable predisposition, early diagnosis and treatment is vital, and both are increasingly reliant on advances in genome sequencing and gene expression analysis. Historically, in the context of the genetic basis of cancer, the focus has been on somatic genetics as most cancer is considered to arise from stochastic acquisition of genetic (and epigenetic) events. However, distinguishing germline and somatic genetics is an important distinction in understanding the pathogenesis of the disease. GERMLINE VERSUS SOMATIC Germline refers to the sex cells (gametes) that are used by sexually reproducing organisms to pass on genes from generation to generation. Egg and sperm cells are called germ cells, as opposed to the other cells of the body that are referred to as somatic cells; somatic cells are any cell of the body except sperm and egg cells. Mutations in somatic cells can affect the individual, but they are not passed on to offspring. NEOPLASIA The word cancer originates from the Latin word for crab and refers to the aggressive and malignant forms of neoplasia, a disease process characterized by uncontrolled cellular proliferation leading to a mass or tumor. The abnormal accumulation of cells in a neoplasm occurs because of an imbalance between the normal processes of cellular proliferation and cellular attrition. Cells proliferate as they pass through the cell cycle and undergo mitosis. Attrition, due to programmed cell death (see Chapter 15), removes cells from a tissue. For a neoplasm to be a cancer, however, it must also be malignant, which means that not only is its growth uncontrolled, but it is also capable of invading neighboring tissues that surround the original site (the primary site) and can spread (metastasize) to more distant sites (Fig. 16.1). Tumors that do not invade or metastasize are not cancerous but are referred to as benign tumors, although their abnormal function, size, or location may make them anything but benign to the patient (e.g., disrupting visual pathways, impinging upon nerves or causing vascular stasis and thrombus). Cancer is not a single disease. Rather, it comes in many forms and degrees of malignancy and varying biologic processes. There are three main classes of cancer: Sarcomas, in which the tumor has arisen in mesenchymal tissue, such as bone, muscle, or connective tissue, or in nervous system tissue Carcinomas, which originate in epithelial tissue, such as the cells lining the intestine, bronchi, or mammary ducts Hematopoietic and lymphoid malignant neoplasms, such as leukemia and lymphoma, which arise in cells of hematopoietic lineage, including bone marrow and the lymphatic system Within each of the major groups, tumors are classified by site, tissue type, histologic appearance, degree of malignancy, chromosomal aneuploidy, and, increasingly, by which gene variants, fusions, and abnormalities in gene expression are found in the somatic landscape of the tumor as cataloged in data repositories such as the c Bio Portal, COSMIC, PECAN, and Genomic Data Commons (GDC) (Table 16.1). In this chapter we describe how genetic and genomic studies demonstrate that cancer is fundamentally a genetic disease and how cancer evolves because of genetic and environmental factors, as well as distinct patterns of cell turnover at distinct periods over a lifetime. First, we describe genes recognized and implicated ▶

chapter 16 Cancer Genetics and Genomics Michael F. Walsh Cancer is a common disease. Overall, there are 14 million new cases of cancer diagnosed each year and over 8 million deaths from the disease wo...

Ch16 · Pt2 348 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE in initiating cancer and the mechanisms by which dysfunction of these genes can result in disease. Second, we review heritable cancer syndromes and demonstrate how insights gained into their pathogenesis have illuminated the basis of the much more common, sporadic forms of cancer. We examine some of the special challenges that such heritable syndromes present for medical geneticists, genetic counselors, and oncologists. Third, we illustrate ways in which genetics and genomics have changed both how we think about the causes of cancer and how we diagnose and treat the disease. The identification of mutations, altered epigenomic modifications, and abnormal gene expression in cancer cells is rapidly expanding our knowledge of why cancer develops and is truly changing approaches to cancer diagnosis and treatment. Furthermore, integrating somatic and germline Normal epithelium Proliferation Local invasion Lymph node invasion Distant metastases Lymphatics Blood vessel Figure 16.1 General scheme for development of a carcinoma in an epithelial tissue such as colonic epithelium. The diagram shows progression from normal epithelium to local proliferation, invasion across the lamina propria, spread to local lymph nodes, and final distant metastases to liver and lung. ▶

348 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE in initiating cancer and the mechanisms by which dysfunction of these genes can result in disease. Second, we review heritable cancer syndro...

Ch16 · Pt3 CHAPTER 16 — Cancer Genetics and Genomics 349 variant data is enabling more rapid interpretations of variants detected in constitutional samples than possible without companion germline sequencing. GENETIC BASIS OF CANCER Driver and Passenger Gene Mutations Applying next generation sequencing (NGS) (see Chapter 4) and RNA expression studies (see Chapter 3) has provided clarity to understanding the origins of cancer. By aggregating and analyzing thousands of samples obtained from a wide variety of cancer types, researchers continue building The Cancer Genome Atlas, a public catalog of variants, epigenomic modifications, and abnormal gene expression profiles, which is visualized in the GDC. This endeavor along with Project Genomics Evidence Neoplasia Information Exchange (GENIE) housed in the c Bio Portal (https://www.cbioportal.org/) and the Pediatric Cancer Genome Project (PCGP) with illustrated data via the PECAN portal (https://pecan. stjude.cloud/) are tremendous undertakings toward the annotation and classification of genomic variation detected in human cancers. These efforts continue to grow, and findings thus far are extremely informative. The number of mutations present in a tumor can vary from just a few to many tens of thousands. In general, pediatric cancers are more “silent” than adult tumors in terms of the number of mutations detected; however, there are notable exceptions to this trend (e.g., constitutional biallelic pathogenic variants in the mismatch repair (MMR) genes result in a very high mutational burden in both pediatric and adult tumors). When identified, this exceptionally high tumor mutational burden indicates a consideration for immunotherapy. Most variants identified through tumor sequencing appear to be random, are not recurrent in particular cancer types, and likely occurred as the cancer developed rather than directly causing the neoplasia to develop or progress. These are referred to as passenger mutations. However, a subset of a few hundred genes has repeatedly been found to be mutated at a frequency too high to be considered simply passenger in nature. These mutated genes occur in many samples of the same cancer type and often in multiple different types of cancers. They are presumed to be involved in the development or progression of the cancer itself and are therefore referred to as driver genes; that is, they harbor mutations (so-called driver mutations) that are likely to be causing a cancer to develop or progress. Although some driver genes are specific to particular tumor types, some, such as those in the TP53 gene encoding the p 53 protein, are found in the vast majority of cancers. Although the most common driver genes are now known, it is likely that additional, less common driver genes will be identified as The Cancer Genome Atlas continues to grow. Another resource in identifying driver genes, (https://cancerhotspots.org/) provides evidence for variants as oncogenic based on gene size, expected mutation rate, and cancer types detected. This database is supported by mathematical modeling and statistical rigor to determine the likelihood that a specific variant is oncogenic. Spectrum of Driver Mutations Various genomic alterations can act as driver mutations. In some cases, a single nucleotide change or small insertion or deletion can be a driver mutation. Large numbers of cell divisions are required to produce an adult organism of an estimated 1014 cells from a single-cell zygote. Given a frequency of 10−10 replication errors per DNA base per cell division, and an estimated 1015 cell divisions during the lifetime of an adult, replication errors alone result in thousands of new single nucleotide TABLE 16.1 Classes of Driver Genes Mutated in Cancer Genes With Specific Effects on Cellular Proliferation or Apoptosis Genes With Global Effects on Genome or DNA Integrity or on Gene Expression Cell-cycle regulation Cell-cycle checkpoint proteins Cellular proliferation signaling Transcription factors Receptor and membrane-bound tyrosine kinases Growth factors Intracellular serine-threonine kinases PI3 kinases G proteins and G protein–coupled receptors m TOR signaling Wnt/β-catenin signaling Transcription factors Differentiation and lineage survival Transcription factors protecting specific cell lineages Genes involved in exit from cell cycle into G0 Apoptosis Genome integrity Chromosome segregation Genome and gene mutation DNA repair Telomere stability Gene expression: abnormal metabolites affecting activity of multiple genes/gene products Gene expression: epigenetic modifications of DNA/chromatin DNA methylation and hydroxymethylation Chromatin histone methylation, demethylation, and acetylation Nucleosome remodeling Chromatin accessibility and compaction (SWI/SNF complexes) Gene expression: posttranscriptional alterations Aberrant mRNA splicing Micro RNAs affecting mRNA stability and translation Gene expression: protein stability/turnover mRNA, Messenger RNA; m TOR, mammalian target of rapamycin; PI3, phosphatidylinositol-3. ▶

Ch16 · Pt4 350 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE or small insertion/deletion variants in the genome in every cell of the organism. Some environmental agents, such as carcinogens in cigarette smoke or ultraviolet or X-irradiation, will increase the rate of mutation across the genome. If, by chance, mutations occur in critical driver genes in a particular cell, then the oncogenic process may be initiated and in some instances be evidenced by a tumor signature. Gross chromosome and subchromosomal changes (see Chapters 5 and 6) can also serve as driver mutations. Particular translocations or fusions are sometimes highly specific for certain types of cancer and involve specific genes (e.g., the BCR-ABL translocation in chronic myelogenous leukemia) (Case 10). In contrast, other cancers can have complex rearrangements in which chromosomes break into numerous pieces and rejoin, forming novel and complex combinations (a process known as chromothripsis [“chromosome shattering”]). Finally, large genomic alterations involving many kilobases of DNA can form the basis for loss of function or increased function of one or more driver genes. Large genomic alterations include deletions of a segment of a chromosome or multiplication of a chromosomal segment to produce regions with many copies of the same gene (gene amplification). The nature of these chromosomal events may be driven by somatic or germline events. In the case of fusions, these are nearly always postzygotic events. Complex combinations may be driven by constitutional alterations, for example, in the case of TP53 germline pathogenic variants associated with chromothripsis in some cancers. Large duplications or deletions may reflect constitutional or somatic origin. The Cellular Functions of Driver Genes The nature of some driver mutations comes as no surprise: the mutations directly affect specific genes that regulate processes that are readily understood to be important in oncogenesis. These processes include cell cycle regulation, cellular proliferation, differentiation and exit from the cell cycle, growth inhibition by cell- cell contacts, and programmed cell death (apoptosis). However, the effects of other driver mutations are not so readily understood and include genes that act more globally and indirectly affect the expression of many other genes. Included in this group are genes encoding products that maintain genome and DNA integrity or genes that affect gene expression, either at the level of transcription by epigenetic changes, at the posttranscriptional level through effects on messenger RNA (mRNA) translation or stability, or at the posttranslational level through their effects on protein turnover (see Table 16.1). Other driver genes affect translation, including, for example, genes that encode noncoding RNAs from which regulatory micro RNAs (miRNAs) are derived (see Chapter 3). Many miRNAs have been found to be either overexpressed or down-regulated in various tumors, sometimes strikingly so. Because each miRNA may regulate as many as 200 different gene targets, over- or underexpression of miRNAs may have widespread oncogenic effects because many driver genes will be dysregulated. Noncoding miRNAs that impact gene expression and contribute to oncogenesis are referred to as oncomirs. DICER1 is a gene encoding a protein involved in the production of miRNAs, and germline pathogenic variants in this gene predispose individuals to a number of benign and malignant tumors, including (among others) thyroid cancer, multinodular goiter, Sertoli-Leydig cell tumors, cystic nephroma, and pleuropulmonary blastoma. Fig. 16.2 outlines how mutations in specific regulators of growth and in global guardians of DNA and genome integrity perturb normal homeostasis (see Fig. 16.2A), leading to a vicious cycle of loss of cell cycle control, uncontrolled proliferation, interrupted differentiation, and defects in apoptosis (see Fig. 16.2B). Oncogenes and Tumor Suppressor Genes Both classes of driver genes—those with specific effects on cellular proliferation or survival and those with global effects on genome or DNA integrity (see Table 16.1)—can be further divided into two functional categories depending on how they drive oncogenesis when mutated. The first category includes proto-oncogenes. When mutated in particular ways, these genes become drivers through alterations that lead to excessive levels of activity. Once mutated in this way, driver genes of this type are referred to as activated oncogenes. Only a single mutation on one allele is typically sufficient for activation. The mutations that activate proto- oncogenes range from highly specific point mutations causing dysregulation or hyperactivity of a protein, to chromosome translocations that drive overexpression of a gene, to gene amplification events that create an overabundance of the encoded mRNA and protein product (Fig. 16.3). The second, and more common, category of driver genes includes tumor suppressor genes (TSGs), mutations that cause a loss of expression of proteins necessary to control the development of cancers. To drive oncogenesis, loss of function of a TSG typically requires variants on both alleles. There are many ways that a cell can lose the function of TSG alleles; loss-of-function mechanisms range from missense, nonsense, or frameshift mutations to gene deletions or loss of a part or even an entire chromosome. Loss of function of TSGs can also result from epigenetic transcriptional silencing due to altered chromatin conformation or promoter methylation (see Chapter 3) or from translational silencing by miRNAs or disturbances in other components of the translational machinery (see Box). ▶

350 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE or small insertion/deletion variants in the genome in every cell of the organism. Some environmental agents, such as carcinogens in cigaret...

Ch16 · Pt5 CHAPTER 16 — Cancer Genetics and Genomics 351 Cellular Heterogeneity Within Individual Tumors The accumulation of driver mutations does not occur synchronously, in lockstep, in every cell of a tumor. To the contrary, cancer evolves along multiple lineages within a tumor, as chance mutational and epigenetic events in different cells activate proto-oncogenes and cripple the machinery for maintaining genome integrity, leading to more genetic changes in a vicious cycle of more mutations and worsening growth control. The lineages that experience an enhancement of growth, survival, invasion, and distant spread will come to predominate as the cancer evolves and progresses (see Box 16.1). In this way the original clone of neoplastic cells evolves and gives rise to multiple sublineages, each carrying a set of mutations and epigenomic alterations that are different from but overlap with what is carried in other sublineages. The profile of mutations and epigenomic DNA replication/repair Chromosome stability and segregation Genome Epigenome Gene expression DNA methylation and hydroxymethylation Chromatin accessibility Histone modifications Copy number transcription translation Transcriptional regulation Proteins and micro RNAs Histone modification enzymes Proteins controlling chromosome segregation chromosome/telomere stability Cell cycle control Controlled proliferation Terminal differentiation Apoptosis DNA repair proteins DNA modification enzymes Checkpoint proteins Growth factors and receptors Transcription factors Apoptosis factors DNA replication/repair Chromosome stability and segregation Loss of genomic integrity Abnormal epigenome profile Disordered copy number and gene expression DNA methylation and hydroxymethylation Chromatin accessibility Histone modifications Transcriptional regulation Proteins and micro RNAs Histone modification enzymes Proteins controlling chromosome segregation chromosome/telomere stability Loss of cell cycle control Uncontrolled proliferation Interrupted differentiation Failure of apoptosis DNA repair proteins DNA modification enzymes Checkpoint proteins Growth factors and receptors Transcription factors Apoptosis factors A B Figure 16.2 (A) Overview of normal genetic pathways controlling normal tissue homeostasis. The information encoded in the genome (black arrows) results in normal gene expression, as modulated by the epigenomic state. Many genes provide negative feedback (purple arrows) to ensure normal homeostasis. (B) Perturbations in neoplasia. Abnormalities in gene expression (dotted black arrows) lead to a vicious cycle of positive feedback (brown dotted lines) of progressively more disordered gene expression and genome integrity. ▶

CHAPTER 16 — Cancer Genetics and Genomics 351 Cellular Heterogeneity Within Individual Tumors The accumulation of driver mutations does not occur synchronously, in lockstep, in every cell of a tumor....

Ch16 · Pt6 352 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE Proto-oncogene Activating mutation Functional product Abnormal protein Gene amplification Excessive amount of protein Novel protein Excessive amount of protein Proto-oncogene Coding mutation Regulatory mutation Translocation Figure 16.3 Different mutational mechanisms leading to proto-oncogene activation. These include a single point mutation leading to an amino acid change that alters protein function, mutations or translocations that increase expression of an oncogene; a chromosome translocation that produces a novel product with oncogenic properties; and gene amplification leading to excessive amounts of the gene product. BOX 16.1 GENETIC BASIS OF CANCER Regardless of whether a cancer occurs sporadically in an individual, purely as a result of somatic mutation, or repeatedly in many individuals in a family who share an inherited germline pathogenic variant, cancer is a genetic disease. Genes in which mutations cause cancer are referred to as driver genes, and the cancer-causing mutations in these genes are driver mutations. Driver genes fall into two distinct categories: proto- oncogenes and tumor suppressor genes (TSGs). An activated oncogene is a mutant allele of a proto- oncogene, a class of normal cellular protein-coding genes that promote growth and survival of cells. Activated oncogenes facilitate malignant transformation by stimulating proliferation or inhibiting apoptosis. Oncogenes encode proteins such as: Those in signaling pathways that control cell proliferation Transcription factors that control the expression of growth-promoting genes Inhibitors of programmed cell death machinery A TSG is a gene in which loss of function through mutation or epigenetic silencing either directly removes normal regulatory controls on cell growth or leads indirectly to such losses through an increased mutation rate or aberrant gene expression. TSGs encode proteins involved in many aspects of cellular function, including maintenance of correct chromosome number and structure, DNA repair, cell cycle regulation, cellular proliferation, or contact inhibition, just to name a few examples. Tumor initiation can be caused by different types of genetic alterations. These include: Activating or gain-of-function mutations, including gene amplification, point mutations, and promoter mutations, that convert one allele of a proto- oncogene into an activated oncogene Ectopic and heterochronic mutations (see Chapter 11) of proto-oncogenes Chromosome translocations leading to gene fusions that cause misexpression of genes or create chimeric genes encoding proteins with novel functional properties Loss of function of both alleles, or a dominant negative mutation of one allele, of a TSG Tumor progression occurs because of accumulating additional genetic damage, through mutations or epigenetic silencing, of driver genes that encode the machinery that repairs damaged DNA and maintains cytogenetic normality. A further consequence of genetic damage is altered expression of genes that promote vascularization and the spread of the tumor through local invasion and distant metastasis. changes can differ between the primary and its metastases, between different metastases, and even between the cells of the original tumor or within a single metastasis. A paradigm for the development of cancer (Fig. 16.4) provides a useful conceptual framework for considering the role of genomic and epigenomic changes in the evolution of cancer, a point we emphasize throughout this chapter. It is a general model that applies to all cancers. Although the focus of this chapter is on genomic and epigenomic changes within the tumor, the surrounding normal tissue also plays an important role by providing the blood supply that nourishes the tumor, by permitting cancer cells to escape from the tumor and metastasize, and by shielding the tumor from immune attack. Thus cancer is a complex process, both within the tumor and between the tumor and the normal tissues that surround it. CANCER IN FAMILIES Although essentially all individuals are at risk to develop a cancer at some point during their lifetime, many forms of cancer have a higher incidence in relatives of people ▶

352 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE Proto-oncogene Activating mutation Functional product Abnormal protein Gene amplification Excessive amount of protein Novel protein Excessiv...

Ch16 · Pt7 CHAPTER 16 — Cancer Genetics and Genomics 353 with cancer than in the general population. In some cases, this increased incidence is due primarily to inheritance of a single mutant gene with high penetrance. These pathogenic variants result in hereditary cancer syndromes (see, e.g., Cases 7, 29, 39, and 48) following mendelian patterns of inheritance that were presented in Chapter 7. Among these syndromes we currently know of ~100 different genes in which pathogenic variants increase the risk for cancer many-fold higher than in the general population. There are also many additional genetic disorders that are not usually considered to be hereditary cancer syndromes and yet include some increased predisposition to cancer (Case 6) (e.g., the 10- to 20-fold increased lifetime risk for leukemia in Down syndrome [see Chapter 6]). These clear examples notwithstanding, it is important to emphasize that not all families with an apparently increased incidence of cancer can be explained by known mendelian or clearly recognized genetic disorders. Many of these families likely represent the effects of both shared environment and one or more genetic variants that increase susceptibility and are therefore classified as multifactorial, with complex inheritance (see Chapter 9), as will be explored later in this chapter. Individuals with a hereditary cancer predisposition likely represent at least 15% of all patients with cancer; identification of a genetic basis for their disease has great importance both for clinical management of these families and for understanding cancer in general. Identifying the heritable basis of cancer is important for diagnostics, screening, therapeutics, cascade testing, and family planning. Relatives of individuals with strong hereditary predispositions, in particular when due to pathogenic variants in a single gene, can be offered testing and counseling to provide appropriate reassurance or knowledge about their own risk, guidance on screening and early tumor detection, therapeutic considerations in the context of disease, prenatal and preconception counseling, and testing of other individuals in the family at risk. As is the case with many common diseases, understanding the hereditary forms of cancer provides crucial insights into disease mechanisms that go far beyond the rare hereditary forms themselves. Finally, in multiple studies over the last decade, pathogenic variants in a broad array of cancer predisposition genes have been revealed in agnostic studies, including various cancer populations. These concepts are illustrated in the examples discussed in the sections that follow. Activated Oncogenes in Hereditary Cancer Syndromes Multiple Endocrine Adenomatosis, Type 2 The type A variant of multiple endocrine neoplasia, type 2 (MEN2A), is an autosomal dominant disorder characterized by a high incidence of medullary carcinoma of the thyroid that is often but not always associated with pheochromocytoma, benign parathyroid adenomas, or both. Patients with the rarer type B variant (MEN2B) have, in addition to younger age of onset of the tumors seen in patients with MEN2A, thickening of nerves and the benign neural tumors, known as neuromas, on the mucosal surface of the mouth and lips and along the gastrointestinal tract. The pathogenic variants responsible for MEN2 are in the RET oncogene. Individuals who inherit an activating variant in RET have a greater than 60% chance of developing medullary thyroid carcinoma. Blood tests for thyrocalcitonin or urinary catecholamines synthesized Normal cell Mutations in DNA repair genes Mutations in DNA modifying genes Mutations in chromatin modifying genes Increased proliferation Early neoplasia Progressive neoplasia Progressive neoplasia Progressive neoplasia Progressive neoplasia Carcinoma Carcinoma Carcinoma Metastasis Metastasis Metastasis Metastasis Metastasis Mutation in Gene A Mutation in Gene B Mutation in Gene C Increasing chromosomal aneuploidy Figure 16.4 Stages in the evolution of cancer. Increasing degrees of abnormality are associated with sequential loss of tumor suppressor genes from several chromosomes and activation of proto-oncogenes, with or without a concomitant defect in DNA repair. Multiple lineages, carrying different mutations and epigenomic profiles, occur within the primary tumor itself, between the primary and metastases and between different metastases. ▶

CHAPTER 16 — Cancer Genetics and Genomics 353 with cancer than in the general population. In some cases, this increased incidence is due primarily to inheritance of a single mutant gene with high pene...

Ch16 · Pt8 354 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE by pheochromocytomas are abnormal in over 90% of individuals with MEN2. RET encodes a cell-surface protein that contains an extracellular domain that can bind signaling molecules and a cytoplasmic tyrosine kinase domain. Tyrosine kinases are a class of enzymes that phosphorylate tyrosines in proteins. Tyrosine phosphorylation initiates a signaling cascade of changes in protein-protein and DNA-protein interactions and in the enzymatic activity of many proteins (Fig. 16.5). Normally, tyrosine kinase receptors must bind specific signaling molecules to undergo the conformational change that makes them enzymatically active and able to phosphorylate other cellular proteins. The pathogenic variants in RET that cause MEN2 increase its kinase activity even in the absence of its ligand (a state referred to as constitutive activation). The RET gene is expressed in many tissues of the body and is required for normal embryonic development of autonomic ganglia and the kidney. It is unclear why germline activating mutations in this proto-oncogene result in particular cancers of distinct histologic types restricted to specific tissues, whereas other tissues in which the oncogene is expressed do not develop tumors. Interestingly, RET is also implicated in some cases of Hirschsprung disease (see Chapter 9), although the associated pathogenic variants are usually loss of function, not activating. There are, however, some families in which the same pathogenic variant in RET can act as an activated oncogene in some tissues (such as thyroid) and cause MEN2A, and not have sufficient function in other tissues such as the developing enteric neurons of the gastrointestinal tract, resulting in Hirschsprung disease. Thus even the identical variant can have different effects on different tissues. The Two-Hit Theory of Tumor Suppressor Gene Inactivation in Cancer As introduced earlier, whereas the proteins encoded by proto-oncogenes promote cancer when activated or overexpressed, mutations in TSGs contribute to malignancy by a different mechanism—namely, the loss of function of both alleles of the gene. The products of many TSGs have now been isolated and characterized, some of which are presented in Table 16.2. Suppress apoptosis Stimulate proliferation Recruits multiple proteins and activates other kinases and small G proteins that in turn activate various transcription factors L 1 2 PO4 SHC PO4 L SHC L PO4 PO4 L L L L L L L Kinase Figure 16.5 Schematic diagram of the function of the Ret receptor, the product of the RET proto-oncogene. Upon binding of a ligand (L), such as glial-derived growth factor or neurturin, to the extracellular domain, the protein dimerizes and activates its intracellular kinase domain to autophosphorylate specific tyrosine residues. These then bind the SHC adaptor protein, which sets off multiple cascades of complex protein interactions involving other serine-threonine and phosphatidylinositol kinases and small G proteins, which in turn activate other proteins, ultimately activating certain transcription factors that suppress apoptosis and stimulate cellular proliferation. Pathogenic variants in RET that result in the type A variant of multiple endocrine neoplasia, type 2 (MEN2A), cause inappropriate dimerization and activation of its own intrinsic kinase without ligand binding. ▶

354 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE by pheochromocytomas are abnormal in over 90% of individuals with MEN2. RET encodes a cell-surface protein that contains an extracellular d...

Ch16 · Pt9 CHAPTER 16 — Cancer Genetics and Genomics 355 TABLE 16.2 Selected Tumor Suppressor Genes Disorders in Which the Gene Is Affected Gene Gene Product and Possible Function Familial Sporadic RB1 p 110 Cell cycle regulation Retinoblastoma Retinoblastoma, small cell lung carcinomas, breast cancer TP53 p 53 Cell cycle regulation Li-Fraumeni syndrome Lung cancer, breast cancer, many others APC APC Multiple roles in regulating proliferation and cell adhesion Familial adenomatous polyposis Colorectal cancer VHL VHL Forms part of a cytoplasmic destruction complex with APC that normally inhibits induction of blood vessel growth when oxygen is present von Hippel-Lindau syndrome Clear cell renal carcinoma BRCA1, BRCA2 BRCA1, BRCA2 Chromosome repair in response to double- stranded DNA breaks Hereditary breast and ovarian cancer Breast cancer, ovarian cancer MLH1, MSH2, MSH6, PMS2, EPCAM MLH1, MSH2, MSH6, PMS2, EPCAM Repair nucleotide mismatches between strands of DNA Lynch syndrome Colorectal cancer The existence of TSG mutations leading to cancer was proposed by Alfred Knudson some five decades ago to explain why certain tumors can occur in either hereditary or sporadic forms (Fig. 16.6) (see discussion in next section). It was suggested that the hereditary form of the childhood cancer retinoblastoma (see next section) might be initiated when a retinal cell in a person heterozygous for a germline pathogenic variant in the retinoblastoma TSG (now known to be RB1), required to prevent the development of the cancer, undergoes a second somatic event that inactivates the other RB1 allele. Multiple tumors Bilateral Early onset Single tumors Unilateral Later onset Normal gene Mendelian Sporadic Germline mutation Somatic mutation Somatic mutation Somatic mutation Figure 16.6 Comparison of mendelian and sporadic forms of cancers such as retinoblastoma and familial adenomatous polyposis of the colon. See text for discussion. As a consequence of this second somatic event, the cell loses function of both alleles, giving rise to a tumor. In the sporadic form of retinoblastoma, both alleles are also inactivated, but in this case the inactivation results from two somatic events occurring in the same cell. This so-called Knudson two-hit model is now widely accepted as the explanation for many hereditary cancers in addition to retinoblastoma, including cancers arising in familial adenomatous polyposis (FAP), hereditary breast cancer, neurofibromatosis type 1 (NF1), Lynch syndrome (LS), and Li-Fraumeni syndrome (LFS). ▶

CHAPTER 16 — Cancer Genetics and Genomics 355 TABLE 16.2 Selected Tumor Suppressor Genes Disorders in Which the Gene Is Affected Gene Gene Product and Possible Function Familial Sporadic RB1 p 110 Cel...

Ch16 · Pt10 356 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE Tumor Suppressor Genes in Autosomal Dominant Cancer Syndromes Retinoblastoma Retinoblastoma is the prototype of diseases caused by a pathogenic variant in a TSG. It is a rare malignant tumor of the retina in infants, with an incidence of ~1 in 20,000 births (Fig. 16.7) (Case 39). It is the classic example put forth by Knudson, illustrating the role of a germline event leading to earlier age of disease and wider extent (unilateral vs bilateral). Treatment of a retinoblastoma may require removal of the affected eye; however, the advent of intraarterial chemotherapy has allowed many tumors to be effectively treated by local therapy so that vision can be preserved. Approximately 40% of cases of retinoblastoma are of the heritable form, in which the child (as just discussed and as represented by the family shown in Fig. 16.6) has one germline pathogenic variant in RB1, either inherited from a heterozygous parent or which occurred de novo, or from a parent with germline mosaicism for the RB1 pathogenic variant (see Chapter 7). In these children, retinal cells, which like all other cells of the body, are already carrying one defective RB1 allele, suffer a somatic mutation in the other allele, leading to loss of function from both copies of RB1 and initiating tumor development (Fig. 16.8). The disorder appears to be inherited as a dominant trait because the large number of primordial retinoblasts and their rapid rate of proliferation make it very likely that a somatic mutation will occur as a second hit Figure 16.7 Retinoblastoma in a young girl, showing as a white reflex in the affected left eye when light reflects directly off the tumor surface. (Photograph courtesy B. L. Gallie, The Hospital for Sick Children, Toronto.) Tumor genotypes Constitutional genotype Locus A Locus B 1 1 2 2 Epigenetic silencing Somatic recombination Mutation Loss and duplication Chromosome loss 1 1 2 2 1 1 1 1 1 1 1 1 2 1 1 1 2 2 RB1 rb + rb rb rb rb rb rb rb rb (+) Figure 16.8 Chromosomal mechanisms that could lead to loss of heterozygosity (LOH) for DNA markers at or near a tumor suppressor gene in an individual heterozygous for a germline pathogenic variant. The figure depicts the events that constitute the second hit that leads to retinoblastoma with LOH. Local events such as mutation, gene conversion, or transcriptional silencing by promoter methylation, however, could also cause loss of function of both RB1 genes without producing LOH. +, Normal allele; rb, mutant allele. ▶

356 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE Tumor Suppressor Genes in Autosomal Dominant Cancer Syndromes Retinoblastoma Retinoblastoma is the prototype of diseases caused by a pathoge...

Ch16 · Pt11 CHAPTER 16 — Cancer Genetics and Genomics 357 in one or more of the retinoblasts already carrying a heterozygous RB1 pathogenic variant. Because the chance of a second hit is so great, heterozygotes for the disorder often have tumors arising at multiple sites, which may be multifocal tumors in one eye or both eyes (bilateral retinoblastoma), as well as less commonly in the pineal gland (referred to as trilateral retinoblastoma). The occurrence of a second hit is, however, a matter of chance and does not occur 100% of the time; thus the penetrance of heritable retinoblastoma is high (>90%) but not complete. The other 60% of cases of retinoblastoma are sporadic; in these cases, both RB1 alleles in a single retinal cell have been mutated or inactivated independently by chance, and the child does not carry a pathogenic RB1 variant in the germline. Because two hits in the same cell is a statistically rare event, there is usually only a single clonal tumor: the retinoblastoma is found at one location (unifocal) in one eye only. However, a unilateral tumor does not guarantee that the child does not have the heritable form of retinoblastoma because 15% of patients with unilateral retinoblastoma have a germline pathogenic RB1 variant. Another difference between hereditary and sporadic tumors is that the average age at onset of the sporadic form is in early childhood— later than in infants with the heritable form (see Fig. 16.6)—reflecting the longer time typically needed for two somatic mutations, rather than one, to occur. In a few patients with retinoblastoma, the variant responsible is a cytogenetically detectable deletion or translocation of the portion of chromosome 13 containing the RB1 gene. Such chromosomal changes, if they also disrupt genes adjacent to RB1, may cause a contiguous gene deletion syndrome involving varying degrees of developmental delay, congenital anomalies, and dysmorphic features. Nature of the Second Hit. Typically, for retinoblastoma as well as for the other hereditary cancer syndromes, the first hit is an inherited pathogenic variant; that is, a change in the DNA sequence. The second hit, however, can be caused by a variety of genetic, epigenetic, or genomic mechanisms (see Fig. 16.8). Although it is most often a somatic mutation, loss of function without mutation, such as occurs with epigenetic silencing (see Chapter 3), has been observed. Although a number of mechanisms have been documented, the common theme is loss of function of RB1. The RB1 gene product, p 110 Rb 1, is a phosphoprotein that normally regulates entry of the cell into the S phase of the cell cycle (see Chapter 2). Thus loss of the RB1 gene and/or absence of the normal RB1 gene product (by any mechanism) deprives cells of an important checkpoint and allows uncontrolled proliferation (see Table 16.2). Loss of Heterozygosity. In addition to mutation and epigenetic silencing, a novel and important genomic mechanism was uncovered by geneticists who compared DNA polymorphisms at the RB1 locus in DNA from normal cells to those in the retinoblastoma tumor from the same patient. Individuals with retinoblastoma who were informative by being heterozygous at polymorphic loci flanking the RB1 locus in normal tissues (see Fig. 16.8) frequently had tumors with alleles from only one of their two chromosome 13 homologues. This reflected a loss of heterozygosity (LOH) in tumor DNA in and around the RB1 locus. Furthermore, in familial cases, the retained chromosome 13 markers were the ones inherited from the affected parent. Thus, in these cases, LOH represents the second hit. LOH may occur by interstitial deletion, or by mechanisms such as mitotic recombination or monosomy 13 due to nondisjunction (see Fig. 16.8). LOH is the most common mutational mechanism by which the function of the remaining normal RB1 allele is disrupted in heterozygotes, although each of the mechanisms shown in Fig. 16.8 has been documented. LOH is a feature of a number of cancers, both heritable and sporadic, and is often considered evidence for a TSG in the region of LOH. Hereditary Breast Cancer due to Pathogenic Variants in BRCA1 or BRCA2 Breast cancer is common, with 250,000 women diagnosed annually in the United States alone. It is estimated that ~5% of breast cancer cases are due to a highly penetrant dominantly inherited mendelian predisposition that increases the risk for female breast cancer four- to sevenfold over the 12% lifetime risk observed in the general female population. In these families, one often sees features characteristic of hereditary (as opposed to sporadic) cancer: multiple affected individuals, earlier age at onset, frequent multifocal or bilateral disease or a second independent primary breast tumor, and additional primary cancers in other tissues such as ovary and pancreas. Although a number of genes in which pathogenic variants cause highly penetrant mendelian forms of breast cancer have been discovered from family studies, the two genes responsible for the majority of all hereditary breast cancers are BRCA1 and BRCA2 (Case 7). Together, these two TSGs account for approximately one-half and one-third, respectively, of autosomal dominant familial breast cancer. Thousands of pathogenic variants in both genes have now been catalogued. Pathogenic variants in BRCA1 and BRCA2 are also associated with a significant increase in the risk for ovarian and fallopian duct cancer. Moreover, pathogenic variants in BRCA2 and, to a lesser extent, BRCA1 also account for 10% to 20% of all male breast cancer and increase the risk for male breast cancer 10- to 60-fold over the 0.1% lifetime risk in the general population (Table 16.3). BRCA2 is also the most commonly mutated gene observed in men with metastatic prostate cancer. The gene products of BRCA1 and BRCA2 are nuclear proteins contained within the same multiprotein ▶

CHAPTER 16 — Cancer Genetics and Genomics 357 in one or more of the retinoblasts already carrying a heterozygous RB1 pathogenic variant. Because the chance of a second hit is so great, heterozygotes f...

Ch16 · Pt12 358 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE complex. This complex has been implicated in the cellular response to double-stranded DNA breaks, such as those occur ring during homologous recombination or because of damage to DNA. As might be expected for any TSG, tumor tissue from heterozygotes for BRCA1 and BRCA2 pathogenic variants frequently demonstrates LOH with loss of the normal allele. Moreover, germline pathogenic variants in BRCA1/2 also lead to tumor-specific phenotypes in breast and ovarian cancer as reflected by signature 3 or BRCAness characterized by high mutation burden of multiple types. Penetrance of BRCA1 and BRCA2 Pathogenic Variants. Presymptomatic detection of women at risk for breast cancer as a result of any of these susceptibility genes relies on detecting clearly pathogenic variants. For the purposes of patient management and counseling, it would be helpful to know the lifetime risk for development of breast cancer in individuals, whether male or female, carrying particular variants in BRCA1 and BRCA2, compared with the risk in the general population (see Table 16.3). Initial studies showed a greater than 80% risk for breast cancer by the age of 70 years in women heterozygous for BRCA1 pathogenic variants, with a somewhat lower estimate for BRCA2 variant carriers. These calculations relied on estimates of cancer risk in female relatives within families ascertained because breast cancer had already occurred many times in the family (i.e., families in which the particular BRCA1 or BRCA2 pathogenic variant was highly penetrant). When similar risk estimates were made from population-based studies, however, in which women carrying BRCA1 and BRCA2 pathogenic variants were not selected because they were members of families in which many cases of breast cancer had already developed, the risk estimates were lower and ranged from 40% to 50% by the age of 70 years. The discrepancy between the penetrance of pathogenic variants in families with multiple occurrences of breast cancer and the penetrance in women identified by population screening and not by family history suggests that other genetic or environmental factors must play a role in the ultimate penetrance of BRCA1 and BRCA2 pathogenic variants. In addition to pathogenic variants in BRCA1 and BRCA2, pathogenic variants in other genes can also cause autosomal dominantly inherited breast cancer syndromes, albeit less commonly. These include the LFS, hereditary diffuse gastric and lobular breast cancer, Peutz-Jeghers syndrome, and Cowden syndrome. These conditions have lifetime breast cancer risks that approach those seen in carriers of BRCA1 or BRCA2 pathogenic variants, as well as risks for other cancers such as sarcomas, brain tumors, and carcinomas of the stomach, thyroid, and small intestine. Clinicians faced with a family with multiple affected individuals with breast cancer often look for distinguishing signs in the patient and family history to help guide the choice of which genes to test (see Box 16.2). However, the rapid decline in the cost of gene and exome sequencing has allowed the development of gene panels in which multiple genes can be simultaneously analyzed, often at a cost that is equivalent to or even less than what was charged previously to analyze just one or two genes. Many breast and ovarian cancer panels include genes associated with moderately increased risk of breast and ovarian cancer (i.e., ATM, CHEK2, PALB2, BRIP1, RAD51C, and RAD51D). Hereditary Colon Cancer Colorectal cancer, a malignancy of the epithelial cells of the colon and rectum, is one of the most common forms of cancer. It affects ~1.3 million individuals worldwide per year (150,000 of whom are in the United States) and is responsible for ~10% to 15% of all cancer. Most cases are sporadic, but a small proportion of colon cancer cases are familial, among which are two autosomal dominant conditions: FAP and LS, along with their variants. Familial Adenomatous Polyposis. FAP and its subvariant, Gardner syndrome, together have an incidence of ~1 per 10,000. In FAP, benign adenomatous polyps numbering in the many hundreds develop in the colon TABLE 16.3 Lifetime Cancer Risks in Carriers of BRCA1 or BRCA2 Pathogenic Variants Compared to the General Population Cancer Type General Population Risk Cancer Risk When Pathogenic Variant Present BRCA1 BRCA2 Breast in females 12% 50–80% 40–70% Second primary breast in females 3.5% within 5 yr Up to 11% 27% within 5 yr 12% within 5 yr 40–50% at 20 yr Ovarian 1–2% 24–40% 11–18% Male breast 0.1% 1–2% 5–10% Prostate 15% (N. European origin) 18% (black individuals) <30% <39% Pancreatic (both sexes) 0.50% 1–3% 2–7% Data from Petrucelli N, Daly MB, Pal T. BRCA1- and BRCA2-Associated Hereditary Breast and Ovarian Cancer. 1998 Sep 4 [Updated 2022 May 26]. In: Adam MP, Everman DB, Mirzaa GM, et al., editors. Gene Reviews® [Internet]. Seattle (WA): University of Washington, Seattle; 1993-2022. Available from: http://www.ncbi. nlm.nih.gov/books/NBK1247/. ▶

358 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE complex. This complex has been implicated in the cellular response to double-stranded DNA breaks, such as those occur ring during homologou...

Ch16 · Pt13 CHAPTER 16 — Cancer Genetics and Genomics 359 during the first 2 decades of life. In almost all cases, one or more of the polyps become malignant. Surgical removal of the colon (colectomy) prevents the development of colorectal malignancy. FAP is caused by autosomal dominantly inherited heterozygous loss-of-function variants in a TSG known as APC (so-named because the condition used to be called adenomatous polyposis coli). Gardner syndrome is also due to pathogenic variants in APC and is therefore allelic to FAP. Patients with Gardner syndrome have, in addition to the adenomatous polyps with malignant transformation seen in FAP, extracolonic anomalies, including osteomas of the jaw and desmoids, which are tumors arising in the muscle of the abdominal wall. Although the relatives of an individual affected with Gardner syndrome who also carry the same APC pathogenic variant tend to also show the extracolonic manifestations of Gardner syndrome, the same variant in unrelated individuals has been found to cause only FAP. Thus whether an individual has FAP or Gardner syndrome is not simply due to which pathogenic variant is present in the APC gene but is likely affected by variation elsewhere in the genome. Lynch Syndrome. Approximately 2% to 4% of cases of colon cancer are attributable to LS (Case 29). LS is characterized by autosomal dominant inheritance of colon cancer in association with a small number of adenomatous polyps that begin during early adulthood. The number of polyps is generally quite small in comparison to the hundreds to thousands of adenomatous polyps seen with FAP. Nonetheless, polyps in LS have high potential to undergo malignant transformation. Heterozygotes for pathogenic variants in MLH1, one of the most penetrant LS genes, have an ~80% lifetime risk for colon cancer; female heterozygotes also have a ~40% risk for endometrial cancer. There are also additional risks of 10% to 20% for cancer of the biliary or urinary tract and the ovary. Sebaceous gland tumors of the skin may be the first presenting sign in LS (in which case it is a variant called Muir-Torre syndrome); thus the presence of such tumors in a patient should raise suspicion of a possible hereditary colon cancer syndrome. LS results from loss-of-function variants in one of four DNA repair genes (MLH1, MSH2, MSH6, and PMS2) that encode MMR proteins. Although all four of these genes have been implicated in LS in different families, MLH1 and MSH2 are together responsible for the majority of LS, whereas MSH2 and PMS2 are often associated with a lesser degree of MMR deficiency and lower penetrance. Like BRCA1 and BRCA2, the LS MMR genes are TSGs involved in maintaining the integrity of the genome. Unlike BRCA1 and BRCA2, however, the LS genes are not involved in double-stranded DNA break repair. Instead, their role is to repair incorrect DNA base pairing (i.e., pairing other than A with T or C with G) that can arise during DNA replication. At the cellular level, the most striking phenotype of cells lacking MMR proteins is an enormous increase in both point mutations and mutations occurring during replication of simple DNA repeats, such as segments containing a string of the same base, for example (A)n, or a microsatellite, such as (TG)n (see Chapter 4). Microsatellites are believed to be particularly vulnerable BOX 16.2 DIAGNOSTIC CRITERIA FOR HEREDITARY CANCER SYNDROMES Li-Fraumeni Syndrome (LFS): Revised Chompret Criteria Proband with tumor belonging to LFS tumor spectrum (e.g., soft tissue sarcoma, osteosarcoma, CNS tumor, premenopausal breast cancer, adrenocortical carcinoma) before age 46 years AND at least one first- or second-degree relative with LFS tumor (except breast cancer if proband has breast cancer) before age 56 years or with multiple tumors; OR Proband with multiple tumors (except multiple breast tumors), two of which belong to LFS tumor spectrum and first of which occurred before age 46 years; OR Patient with adrenocortical carcinoma or choroid plexus tumor (i.e., rhabdomyosarcoma of embryonal anaplastic subtype) or medulloblastoma (SHH subtype) or childhood acute lymphoblastic leukemia (low) hypodiploid, irrespective of family history Hereditary Diffuse Gastric and Lobular Breast Cancer Syndrome Family history of diffuse gastric cancer with two or more cases of gastric cancer, with at least one diffuse gastric cancer diagnosed before age 50 years Family with multiple lobular breast cancers Peutz-Jeghers Syndrome Peutz-Jeghers–type hamartomatous polyps in the small intestine as well as in the stomach, large bowel, and extraintestinal sites, including the renal pelvis, bronchus, gallbladder, nasal passages, urinary bladder, and ureters Pigmented macules on the face, around oral mucosa and the perianal region, most pronounced in childhood Cowden Syndrome Early-onset breast cancer, particularly before age 40 Macrocephaly, especially ≥63 cm in males or ≥60 cm in females Thyroid cancer, particularly follicular type, before age 50 Goiter, Hashimoto thyroiditis Dysplastic gangliocytoma of the cerebellum (Lhermitte- Duclos disease) Intestinal hamartomas Esophageal glycogenic acanthosis Skin findings of tricholemmomas or penile freckling Papillomas of oral cavity From Bougeard G, Renaux-Petel M, Flaman JM, et al: Revisiting Li-Fraumeni syndrome from TP53 mutation carriers, J Clin Oncol 33(21):2345–2352, 2015. https://doi.org/10.1200/JCO.2014.59.5728; Kratz CP, Freycon C, Maxwell KN, et al: Analysis of the Li-Fraumeni spectrum based on an international germline TP53 variant data set: An International Agency for Research on Cancer TP53 database analysis, JAMA Oncol 7(12):1800–1805, 2021. https://doi.org/10.1001/ jamaoncol.2021.4398 ▶

CHAPTER 16 — Cancer Genetics and Genomics 359 during the first 2 decades of life. In almost all cases, one or more of the polyps become malignant. Surgical removal of the colon (colectomy) prevents th...

Ch16 · Pt14 360 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE to mismatch because slippage of the strand being synthesized on the template strand can occur more readily when a short tandem repeat is being synthesized. Such instability, referred to as the microsatellite instability- positive (MSI+) phenotype, occurs at two orders of magnitude higher frequency in cells lacking both copies of an MMR gene. The MSI+ phenotype is easily seen in DNA as three, four, or even more alleles of a microsatellite polymorphism in a single individual’s tumor DNA (Fig. 16.9). It is estimated that cells lacking both copies of an MMR gene may carry 100,000 mutations within simple repeats throughout the genome. Because of the increased mutation rate in these classes of sequence, loss of function of MMR genes will lead to somatic mutations in other driver genes. Two such driver genes have been isolated and characterized. The first is APC, whose normal function and role in FAP were described previously. The second is the gene TGFBR2, in which heterozygous germline pathogenic variants primarily cause a connective tissue disorder called Loeys- Dietz syndrome; however, cases of early-onset colon cancer have also been reported. TGFBR2 encodes transforming growth factor β receptor II, a serine-threonine kinase that inhibits intestinal cell division. Somatically, TGFBR2 is particularly vulnerable to mutation when MMR proteins are lost because it contains a stretch of 10 adenines encoding three lysines within its coding sequence; deletion of one or more of these As results in a frameshift and loss-of-function mutation. LS is an excellent example of how a gene, like MLH1, which has a global effect on mutation rate throughout the genome, can be a driver gene through its effect on other genes, such as TGFBR2, that are more specifically involved in driving the development of a cancer. Pathogenic Variants in Tumor Suppressor Genes Causing Autosomal Recessive Pediatric Cancer Syndromes As expected from the important role that DNA replication and repair enzymes play in mutation surveillance and prevention, inherited defects that alter the function of DNA repair enzymes can lead to a dramatic increase in the frequency of mutations of all types, including those that lead to cancer. Pathogenic variants in the LS MMR genes are frequent enough in the population for there to be rare individuals with two (biallelic) germline mutations in one of the LS genes. Although much rarer than autosomal dominant forms of LS just discussed, this condition, known as constitutional MMR deficiency (CMMRD), results in a markedly elevated risk for many cancers during childhood, including colorectal and small bowel cancer, as well as some cancers not associated with LS, such as leukemia and lymphoma and various types of brain tumors. The absence of effective MMR in these tumors leads to high tumor mutational burden and expression of neoantigens, which have been shown to be effective targets for immune checkpoint inhibition (immunotherapy) yielding dramatic tumor responses in some cases. This represents one of the first approaches to targeted therapy for cancers based on underlying germline pathogenic variants. Several other well-known autosomal recessive disorders, including xeroderma pigmentosum (Case 48), ataxia-telangiectasia, Fanconi anemia, and Bloom syndrome, are also due to loss of function of proteins required for normal DNA repair or replication. Patients with these rare conditions have a high frequency of somatic chromosome and gene mutations and, as a result, a markedly increased risk for various types of cancer, particularly leukemia or, in the case of xeroderma pigmentosum, skin cancers in sun-exposed areas. Clinically, radiography must be used with extreme caution, if at all, in patients with ataxia-telangiectasia, Fanconi anemia, and Bloom syndrome, and exposure to sunlight must be avoided in patients with xeroderma pigmentosum. Although these are rare autosomal recessive disorders, heterozygote carriers are common, and some appear to be at increased risk for malignant neoplasia. For example, Fanconi anemia, in which individuals are at risk for congenital anomalies, bone marrow failure, leukemia, and squamous cell carcinoma of the head and neck, is a chromosome instability syndrome resulting from biallelic pathogenic variants in one of at least 22 different genes involved in DNA and chromosome repair. In the aggregate, Fanconi anemia has a population frequency of approximately one to five per million, which translates to a carrier frequency of approximately one to two per 500. One of these Fanconi anemia genes turns out to be the known hereditary cancer gene BRCA2. Others include BRIP1, PALB2, and RAD51C (discussed in the Marker #1 N T N T N T Marker #2 Marker #3 Figure 16.9 Gel electrophoresis of three different microsatellite polymorphic markers in normal (N) and tumor (T) samples from a patient with a germline pathogenic variant in MSH2 and microsatellite instability. Although marker 2 shows no difference between normal and tumor tissues, genotyping at markers 1 and 3 reveals extra alleles (blue arrows), some smaller, some larger, than the alleles present in normal tissue. ▶

360 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE to mismatch because slippage of the strand being synthesized on the template strand can occur more readily when a short tandem repeat is bei...

Ch16 · Pt15 CHAPTER 16 — Cancer Genetics and Genomics 361 next section), which increase susceptibility to breast cancer in carriers of heterozygote pathogenic variants. Similarly, female heterozygotes for pathogenic variants in ATM (the gene responsible for ataxia-telangiectasia) have a twofold increased lifetime risk for breast cancer compared with controls and a fivefold higher risk for breast cancer before the age of 50 years. Thus heterozygotes for germline pathogenic variants in genes related to chromosome instability syndromes constitute a sizable pool of individuals at increased risk for cancer. Testing for Germline Pathogenic Variants Causing Hereditary Cancer As introduced earlier, although some sporadic cancers will be truly sporadic and due entirely to somatic mutation(s), other cancers that may appear to be sporadic likely reflect a predisposition to specific cancer(s) due to familial variants in one or more genes. This raises the possibility of using genetic testing to screen for germline pathogenic variants that might inform risk estimates for members of the general population or for families with insufficient family history to implicate a hereditary cancer syndrome. Here we illustrate the issues involved in the case of two common neoplasias: breast cancer and colorectal cancer. BRCA1 and BRCA2 Testing Identification of a germline pathogenic variant in BRCA1 or BRCA2 in a patient with breast cancer is of obvious importance for genetic counseling and cancer risk management for the patient’s children, siblings, and other relatives, who may or may not be at increased risk. Such testing is of course also important for the patient’s own management. For instance, in addition to removal of the cancer, a woman found to carry a BRCA1 pathogenic variant might also choose to have a prophylactic mastectomy of the unaffected breast or a bilateral oophorectomy simultaneously to reduce cancer risk while minimizing the number of separate surgeries and anesthesia exposures. Finding a pathogenic variant in the proband or a first-degree relative would also allow targeted testing in the rest of the family. Importantly, however, the fraction of all female breast cancer patients whose disease is caused by a germline pathogenic variant in either the BRCA1 or BRCA2 gene is small, with estimates that vary between 1% and 3% in populations unselected for family history of breast or ovarian cancer, or for age at onset of the disease. Male breast cancer is 100 times less common than female breast cancer, but when it occurs, the frequency of germline pathogenic variants in hereditary breast cancer genes, particularly BRCA2, is ~16%. Until quite recently, the cost of analysis of BRCA1 and BRCA2 was used to justify limiting testing to those patients most likely to be carrying a pathogenic variant, such as all male breast cancer patients and all women younger than 50 years with breast cancer, women with bilateral breast cancer, or women with first- and second- degree relatives with ovarian cancer or breast cancer. However, as the cost of sequencing falls, and large panels of breast cancer susceptibility genes, including BRCA1 and BRCA2, can now be analyzed for less than it cost previously to sequence just BRCA1 and BRCA2, testing guidelines are inevitably undergoing ongoing reevaluation. Testing at least BRCA1 and BRCA2 in all women with high-risk, early-stage, human epidermal growth factor receptor 2 (HER2)–negative breast cancer has gained further support as treatment with PARP inhibitors has been shown to increase survival in individuals with germline BRCA1/2 pathogenic variants. Colorectal Cancer Germline Testing LS is an autosomal dominant cancer predisposition syndrome with up to an 80% lifetime risk of cancer of multiple types. LS patients harbor germline pathogenic variants in the MMR genes (MLH1, MSH2, MSH6, PMS2, and EPCAM promoter deletion). Only 4% of patients with colon cancer, not selected for a family history of cancer, carry a germline pathogenic variant in one of these genes; an even smaller fraction carry pathogenic variants in APC, causing FAP. As with breast cancer, geneticists need to balance the cost and yield of sequencing hereditary colorectal cancer genes in every patient with colon cancer against the obvious importance of finding such a pathogenic variant for the patient and their family. Also of clinical benefit in identifying individuals with LS is the rationale for immunotherapy when tumors exhibit a characteristic high mutational burden. For LS, clinical factors such as multiple polyps, early age at onset (age <50 years), the location of the tumor in more proximal portions of the colon, multiple synchronous or metachronous colorectal cancers, a family history of colorectal or other cancers (particularly endometrial cancer), and cancer in relatives younger than 50 years of age, all boost the probability that a patient with colon cancer is carrying a pathogenic variant in an MMR gene. Molecular studies of the tumor tissue to look for evidence of the MSI+ phenotype (as discussed earlier in this chapter) or absence of MSH2 and/or MSH6 protein by antibody staining in the tumor also increase the probability that an individual with colorectal cancer carries a germline pathogenic variant in an MMR gene. Unfortunately, loss of MLH1 protein staining in tumors due to promoter methylation is a frequent epigenetic finding in sporadic colon cancers and is therefore much less predictive of LS. Combining clinical and molecular criteria allows the identification of a subset of colorectal cancer patients in whom the probability of finding a germline pathogenic variant in an MMR gene is much greater than 4%. These patients are clearly the most cost-effective group in which sequencing could be recommended. However, as with all such attempts at cost effectiveness, limiting the number of patients studied to increase the yield of patients with positive results inevitably results in missing a sizable minority ▶

CHAPTER 16 — Cancer Genetics and Genomics 361 next section), which increase susceptibility to breast cancer in carriers of heterozygote pathogenic variants. Similarly, female heterozygotes for pathoge...

Ch16 · Pt16 362 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE (20%) of patients with LS. Again, the cost of testing must be reevaluated as technology gets less expensive and the therapeutic importance of identifying cancer predisposition is becoming clearer. More detailed discussions of genetic testing will be presented in Chapter 19. For FAP, the presence of hundreds of adenomatous polyps at an early age, multiple sebaceous adenomas, or the extracolonic manifestations of Gardner syndrome are sufficient to trigger germline testing for an APC pathogenic variant. There are, however, certain APC pathogenic variants that result in many fewer polyps and no extracolonic features (referred to as attenuated FAP). Attenuated FAP can be confused clinically with LS, but the tumors generally lack MMR defects or microsatellite instability. FAMILIAL OCCURRENCE OF CANCER Cancer can also show increased incidence in families without a clear-cut mendelian pattern of inheritance. It is estimated that as many as 20% of all breast cancers occurring in families that lack a clear, highly penetrant mendelian disorder nonetheless have a significant genetic contribution, as revealed by twin and family studies. The observed increase in cancer risk when relatives are affected may be due to pathogenic variants in a single gene but with penetrance that is sufficiently reduced to obscure any mendelian inheritance pattern. For example, pathogenic variants PALB2 can increase lifetime risk for breast cancer to ~25% by age 55 and ~40% by age 85. A lack of increased breast cancer risk in men with PALB2 pathogenic variants further obscures the inheritance pattern, although there is a significantly increased risk for pancreatic cancer. Germline pathogenic variants in BRIP1 and RAD51C have similar effects in the setting of ovarian cancer. The bulk of familial cancer is, however, likely to have a complex etiology caused by both genetic and shared environmental factors (see Chapter 9). The degree of complex familial cancer risk can be assessed by epidemiologic studies that compare how often the disease occurs in relatives versus the general population. The age-specific incidence of many forms of cancer in family members of probands is increased over the incidence of the same cancer in an age-matched cohort in the general population (Fig. 16.10). This increased risk has been observed in individuals whose first-degree relatives (parent, sibling, or child) are affected by a wide variety of different cancers, with an even greater increase in incidence when two first-degree relatives are affected. For example, population-based epidemiologic studies have shown that ~5% of all individuals in North America and Western Europe will develop colorectal cancer in their lifetime, but the lifetime risk is increased two- to threefold if one first-degree relative is affected. In agreement with the frequently complex inheritance of cancer risk, genome-wide association studies (see Chapter 9) have identified more than 150 mostly common variants associated with a variety of cancers. Prostate cancer, in particular, shows multiple associations with variants in homologous recombination damage genes and with single nucleotide polymorphisms located in the intergenic or intronic regions of over a dozen loci in other genes. However, odds ratios for most of these associations are less than 2.0, and many are less than 1.3, therefore accounting for at most 20% of the observed familial risk for prostate cancer. Overall, then, although the role of inherited variants in the genome is clear, we cannot yet explain in detail the increased familial tendencies of most cancers. Whether common variants do not capture all of the risk or there are unrecognized environmental exposures in common between family members remains nonexclusive possibilities. SPORADIC CANCER Previously we introduced the concept of activation of oncogenes by a variety of mutational mechanisms (see Fig. 16.3). Here we explore these mechanisms and their effects in greater detail, particularly in the context of sporadic cancers. Activation of Oncogenes by Point Variation Many mutated oncogenes were first identified by molecular studies of cell lines derived from sporadic cancers. One of the first activated oncogenes discovered was a mutant RAS gene derived from a bladder carcinoma cell line. RAS encodes one of a large family of small guanosine triphosphate (GTP)–binding proteins (G proteins) that serve as molecular on-off switches to activate or inhibit downstream molecules. Remarkably, the activated oncogene and its counterpart proto- oncogene differed at only a single nucleotide. The alteration led to synthesis of an abnormal Ras protein that was able to signal continuously, thus stimulating cell division and transforming it into a tumor. RAS point mutations, almost exclusively confined to one of three amino acids (12, 13, or 61), are now known in many tumors, and the genes in the RAS pathway have been shown experimentally to be the mutational target of known carcinogens, a finding that supports a role for mutated RAS pathway genes in the development of many cancers. To date, nearly 50 human proto-oncogenes have been identified as drivers in sporadic cancer. Only a few of these proto-oncogenes have also been found to be implicated in a hereditary cancer syndrome. Activation of Oncogenes by Chromosome Translocation or Fusions As pointed out previously (see Fig. 16.3), oncogene activation is not always the result of a DNA mutation. In some instances, a proto-oncogene is activated by a ▶

362 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE (20%) of patients with LS. Again, the cost of testing must be reevaluated as technology gets less expensive and the therapeutic importance o...

Ch16 · Pt17 CHAPTER 16 — Cancer Genetics and Genomics 363 chromosomal change, typically a translocation. More than 40 oncogenic chromosome translocations have been described to date, primarily in sporadic leukemias and lymphomas but also in a few rare connective tissue sarcomas. Although originally detected only by cytogenetic analysis, such alterations can be detected now by whole genome or RNA sequence analysis, even using cell-free DNA in plasma samples from cancer patients. In some cases, translocation breakpoints lie within the introns of two genes, thereby fusing two genes into one abnormal gene that encodes a chimeric protein with novel oncogenic properties. The best-known example is the translocation between chromosomes 9 and 22, the Philadelphia chromosome that is seen in chronic myelogenous leukemia (CML) (Fig. 16.11) (Case 10). The translocation moves the proto-oncogene ABL1, a tyrosine Nervous system Testis Hodgkin disease Thyroid gland Melanoma Ovary Non-Hodgkin Cervix Breast Prostate Colon Lung Bladder Rectum Skin Endometrium Stomach Kidney Pancreas Myeloma One parent affected Standardized incidence ratio 8 6 4 2 1 Cancer site Nervous system Testis Hodgkin disease Thyroid gland Melanoma Ovary Non-Hodgkin Cervix Breast Prostate Colon Lung Bladder Rectum Skin Endometrium Stomach Kidney Pancreas Myeloma One sibling affected Standardized incidence ratio 40 30 20 10 1 Cancer site Figure 16.10 Standardized incidence ratios (SIRs) for cancers at various sites in first-degree relatives (parent, sibling, or child) of an affected person. SIR is similar to the relative risk ratio (λr) based on prevalence of disease (as described in Chapter 10), except SIR is the ratio of the incidence of cases of cancer in relatives divided by the number expected from the incidence in age-matched controls. Error bars reflect 95% confidence limits on the SIRs. (Adapted from Hemminki K, Sundquist J, Lorenzo Bermejo J: Familial risks for cancer as the basis for evidence-based clinical referral and counseling, Oncologist 13:239–247, 2008.) ▶

CHAPTER 16 — Cancer Genetics and Genomics 363 chromosomal change, typically a translocation. More than 40 oncogenic chromosome translocations have been described to date, primarily in sporadic leukemi...

Ch16 · Pt18 364 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE kinase, from its normal position on chromosome 9q to a gene of unknown function, BCR, on chromosome 22q. The translocation results in the synthesis of a novel, chimeric protein, BCR-ABL1, containing a portion of the normal Abl protein with increased tyrosine kinase activity. The enhanced tyrosine kinase activity of the novel protein encoded by the chimeric gene is the primary event causing the chronic leukemia. Highly effective drug therapies for CML, such as imatinib, have been developed based on inhibition of this tyrosine kinase activity. In other cases, a translocation activates an oncogene by placing it downstream of a strong, constitutive promoter belonging to a different gene. Burkitt lymphoma is a B-cell tumor in which the MYC proto-oncogene is translocated from its normal position at 8q24 to a position distal to the immunoglobulin heavy chain locus at 14q32 or the immunoglobulin light chain genes on chromosomes 22 and 2. The function of the Myc protein is still not entirely known, but it appears to be a transcription factor with powerful effects on the expression of a number of genes involved in cellular proliferation, as well as on telomerase expression (see later discussion). The translocation brings enhancer or other transcriptional activating sequences, normally associated with the immunoglobulin genes, near the MYC gene (Table 16.4). These translocations allow unregulated MYC expression, resulting in uncontrolled cell division. Telomerase as an Oncogene Another type of oncogene is the gene encoding telomerase, a reverse transcriptase that is required to synthesize the hexamer repeat TTAGGG, a component of telomeres at the ends of chromosomes. Telomerase is needed because, during normal semiconservative replication of DNA (see Chapter 2), DNA polymerase can only add nucleotides to the 3′ end of DNA and cannot complete the synthesis of a growing strand all the way to the very end of that strand on the chromosome arm; thus, in the absence of a specific mechanism to allow replication of telomeres, the end of each chromosome arm would shorten significantly with each and every cell division. In human germline cells and embryonic cells, telomeres contain ~15 kb of the telomeric repeat. As cells differentiate, telomerase activity declines in somatic tissues; as telomerase function is lost, telomeres shorten, with a loss of ~35 bp of telomeric repeat DNA with each cell division. After hundreds of cell divisions, the chromosome ends become damaged, leading cells to stop dividing and enter G0 of the cell cycle; the cells will ultimately undergo apoptosis and die. In contrast, in highly proliferative cells of tissues such as bone marrow, telomerase expression persists, allowing self-renewal. Similarly, telomerase persistence is TABLE 16.4 Characteristic Chromosome Translocations in Selected Human Malignant Neoplasms Neoplasm Chromosome Translocation Percentage of Cases Proto-oncogene Affected Burkitt lymphoma t(8;14)(q 24;q 32) 80 MYC t(8;22)(q 24;q 11) 15 t(2;8)(q 11;q 24) 5 Chronic myelogenous leukemia t(9;22)(q 34;q 11) 90–95 BCR-ABL1 Acute lymphocytic leukemia t(9;22)(q 34;q 11) 10–15 BCR-ABL1 Acute lymphoblastic leukemia t(1;19)(q 23;p 13) 3–6 TCF3-PBX1 Acute promyelocytic leukemia t(15;17)(q 22;q 11) ≈95 RARA-PML Chronic lymphocytic leukemia t(11;14)(q 13;q 32) 10–30 BCL1 Follicular lymphoma t(14;18)(q 32;q 21) ≈100 BCL2 Based on Croce CM: Role of chromosome translocations in human neoplasia, Cell 49:155–156, 1987; Park M, van de Woude GF: Oncogenes: Genes associated with neoplastic disease. In Scriver CR, Beaudet AL, Sly WS, et al, editors: The molecular and metabolic bases of inherited disease, ed 6, New York, 1989, Mc Graw- Hill, pp 251–276; Nourse J, Mellentin JD, Galili N, et al: Chromosomal translocation t(1;19) results in synthesis of a homeobox fusion mRNA that codes for a potential chimeric transcription factor, Cell 60:535–545, 1990; Borrow J, Goddard AD, Sheer D, et al: Molecular analysis of acute promyelocytic leukemia breakpoint cluster region on chromosome 17, Science 249:1577–1580, 1990. 5' 3' 5' 3' 9 der(9) 3' 5' 5' 3' ABL1 der(22) Ph 1 BCR-ABL1 22 BCR Figure 16.11 The Philadelphia chromosome translocation, t(9;22) (q 34;q 11). The Philadelphia chromosome (Ph 1) is the derivative chromosome 22, which has exchanged part of its long arm for a segment of material from chromosome 9q that contains the ABL1 oncogene. Formation of the chimeric BCR-ABL1 gene on the Ph 1 chromosome is the critical genetic event in the development of chronic myelogenous leukemia. ▶

364 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE kinase, from its normal position on chromosome 9q to a gene of unknown function, BCR, on chromosome 22q. The translocation results in the sy...

Ch16 · Pt19 CHAPTER 16 — Cancer Genetics and Genomics 365 observed in many tumors, which permits tumor cells to proliferate indefinitely. In some cases, increased telomerase activity results from chromosome or gene mutations that directly up-regulate the telomerase gene; in others, telomerase may be only one of many genes whose expression is altered by a transforming oncogene, such as MYC. The extent of oncogenesis resulting from disorders of telomere biology is still being recognized, as evidenced by classic telomere syndromes in which telomere attrition is a characteristic associated with cancer, and in disorders in which there is alternative lengthening of telomeres. Loss of Tumor Suppressor Genes in Sporadic Cancer TP53 and RB1 in Sporadic Cancers Although LFS, caused by dominantly inherited germline pathogenic variants in TP53, is a rare familial syndrome, somatic mutation of TP53 is one of the most common genetic alterations seen in sporadic cancer (see Table 16.2). Mutations in TP53, deletion of the segment of chromosome 17p that includes TP53, or loss of the entire chromosome 17 are frequently seen in a wide range of sporadic cancers. These include breast, ovarian, bladder, cervical, esophageal, colorectal, skin, and lung carcinomas; glioblastoma; osteogenic sarcoma; and hepatocellular carcinoma. TP53 is the most commonly mutated gene in cancer. The retinoblastoma gene RB1 is also frequently mutated in many sporadic cancers. For example, 13q14 LOH in human breast cancers is associated with loss of RB1 mRNA in the tumor tissue. In other cancers, the RB1 gene is intact and its mRNA appears to be at or near normal levels, yet the Rb 1 protein is deficient. This anomaly has now been explained by the recognition that RB1 can be down-regulated in association with overexpression of the oncomir mi R-106a, which targets RB1 mRNA and blocks its translation. CYTOGENETIC CHANGES IN CANCER Aneuploidy and Aneusomy As introduced in Chapter 5, cytogenetic changes are hallmarks of cancer, whether sporadic or familial, particularly in later and more malignant or invasive stages of tumor development. Constitutional chromosomal abnormalities also predispose to cancer, as in Down syndrome (acute lymphoblastic leukemia and acute myeloid leukemia), Turner syndrome (germ cell tumors), and Klinefelter (germ cell tumors, breast cancer). Somatic cytogenetic alterations suggest that a critical element of cancer progression includes defects in genes involved in maintaining chromosome stability and integrity and ensuring accurate mitotic segregation. Initially, most of the cytogenetic studies of tumor progression were carried out in leukemias because the tumor cells were amenable to being cultured and karyotyped by standard methods. For example, when CML, with the t(9;22) Philadelphia chromosome, evolves from the typically indolent chronic phase to a severe, life-threatening blast crisis, there may be several additional cytogenetic abnormalities, including numeric or structural changes, such as a second copy of the 9;22 translocation chromosome or an isochromosome 17q. In advanced stages of other forms of leukemia, other translocations are common. In contrast, a vast array of chromosomal abnormalities is seen in most solid tumors. Cytogenetic abnormalities found repeatedly in a specific type of cancer are likely to be driver events involved in the initiation or progression of the malignant neoplasm. A current focus of cancer research is to develop a comprehensive cytogenetic and genomic definition of these abnormalities, many of which result in enhanced proto-oncogene expression or the loss of TSG alleles. Medulloblastoma is a salient example of this comprehensive molecular and cytogenetic characterization for which four distinct types are described: SHH, Wnt, Group 3, and Group 4. Each has characteristic clinical features and distinct treatment-related outcomes. Genome sequencing is replacing cytogenetic analysis in many instances because it provides a level of sensitivity and precision well beyond detection of cytologically visible genome changes. Furthermore, RNA (cDNA) fusion detection utilizing NGS is also commonly deployed to detect somatic oncogenic fusions, and technologies now exist that enable detection of fusions without prior knowledge of the fusion partner or translocation breakpoints. Gene Amplification In addition to translocations and other rearrangements, another cytogenetic aberration seen in many cancers is gene amplification, a phenomenon in which many additional copies of a segment of the genome are present in the cell (see Fig. 16.3). Gene amplification is common in cancers, including neuroblastoma, squamous cell carcinoma of the head and neck, colorectal cancer, and malignant glioblastomas of the brain. Amplified segments of DNA are readily detected by comparative genome hybridization or genome sequencing and appear as two types of cytogenetic change in routine chromosome analysis: double minutes (very small accessory chromosomes) and homogeneously staining regions that do not band normally and contain multiple, amplified copies of a particular DNA segment. How and why double minutes and homogeneously staining regions develop are poorly understood, but amplified regions are known to include extra copies of proto-oncogenes such as the genes encoding Myc, Ras, and epithelial growth factor receptor, which stimulate cell growth, block apoptosis, or both. For example, amplification ▶

CHAPTER 16 — Cancer Genetics and Genomics 365 observed in many tumors, which permits tumor cells to proliferate indefinitely. In some cases, increased telomerase activity results from chromosome or ge...

Ch16 · Pt20 366 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE of the MYCN proto-oncogene encoding N-Myc is an important clinical indicator of prognosis in the childhood cancer neuroblastoma. MYCN is amplified more than 200-fold in 40% of advanced stages of neuroblastoma; despite aggressive treatment, only 30% of patients with advanced disease survive 3 years. In contrast, MYCN amplification is found in only 4% of early- stage neuroblastoma, and the 3-year survival is 90%. Amplification of genes encoding the targets of chemotherapeutic agents has also been implicated as a mechanism for the development of drug resistance in patients previously treated with chemotherapy. THE ROLE OF EPIGENETICS IN CANCER Some cancers (e.g., breast or prostate) are readily diagnosed based on the organ in which they arise. Other cancer types (such as central nervous system [CNS] or sarcomas) are more difficult to diagnose. Tumors in these tissue types may have similar histologies but very different biologic and prognostic characteristics. Distinguishing these can be addressed using DNA methylation (DNAm) analysis. Another difficult scenario addressed by DNAm is cancer originating from an unknown primary: disease that is metastatic at diagnosis, but the primary cancer it arose from is unclear. DNAm analysis is increasingly incorporated into the diagnostic investigation of various cancers due to its precision in defining specific tumor types, especially those that evade definition by other types of molecular and pathologic analyses (i.e., some brain tumors). For these situations, DNAm analysis is likely superior to gene expression signatures and is closer to application in clinical practice. DNAm signatures can also aid in risk assessment, diagnosis, and prognostication. Cancer, although conventionally considered a genetic disorder, typically involves genome-wide epigenetic dysregulation, including alterations to DNAm, histone modifications, chromatin remodeling, and micro RNA. These changes can support the development of cancer by a variety of mechanisms. There is generalized DNAm dysregulation in cancer, which contributes to tumor development in a variety of ways. Generally, Cp G islands near gene promoters will gain methylation, which can be associated with changes in that gene’s expression. Conversely, hypomethylation events are more common but not associated with specific genomic features. It is unclear whether hypomethylation in cancer plays a functional role, but it appears to be related to genome instability, manifested through cytogenetic events such as aneuploidy. Furthermore, silencing of certain critical homeostatic genes (e.g., DNA repair genes) can lead to MMR deficiency and hypermutability. Further genome-wide alterations in DNAm can also be downstream consequences of variants in chromatin modifier genes (e.g., genome-wide hypermethylation due to DNMT3A gain of function or TET2 loss of function). Finally, loss-of-function sequence variants in epigenetic regulators have been identified as a hallmark of etiology in several cancers: in certain hematologic malignancies and variants in epigenetic regulators, including MLL1 and CBP/p 300, which normally mediate lineage specification/differentiation and cause blocks in transitions to correct commitment pathways, resulting in proliferation of undifferentiated cells that manifest as leukemia. In brain tumors, H3-K27M plays a role in midline glioma development. Epigenetic changes involving chromosome 11p15.5 predispose to Wilms tumor and hepatoblastoma, as in Beckwith-Wiedemann syndrome (Case 6). Improved Diagnostic Yield with Methylation Testing The introduction of genome-wide DNAm profiling of tumors has been transformative in diagnostics. Importantly, DNAm-based tumor classification is as reliable as gene expression; it has emerged as a promising approach to differentiate tumor types and to improve diagnostics and prognostics. This is exemplified by CNS tumors and sarcomas, which can be more precisely defined by DNAm profiling than with traditional pathologic subgroups. This results from DNAm not only providing data about the current state of cellular modification but defining the tumor’s cell type of origin. It appears that the state of cell differentiation at the time of tumor initiation remains relatively stable during tumor development/progression. Furthermore, DNAm, as a method of tumor subgrouping, provides a means to classify medulloblastoma subgroups for clinical trials and therapy modification. The World Health Organization (WHO) now recognizes medulloblastoma as four different diseases based on these subgroups initially defined by DNAm. Therapies Targeting Epigenetic Modifications Epigenetic changes are reversible and therefore represent a viable target for therapeutic intervention. In the cancer realm, DNAm signatures are not only used for treatment selection, based on optimized diagnostics, but also to identify new treatment targets. Significant progress has been made in the development of pharmaceutical agents that target histones and DNAm. Some, including DNA methyltransferase inhibitors, which reverse aberrant hypermethylation, have been approved for clinical use for treatment of a variety of cancers, including hematologic malignancies and solid tumors. There are several other epigenetic agents currently available as standard-of-care cancer treatments. Romidepsin, a histone deacetylase, has been approved by the US Food and Drug Administration for cutaneous T-cell lymphoma—a painful and disfiguring condition. Positive response rates are ~30%, and the median duration of response is longer than 1 year. As these epigenetic drugs are not curative, they are frequently combined with other treatments, including ▶

366 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE of the MYCN proto-oncogene encoding N-Myc is an important clinical indicator of prognosis in the childhood cancer neuroblastoma. MYCN is a...

Ch16 · Pt21 CHAPTER 16 — Cancer Genetics and Genomics 367 classic chemotherapies and immune checkpoint inhibitors, to broaden response rates among patients. In summary, although epigenetic therapies are still a work in progress, chromatin remains an important therapeutic target for investigation. One of the biggest limitations of epitargeted drug therapies is that they target epigenetic marks nonspecifically; there need to be more tailored therapies to reduce harm and improve outcomes. APPLYING GENOMICS TO INDIVIDUALIZE CANCER THERAPY Genomics is already having a major impact on diagnostic precision and optimization of therapy in cancer. In this section we describe how one such approach, gene expression profiling, is used to guide diagnosis and treatment. Gene Expression Profiling and Clustering to Identify Signatures Comparative hybridization techniques can be used to simultaneously measure the level of mRNA expression of some or all of the genes in any human tissue sample. A measurement of mRNA expression in a sample of tissue constitutes a gene expression profile specific to that tissue. Fig. 16.12 depicts a hypothetical, idealized situation of eight samples, four from each of two types of tumor, A and B, profiled for 100 different genes. The expression profile derived from expression arrays for this simple example is already substantial, consisting of 800 expression values. In a real expression profiling experiment, however, hundreds of samples may be analyzed for the expression of all human genes, producing a massive data set of millions of expression values. Organizing the data and analyzing them to extract key information are challenging problems that have inspired the development of sophisticated statistical and bioinformatic tools. Using such tools, one can organize the data to find groups of genes whose expression seems to correlate (i.e., increase or decrease together) between and among the samples. Grouping genes by their patterns of expression across samples is termed clustering. Clusters of gene expression can then be tested to determine if any correlate with particular characteristics of the samples of interest. For example, profiling might indicate that a cluster of genes with a correlated expression profile is found more frequently in samples from tumor A than from tumor B, whereas another cluster of genes with a Samples Individual sample profiles CLUSTERING INTO SIGNATURES EXPRESSION PROFILING Expression level Tumor A Samples Genes 1 25 27 33 40 51 83 22 30 35 38 56 88 1 2 99 100 Gene # ↑in A ↓in B ↓in A ↑in B ↓in B ↑in B 12345678 0.25 1 4.0 1 2 4 6 8 2 3 6 8 Tumor B Samples 1 4 5 7 3 5 7 Figure 16.12 Schematic of an idealized gene expression profiling experiment of eight samples and 100 genes. (Left) Individual arrays of gene sequences spotted on glass or silicon chips are used for comparative hybridization of eight different samples relative to a common standard. Red indicates decreased expression compared with control, green indicates increased expression, and yellow is unchanged expression. (In this schematic, red, yellow, and green represent decreased, equal, or increased expression, whereas a real experiment would provide a continuous quantitative reading with shades of red and green.) (Center) All 800 expression measurements are organized so that the relative expression for each gene (1–100) is put in order vertically in a column under the number of each sample. (Right) Clustering into signatures involves only those 13 genes that showed correlation across subsets of samples. Some genes have reciprocal (high vs low) expression in the two tumors; others show a correlated increase or decrease in one tumor and not the other. ▶

CHAPTER 16 — Cancer Genetics and Genomics 367 classic chemotherapies and immune checkpoint inhibitors, to broaden response rates among patients. In summary, although epigenetic therapies are still a w...

Ch16 · Pt22 368 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE correlated expression profile is more frequent in samples derived from tumor B than from tumor A. Clusters of genes whose expression correlates with each other and with a particular set of samples constitute an expression signature characteristic of those samples. In the hypothetical profiles in Fig. 16.12, certain genes have a correlated expression that serves as a signature for tumor A; tumor B has a signature derived from the correlated expression of a different subset of these 100 genes. Application of Gene Signatures The application of gene expression profiles to characterize tumors is useful in several ways. First, it increases our ability to discriminate between different tumors in ways that complement the standard criteria applied by pathologists to characterize tumors, such as histologic appearance, cytogenetic markers, and expression of specific marker proteins. Once distinguishing signatures for different tumor types (e.g., tumor A vs tumor B) are defined using known samples, the expression pattern of unknown tumor samples can then be compared with the expression signatures for tumor A and tumor B and classified as A-like, B-like, or neither, depending on how well their expression profiles match the signatures of A and B. Pathologists have used expression profiling to make difficult distinctions between tumors that require very different management approaches. These include distinguishing large B-cell lymphoma from Burkitt lymphoma, differentiating primary lung cancers from squamous cell carcinomas of the head and neck metastatic to lung, and identifying the tissue of origin of a cryptic primary tumor whose metastasis gives too little information to allow its classification. Second, different signatures may be found to correlate with known clinical outcomes, such as prognosis, response to therapy, or any other outcome of interest. If validated, such signatures can be applied prospectively to help guide therapy in newly diagnosed patients. Finally, for basic research, clustering may reveal previously unsuspected connections of functional importance among genes involved in a disease process. Gene Expression Profiling in Cancer Prognosis Choosing the appropriate therapy for most cancers is difficult for patients and their physicians alike because recurrence is common and difficult to predict. Better characterization of each patient’s cancer as to recurrence risk and metastatic potential would clearly be beneficial for deciding between more or less aggressive courses of surgery and/or chemotherapy. For example, in breast cancer—although presence of the estrogen and progesterone receptors, amplification of the HER2 oncogene, and absence of metastatic tumor in lymph nodes found on dissection of axillary lymphatics are strong predictors of better response to therapy and prognosis—they are still imprecise. Expression profiling (Fig. 16.13) is opening up a promising new avenue for clinical decision making in the management of breast cancer, as well as in other cancers, including lymphoma, prostate cancer, and metastatic adenocarcinomas of diverse tissue origins (lung, breast, colorectal, uterine, and ovarian). Gene expression profiling of various sets of genes is clinically available for use in the management of breast, colon, and ovarian cancer; which genes and how many are included in the profile depends on the tumor type and vendor. Although the clinical utility and cost effectiveness continue to be debated (see Chapter 19), there is a general consensus that combinations of clinical and gene expression data in patients newly diagnosed with cancer will provide better prospective estimates of prognosis and improved guidance of therapy. It is hoped that by improving the accuracy of prognosis with tumor expression profiling, oncologists can better tailor therapy and minimize exposure to toxic drugs when possible. The fact that prognosis for practically every patient could be associated with a particular combination of clinical features, genome sequence, and expression signatures underscores a crucial point about cancer: each person’s cancer is a unique disorder. The genomic and gene expression heterogeneity among patients who all carry the same cancer diagnosis should not be surprising. Every patient is unique in the genetic variants carried, including those variants that will affect how the cancer develops and the body responds to it. Moreover, the clonal evolution of a cancer implies that chance mutational and epigenetic events will likely occur in different and unique combinations in every patient’s particular cancer. Targeted Cancer Therapy Until recently, most nonsurgical cancer treatments relied on cytotoxic agents, such as chemotherapeutic agents or radiation, designed to preferentially kill tumor cells while attempting to spare normal tissues. Despite tremendous successes in curing such diseases as childhood acute lymphocytic leukemia and Hodgkin lymphoma, most cancer patients in whom complete removal of the tumor with surgery is not possible achieve remission, not cure, of their disease, usually at the cost of substantial toxicity from cytotoxic agents. The discovery of specific driver genes and their mutations in cancers has opened a new avenue for precisely targeted, less toxic treatments. Activated oncogenes are tempting targets for cancer therapy through direct blockade of their aberrant function. This can include blocking an activated cell surface receptor by monoclonal antibodies, or targeted inhibition of intracellular constitutive kinase activity with drugs designed to specifically inhibit their enzymatic activities. The proof of principle for this approach was established with the development of imatinib, a highly effective inhibitor of a number of tyrosine kinases, including the ABL1 kinase in CML. Prolonged remissions of this disease have been seen, in some cases with apparently ▶

368 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE correlated expression profile is more frequent in samples derived from tumor B than from tumor A. Clusters of genes whose expression correla...

Ch16 · Pt23 CHAPTER 16 — Cancer Genetics and Genomics 369 indefinite postponement of the transformation into a virulent acute leukemia (blast crisis) that so often meant the end of a CML patient’s life. Additional kinase inhibitors have been developed to target other activated oncogene driver genes in a variety of tumor types. Furthermore, constitutional pathogenic variants have been the impetus for targeted therapies (e.g., BRCA1/BRCA2, MLH1, MSH2, MSH6, PMS2, VHL1, NF1) (Table 16.5). The initial results with targeted therapies, although very promising in some cases, have not led to permanent cures in most patients largely because tumors develop resistance to the targeted therapy. The outgrowth of resistant tumors is not surprising. First, as previously discussed, cancer cells are highly mutable, and their genomes undergo recurrent mutation. Even if only a small minority of cells acquire resistance through either mutation of the targeted oncogene itself or a compensatory mutation elsewhere, the tumor can progress even in the face of oncogene inhibition. Newer compounds that can overcome drug resistance are being developed and used in clinical trials. Ultimately, combination therapy that targets different driver genes may be required, based on the idea that a tumor cell is less likely to develop resistance in multiple unrelated pathways targeted by a combination of agents. CANCER AND THE ENVIRONMENT Although the theme of this chapter emphasizes the genetic basis of cancer, there is no contradiction in considering the role of environment in carcinogenesis. By environment, we mean exposure to a wide variety of different types of agents—food, natural and artificial radiation, chemicals, and even viruses and bacteria that are colonizing the gut. The risk for cancer shows significant variation among different populations and even within the same population in different environments. For example, gastric cancer is almost three times as common among Japanese people in Japan as among Japanese people living in Hawaii or Los Angeles. In some cases, environmental agents act as mutagens that cause somatic mutations; the somatic mutations, in turn, are responsible for carcinogenesis. According to some estimates based chiefly on data from the aftermath of the atomic bombings of Hiroshima and Nagasaki, as much as 75% of the risk for cancer may be environmental Series of tumors Cluster A Cluster B Microarray analysis Hierarchical clustering Correlation with outcome Gene 1 Gene 2 Gene 3 Survival Cluster B 0 20 40 60 80 100 120 140 Months Figure 16.13 Expression patterns for a series of genes (along the vertical axis at left) for series of patient tumors, with the tumors arranged along the horizontal axis at top so that tumors with more similar expression patterns are grouped more closely together. The tumors appear to generally cluster into two groups, which are then correlated with long-term survival. (Adapted from Reis-Filho J, Pusztai L: Gene expression profiling in breast cancer: Classification, prognostication, and prediction, Lancet 378:1812–1823, 2011.) ▶

CHAPTER 16 — Cancer Genetics and Genomics 369 indefinite postponement of the transformation into a virulent acute leukemia (blast crisis) that so often meant the end of a CML patient’s life. Additiona...

Ch16 · Pt24 370 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE in origin. In other cases there appears to be a correlation between certain exposures and risk for cancer, such as the benefits of dietary fiber or low-dose aspirin therapy in lowering colon cancer risks. The nature of environmental agents that increase or reduce the risk for cancer, the assessment of the additional risk associated with exposure, and ways of protecting the population from such hazards are matters of strong public concern. Radiation Ionizing radiation is known to increase the risk for cancer. Everyone is exposed to some degree of ionizing radiation through background radiation (which varies greatly from place to place) and medical exposure. The risk is dependent on the age at exposure, being greatest for children younger than 10 years and for older adults. Although there are still large areas of uncertainty about the magnitude of the effects of radiation (especially low-level radiation) on cancer risk, some information can be gleaned from events involving large-scale release of radiation into the environment. The data for survivors of the Hiroshima and Nagasaki atomic bombings, for example, show a long latency period, in the 5-year range for leukemia but up to 40 years for some tumors. In contrast, there has been little increase in cancer detectable among populations exposed to ionizing radiation by the more recent nuclear accident at Chernobyl, with the exception of a significant five- to sixfold increase in thyroid cancer among the most heavily exposed children living in Belarus. The increase in thyroid cancer is almost certainly caused by the radioactive iodine (131I) that was present in the nuclear material released from the damaged reactor and was taken up and concentrated within the thyroid gland. Chemical Carcinogens Interest in the carcinogenic effect of chemicals dates back at least to the 18th century, when the high incidence of scrotal cancer in young chimney sweeps was noticed. Today there is concern about many possible chemical carcinogens, especially tobacco, components of the diet, industrial carcinogens, and toxic wastes. Documentation of the risk of exposure is often difficult, but the level of concern is such that all clinicians should have a working knowledge of the subject and be able to distinguish between well-established facts and areas of uncertainty and debate. The precise molecular mechanisms by which most chemical carcinogens cause cancer are still the subject of extensive research. One illustrative example of how a chemical carcinogen may contribute to the development of cancer is that of hepatocellular carcinoma, the fifth most common cancer worldwide. In many parts of the world, hepatocellular carcinoma occurs at increased frequency because of ingestion of aflatoxin B1, a potent carcinogen produced by a mold found on peanuts. Aflatoxin has been shown to mutate a particular base in the TP53 gene, causing a G to T mutation in codon 249, thus converting an arginine codon to serine in the critically important p 53 protein. This mutation is found in nearly half of all hepatocellular carcinomas in patients from parts of the world in which there is a high frequency of contamination of food by aflatoxin, but it is not found in similar cancers in patients whose exposure to aflatoxin in food is low. The p. Arg 249Ser variant in p 53 enhances hepatocyte growth and interferes with the growth control and apoptosis associated with wild-type p 53; LOH of TP53 in hepatocellular carcinoma is associated with a more malignant appearance of the cancer. Although aflatoxin B1 alone is capable of causing hepatocellular carcinoma, it can also act synergistically with chronic hepatitis B and C infections. TABLE 16.5 Cancer Treatments Targeted to Specific Driver Oncogenes Tumor Type Driver Gene and Mutation Representative FDA-Approved Targeted Therapeutic Mechanism of Action Breast cancer Amplified HER2 Trastuzumab Anti-HER2 monoclonal antibody Breast cancer, ovarian, prostate, pancreatic BRCA1/BRCA2 Olaparib PARP inhibitor Colon cancer Mismatch repair MLH1, MSH2, MSH6, PMS2 Nivolumab, pembrolizumab Targeting neoantigens induced by hypermutable state Renal tumors VHL Belzutifan HIF2α inhibitor Malignant peripheral nerve sheath tumors NF1 Selumetinib Kinase inhibitor blocks RAS pathway signaling by inhibiting MEK, downstream of RAS Non–small cell lung cancer Activated EGFR Gefitinib Tyrosine kinase inhibitor Chronic myelogenous leukemia and gastrointestinal stromal tumor Activated receptor tyrosine kinases AB1, KIT, and PDGF Imatinib, nilotinib, and dasatinib Tyrosine kinase inhibitor Non–small cell lung cancer Neuroblastoma Translocated ALK Activated ALK Crizotinib Tyrosine kinase inhibitor Melanoma Activated MEK Trametinib Serine-threonine kinase inhibitor Melanoma Activated BRAF kinase Vemurafenib Serine-threonine kinase inhibitor ALK, Anaplastic lymphoma kinase; EGFR, epidermal growth factor receptor; FDA, US Food and Drug Administration; HER2, human epidermal growth factor receptor 2; MEK, mitogen-activated extracellular signal-regulated kinase; PDGF, platelet-derived growth factor. ▶

370 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE in origin. In other cases there appears to be a correlation between certain exposures and risk for cancer, such as the benefits of dietary f...

Ch16 · Pt25 CHAPTER 16 — Cancer Genetics and Genomics 371 A more complicated situation occurs with an exposure to complex mixtures of chemicals, such as the many known or suspected carcinogens and mutagens found in cigarette smoke. The epidemiologic evidence is overwhelming that cigarette smoke increases the risk for lung cancer and throat cancer, as well as other cancers. Cigarette smoke contains polycyclic hydrocarbons that are converted to highly reactive epoxides that cause mutations by directly damaging DNA. The relative importance of these substances and how they might interact in carcinogenesis are still being elucidated. The case of cigarette smoking also raises another interesting issue. Why do only some cigarette smokers get lung cancer? Increasingly heritable underpinnings are becoming understood. The association between cancer and cigarette smoking provides an important example of the interaction between environmental and genetic factors to either enhance or prevent the carcinogenic effects of chemicals. The enzyme aryl hydrocarbon hydroxylase (AHH) is an inducible protein involved in the metabolism of polycyclic hydrocarbons, such as those found in cigarette smoke. AHH converts hydrocarbons into an epoxide form that is more easily excreted by the body but is also carcinogenic. AHH activity is encoded by members of the CYP1 family of cytochrome P450 genes (see Chapter 19). The CYP1A1 gene is inducible by cigarette smoke, but the inducibility is variable in the population because of different common variants at the CYP1A1 locus. People who carry a high-inducibility variant, particularly those who are smokers, appear to be at an increased risk for lung cancer, with odds ratios of 4 to 5 compared to individuals without the cancer-susceptibility CYP1A1 variant. On the other hand, homozygotes for the recessive low-inducibility variant appear to be less likely to develop lung cancer, possibly because their AHH is less effective at converting the hydrocarbons to highly reactive carcinogens. Similarly, individuals homozygous for common variants in the CYP2D6 gene that reduce the activity of another cytochrome P450 enzyme appear to be more resistant to the potential carcinogenic effects of cigarette smoke or occupational lung carcinogens (e.g., asbestos or polycyclic aromatic hydrocarbons). Normal or ultrafast metabolizers, on the other hand, who carry variants that increase the activity of the Cyp 2D6 enzyme, have a fourfold greater risk for lung cancer than do slow metabolizers. This risk increases to 18- fold among persons exposed routinely to lung carcinogens. A similar association has been reported for bladder cancer. Although the precise genetic and biochemical basis for the apparent differences in cancer susceptibility within the normal population remains to be determined, these associations could have significant public health consequences and may point eventually to a way of identifying persons who are genetically at a higher risk for the development of cancer. ACKNOWLEDGMENT We thank David Malkin, Rosanna Weksberg and Elise Fiala for contributing to this chapter. GENERAL REFERENCES https://www.annualreviews.org/doi/full/10.1146/annurevge nom-110320-121752 --- scaling genetic counseling in genomic era https://www.nature.com/articles/nm.4333 somatic landscape https://www.nature.com/articles/s 41586-020-1943-3 tumor signature https://www.nejm.org/doi/full/10.1056/nejmoa 1508054 peds germline frequency https://pubmed.ncbi.nlm.nih.gov/28873162/ adult germline frequency https://www.nature.com/articles/s 43018-021-00172-1 pediatric pediatric translation https://pubmed.ncbi.nlm.nih.gov/34133209/ adult translation https://ascopubs.org/doi/full/10.1200/JCO.19.02010 cascade testing https://ascopubs.org/doi/full/10.1200/JCO.22.00995 regulation SPECIFIC REFERENCES Bouffet E, Larouche V, Campbell BB, et al: Immune checkpoint inhibition for hypermutant glioblastoma multiforme resulting from germline biallelic mismatch repair deficiency, J Clin Oncol 34(19):2206– 2211, 2016. https://doi.org/10.1200/JCO.2016.66.6552 Bougeard G, Renaux-Petel M, Flaman JM, et al: Revisiting Li-Fraumeni syndrome from TP53 mutation carriers, J Clin Oncol 33(21):2345– 2352, 2015. https://doi.org/10.1200/JCO.2014.59.5728 Chen P-S, Su J-L, Hung M-C: Dysregulation of micro RNAs in cancer, J Biomed Sci 19:90, 2012. Chin L, Anderson JN, Futreal PA: Cancer genomics, from discovery science to personalized medicine, Nat Med 17:297–303, 2011. Di Leva G, Garofalo M, Croce CM: Micro RNAs in cancer, Annu Rev Pathol Mech Dis 9:287–314, 2014. Fiala, EM, Jayakumaran, G, Mauguen, A, et al: Prospective pan-cancer germline testing using MSK-IMPACT informs clinical translation in 751 patients with pediatric solid tumors. Nat Cancer 2, 357–365 (2021). https://doi.org/10.1038/s 43018-021-00172-1 Kiplivaara O, Aaltonen LA: Diagnostic cancer genome sequencing and the contribution of germline variants, Science 339:1559–1562, 2013. Kratz CP, Freycon C, Maxwell KN, et al: Analysis of the Li-Fraumeni spectrum based on an international germline TP53 variant data set: an International Agency for Research on Cancer TP53 database analysis, JAMA Oncol 7(12):1800–1805, 2021. https://doi. org/10.1001/jamaoncol.2021.4398 Lal A, Panos R, Marjanovic M, et al: A gene expression profile test to resolve head & neck squamous versus lung squamous cancers, Diagn Pathol 8:44, 2013. Reis-Filho J, Pusztai L: Gene expression profiling in breast cancer: Classification, prognostication, and prediction, Lancet 378:1812– 1823, 2011. Stadler ZK, Maio A, Chakravarty D, et al: Therapeutic Implications of Germline Testing in Patients With Advanced Cancers. Journal of Clinical Oncology 2021 39:24, 2698–2709. Watson IR, Takahashi K, Futreal PA, et al: Emerging patterns of somatic mutations in cancer, Nat Rev Genet 14:703–718, 2013. Wogan GN, Hecht SS, Felton JS, et al: Environmental and chemical carcinogenesis, Semin Cancer Biol 14:473–486, 2004. Wong MW, Nordfors C, Mossman D, et al: BRIP1, PALB2, and RAD51C mutation analysis reveals their relative importance as genetic susceptibility factors for breast cancer, Breast Cancer Res Treat 127:853–859, 2011. Zhang J, Walsh MF, Wu G, et al: Germline mutations in predisposition genes in pediatric cancer. N Engl J Med. (2015) 373:2336–46. https://doi.org/10.1056/NEJMoa 1508054. USEFUL WEBSITES The Cancer Genome Atlas http://cancergenome.nih.gov/abouttcga/over view c Bio Portal https://www.cbioportal.org/ PECAN https://pecan.stjude.cloud/ COSMIC https://cancer.sanger.ac.uk/cosmic CIVIC https://civicdb.org/welcome Clin Var https://www.ncbi.nlm.nih.gov/clinvar/ Genomic Data Commons https://gdc.cancer.gov/ GENIE https://www.aacr.org/professionals/research/ aacr-project-genie/aacr-project-genie-data/. ▶

CHAPTER 16 — Cancer Genetics and Genomics 371 A more complicated situation occurs with an exposure to complex mixtures of chemicals, such as the many known or suspected carcinogens and mutagens found...

Ch16 · Pt26 372 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE PROBLEMS 1. An individual with retinoblastoma has a single tumor in one eye; the other eye is free of tumors. What steps would you take to try to determine whether this is sporadic or heritable retinoblastoma? What is the empiric likelihood the child has an RB1 germline variant that is likely pathogenic or pathogenic? What genetic counseling would you provide? What information should the parents have before a subsequent pregnancy? Are there subsequent cancer risks? 2. Discuss possible reasons why colorectal cancer is predominantly an adult cancer, whereas retinoblastoma affects children. In which pediatric syndromes have colorectal cancers been reported? 3. Many tumor types are characterized by the presence of an isochromosome for the long arm of chromosome 17. Provide a possible explanation for this finding. In which constitutional cancer syndrome might there be an increase of this finding? 4. Many children with Fanconi anemia have limb defects. If an affected child requires surgery for the abnormal limb, what special considerations arise? 5. Margaret, whose sister has premenopausal bilateral breast cancer, has a greater risk for developing breast cancer herself than Wilma, whose sister has premenopausal breast cancer in only one breast. Both Margaret and Wilma, however, have a greater risk than does Elizabeth, who has a completely negative family history. Discuss the role of molecular testing in these women. What would their breast cancer risks be if a pathogenic BRCA1 or BRCA2 variant were found in the affected relative? What if no pathogenic variants were found? What are the differences between recommendations for screening individuals with pathogenic variants in moderate versus highly penetrant breast cancer predisposition breast cancer genes? 6. Propose a theory for why hereditary cancer syndromes, inherited as autosomal dominant diseases, are rarely caused by activated oncogenes; rather, by germline pathogenic variants in tumor suppressor genes. ▶

372 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE PROBLEMS 1. An individual with retinoblastoma has a single tumor in one eye; the other eye is free of tumors. What steps would you take to...

Chapter 17: Genetic Counseling and Risk Assessment

Ch17 · Pt1 GENETIC COUNSELING In this chapter, we present the fundamentals of the practice of risk estimation, which is a key component of the larger landscape of genetic counseling. Genetic counseling is defined as the process of helping people understand and adapt to the medical, psychological, and familial implications of genetic contributions to disease. Genetic counseling integrates the interpretation of family and medical histories, risk assessment, education, and counseling to promote informed choice and adaptation to the risk or condition. As technology and genomics have evolved, so has the definition of genetic counseling and the roles of professionals working in clinical genetics. CLINICAL GENETICS Clinical genetics is concerned with the diagnosis and management of the medical, social, and psychological aspects of hereditary conditions. As in all other areas of medicine, it is essential in clinical genetics to do the following: Make a correct diagnosis, which often involves laboratory testing, including genetic testing to find the pathogenic variants(s) responsible. Recommend appropriate treatment and management, including referrals to other specialist providers as needed. Help the affected person and family members understand and come to terms with the nature and consequences of the risk or condition. Just as the unique feature of genetic conditions is its tendency to recur within families, the unique aspect of clinical genetics is its focus on both the patient and on members of the patient’s family, both present and future. All providers performing genetic counseling have a responsibility to do the following: Empower patients to inform other family members of their potential risk. Offer testing to provide the most precise risk assessments possible for other family members. Explain what approaches are available to the patient and family members to modify these risks. Finally, genetic counseling is not limited to the provision of information and identification of individuals at risk for manifestation of a genetic condition; rather, it is a process of exploration and communication. Genetic counselors define and address the complex psychosocial issues associated with a genetic condition in a family and provide psychologically oriented counseling to help individuals adapt and adjust to the impact and implications of the condition in the family. For this reason, genetic counseling may be most effectively accomplished through ongoing contact with the family as the medical or social issues become relevant to the lives of those involved. The Profession of Genetic Counseling Genetic counseling can be provided by genetic counselors, physicians, and genetic nurses. However, in the United States, Canada, the United Kingdom, and a few other countries, genetic counseling services are often provided by genetic counselors or genetic nurses, professionals specially trained in genetics and counseling, who serve as members of a health care team. Genetic counseling in the United States and Canada is a self-regulating health profession with its own board (the American and Canadian Boards of Genetic Counseling, respectively) for certification of practitioners and the Accreditation Council for Genetic Counseling for accreditation of training programs. Nurses with genetics expertise are certified through a separate process and organization. In the United States, many states license genetic counselors to provide clinical services. State-based licensing of medical providers serves as a measure to protect the public from unqualified providers by setting a standard for minimum education and training requirements and sets the state-specific scope of practice. Genetic counselors and genetic nurses play an essential role in clinical genetics, participating in many aspects of the investigation and management of genetic conditions. A genetic counselor provides genetic counseling directly to individuals, helps patients and families deal with the many psychological and social issues that arise during genetic counseling, and continues in a supportive role and as a source of information after the clinical investigation and formal counseling have been completed. Genetic counselors are also active in the chapter 17 Genetic Counseling and Risk Assessment Carolyn Dinsmore Applegate ▶

Jodie Marie Vento

Ch17 · Pt2 374 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE field of genetic testing; they serve as liaison between the referring physicians, the diagnostic laboratories, and the families themselves. Their special expertise is valuable to clinical laboratories because explaining and interpreting genetic testing to patients and referring physicians often requires a sophisticated knowledge of genetics and genomics as well as excellent communication skills. Historically, genetic counseling was primarily performed in pediatric and prenatal clinical settings. However, increased understanding of the genetic contribution to medical conditions and the increased availability of genetic testing has increased the need for genetic counseling in many other medical specialties. For example, many genetic counselors now work in the specialties of oncology and cardiology, among others. Similarly, the unique training in genetics and genomics, biomedical technology, and psychosocial counseling received by genetic counselors allows genetic counselors to fulfill roles outside of patient care, such as research, marketing, and product development. Common Indications for Genetic Counseling Table 17.1 lists some of the most common situations that lead people to pursue genetic counseling. Individuals seeking genetic counseling (referred to as the consultands) may themselves have a genetic condition, or they may be the parents of an affected child or have relatives with a potential or known genetic condition. Additionally, consultands may seek genetic counseling in the pretesting setting to determine if they want to pursue genetic testing and in the posttesting setting for explanation and implications of results. Another important aspect of genetic counseling is to help individuals and their families adapt and strengthen their own abilities to manage the risk and impact of a genetic condition through supportive counseling. Genetic counseling is an integral part of prenatal testing (see Chapter 18) and of genetic testing and some screening programs (discussed in Chapter 19). Established standards of medical care require that providers of genetic services obtain a history that includes family and ancestry information, inquire as to possible consanguinity, advise patients of the genetic risks to them and other family members, offer genetic testing or prenatal diagnosis when indicated, and outline the various treatment or management options for reducing the risk for disease. Although genetic counseling case management must be individualized for each consultand’s needs and situation, a standard approach can be summarized (Table 17.2). The process of genetic counseling incorporates education, facilitating decision making and providing emotional support. This approach is necessary to support autonomy and to encourage shared decision making. Psychosocial Considerations Genetic counselors have expertise in psychosocial assessment, communication, and counseling techniques. The psychosocial domain includes the emotional, cognitive, familial, social, economic, and cultural beliefs of those involved. A challenging diagnostic journey or a new medical diagnosis often impacts all of these areas of the psychosocial domain. As discussed later in the chapter, uncertainty can be a particularly challenging experience for patients and their families. Patients and families receiving a genetic diagnosis experience many normal reactions that can include grief, guilt, shame, isolation, frustration, and psychological challenges such as anxiety and depression relating to chronic management of a condition that may be medically and psychosocially complex. Genetic counselors often help patients and their families understand and adapt to the medical, psychological, and familial implications of genetic TABLE 17.1 Common Indications for Genetic Counseling Personal history or family history of a hereditary condition, such as cystic fibrosis, fragile X syndrome, congenital heart defect, hereditary cancer, or diabetes Previous child with multiple congenital anomalies, intellectual disability, or an isolated birth defect such as neural tube defect or cleft lip and palate Pregnancy at risk for a chromosomal or hereditary condition Consanguinity Teratogen exposure, such as to occupational chemicals, medications, alcohol Repeated pregnancy loss or infertility Newly diagnosed medical condition with genetic etiology Before pursuing genetic testing and after receiving results As follow-up for a positive result of a newborn test, as with phenylketonuria Carrier screening A positive first- or second-trimester maternal serum screen, a noninvasive prenatal screen by cell-free fetal DNA analysis, or abnormal fetal ultrasound examination results TABLE 17.2 Genetic Counseling Case Management Case Management Contracting (goal-setting and alignment) Clinical History Family history Medical and developmental history Personal and familial genetic testing results Laboratory, radiologic tests or additional assessments Risk Assessment and Counseling Natural history Inheritance patterns and associated recurrence risk Shared Decision Making Genetic testing options and considerations Review of management and treatment options Referral to appropriate medical providers for diagnosis and management Psychosocial Considerations Psychosocial assessment and support Focused counseling Connection to community, advocacy, and support resources ▶

374 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE field of genetic testing; they serve as liaison between the referring physicians, the diagnostic laboratories, and the families themselves....

Ch17 · Pt3 CHAPTER 17 — Genetic Counseling and Risk Assessment 375 contributions to medical conditions and provide ongoing psychosocial assessment and counseling throughout the lifespan of the patient. Genetic counselors can be particularly helpful during periods of new challenges and transitions. Identifying individualized resources and sources of support is an important tenet of genetic counseling encounters. Many individuals have the strength to deal personally with such challenges; they may even prefer receiving bad news to remaining uninformed, and they make their own decisions based on the most complete and accurate information they can obtain. Other individuals require much more support and may need referral for psychotherapy. The extensive psychological aspects of genetic counseling are beyond the scope of this book, but several texts cited in the General References at the end of this chapter examine this important topic. RISK ASSESSMENT As noted, risk assessment is a key component of the larger genetic counseling process. Genetic counseling is much more than simply determining and providing a numerical risk to a consultand—in fact, it is the combination of counseling and communication skills with expertise in genetics principles and risk estimation that provides the unique niche of genetic counselors in the health care system. In this section we provide the fundamental principles and practice of risk assessment used by geneticists and genetic counselors. FAMILY HISTORY RISK ASSESSMENT The assessment of risk in genetic counseling begins with the personal and family medical histories. Family history collection can aid in identifying patterns of inheritance, establishing rapport with the patient and family, distinguishing genetic risk factors from other environmental risk factors, and determining medical surveillance for at-risk relatives. Applying the known rules of mendelian inheritance introduced in Chapter 7 allows the clinician to provide an assessment of risk for the condition in relatives of affected individuals (Fig. 17.1). Family history is also important when a clinician assesses the risk for complex conditions, as discussed in Chapter 9 and elsewhere in this book. Family history is also critical for determining when genetic and genomic testing is indicated. Even in the absence of a recognizable pattern of mendelian inheritance or genetic testing, the family history can be a useful clinical tool. As discussed in Chapter 9, the more first-degree relatives one has with a complex trait and the earlier in life the medical condition occurs in a family member, the greater the load of susceptibility genes and environmental exposures likely to be present in the patient’s family. Thus consideration of family history can lead to the designation of a patient as being at high risk for a particular medical condition based on family history. For example, a male with three male first-degree relatives with prostate cancer has an 11-fold greater relative risk for development of the medical condition than a man with no such family history. Determining that an individual is at increased risk based on family history can have an impact on individual medical care. For example, if there is family history information about a first-degree relative with colon cancer, that is sufficient to trigger the initiation of colon cancer screening by colonoscopy at the age of 40 years, or 10 years before the earliest diagnosis of colorectal cancer. This contrasts with the recommendation that people at average risk of colorectal cancer start regular screening at age 45. The increase in risk is even more pronounced if two or more relatives have had the same medical condition, an empirical observation that has driven standards of clinical care for screening in this condition. This family history information could also lead to genetic testing for a condition such as Lynch syndrome, which if present could have more significant medical care implications. Although it is an indirect method of assessing the contribution of an individual’s own genetic variants to health and disease susceptibility, the family history is a useful tool to provide individuals with a diagnosis, risk assessment, education, and psychosocial support. Direct detection of genetic risk factors and demonstrating that they are valid for guiding health care is a major challenge in applying genomics to medicine, as we will take up in Chapter 19. Genetic counselors often refer a patient and family with a genetic condition or morphologic anomaly to family and patient support groups. These organizations, which can be focused either on a single medical condition or on a group of conditions, can help those concerned to share their experience, to learn how to deal with the day-to-day problems caused by the condition, to hear of new developments in therapy or prevention, and to promote research into the condition. Many support groups have internet and social media sites, through 1/2 1/2 1/2 1 1 1/2 1/4 1/2 1/2 Figure 17.1 Pedigree of a family with an autosomal recessive condition. The probability of being a carrier is shown beneath each individual symbol in the pedigree. ▶

CHAPTER 17 — Genetic Counseling and Risk Assessment 375 contributions to medical conditions and provide ongoing psychosocial assessment and counseling throughout the lifespan of the patient. Genetic c...

Ch17 · Pt4 376 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE which patients and families give and receive information and advice, ask and answer questions, and obtain much needed emotional support. Similar condition-specific, self-help organizations are active in many nations around the world. RISK COMMUNICATION AND PERCEPTION One of the primary responsibilities of a genetic counselor is to communicate risk effectively. Most individuals can appreciate the concept of risk; however, acceptable risk thresholds and communication preferences are highly individual and may vary depending upon the circumstances. The multifaceted process of risk communication involves calculating the risks, tailored communication, and engaging patients in guided and informative conversations (see Box 17.1). There are many factors that impact the risk communication process. Some of these factors include the ability to internalize and retain risk information, one’s own perception of risk, the impact of fear, distress or anxiety, and patient preference for the format of risk information (e.g., percentage vs proportions). Many adults have limited numeracy, with only 10% of adults scoring in upper levels of numeric understanding. Therefore, assuming individuals can both understand and utilize complex numeric risk to make health decisions can lead to suboptimal counseling outcomes. Risk perception is subject to both internal and external factors, and it is important for the genetic counselor to thoughtfully consider and explore these factors throughout the communication process (Table 17.3). Goal alignment in patient encounters can help to ground these challenging conversations. A critical part of the genetic counseling process is to accurately ascertain the consultand’s questions and needs. The consultand’s goal(s) for the session may be very different from that of the provider and may involve complex family dynamics, profound existential questions, or more pragmatic questions such as deciding about genetic testing or choosing among various management options. In some circumstances qualitative risk descriptions may be helpful; however, they should be used cautiously. Adding qualitative descriptors such as “high” or “low” when describing risk can inadvertently add subjective bias. Presenting both sides of a risk figure can be a useful and balanced strategy. For example, in a couple who is heterozygous for a recessively inherited condition, one could explain there is a 25% chance of an affected offspring and a 75% chance that the offspring would not be affected with each pregnancy. Lastly, checking patient understanding is a key strategy to assess confusion, misinformation, and/or perceptions about risk information that has been presented. There are several studies about patient empowerment that demonstrate that the genetic counseling process of supporting autonomy and decision making is often more impactful than the risk number itself. DETERMINING RECURRENCE RISKS The estimation of recurrence risks is an important component of genetic counseling. Ideally, it is based on knowledge of the genetic nature of the condition in question and on the pedigree of the family being counseled. The consultand whose risk for a genetic condition is to be determined is usually a relative of a proband, such as a sibling of an affected child or a living or future child of an affected adult. In some families, especially for some traits inherited in an autosomal dominant or X-linked pattern, it may also be necessary to estimate the risk for more remote relatives. When a condition is known to have single-gene inheritance, the recurrence risk for specific family members can usually be determined from basic mendelian principles (see Fig. 17.1; also see Chapter 7). On the other hand, risk calculations may be less than straightforward TABLE 17.3 Factors That Impact Risk Perception Seriousness of the condition Personal attributes: age, education, gender, coping style, risk tolerance, optimism, having a living affected child, desire for children Beliefs about etiology, prognosis, and risk management options Stress and perceptions of vulnerability Familial experience with the condition Sense of “likeness” with the affected family member Level and accuracy of knowledge Heightened media attention From Uhlmann WR, Schuette JL, Yashar B: A guide to genetic counseling, ed 2, New York, 2009, Wiley-Liss. BOX 17.1 GENETIC COUNSELING AND RISK ASSESSMENT One component of genetic counseling is to provide information and support to families at risk for having, or who already have, members with genetic conditions. Genetic counseling helps the family or individual to do the following: Comprehend the medical facts, including the diagnosis, the probable course of the condition, and the available management. Understand the way heredity contributes to the condition and the inheritance risks for themselves and other family members. Understand the available reproductive options for mitigating genetic risks. Identify those values, beliefs, goals, and relationships affected by the risk for, or presence of, hereditary condition. Choose the course of action that seems most appropriate to them in view of their risk, their family goals, and their ethical and religious standards. Make the best possible adjustment to the condition or to the inheritance risks for that condition, or both, by providing supportive counseling to families and making referrals to appropriate specialists, social services, and family and patient support groups. ▶

376 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE which patients and families give and receive information and advice, ask and answer questions, and obtain much needed emotional support. Sim...

Ch17 · Pt5 CHAPTER 17 — Genetic Counseling and Risk Assessment 377 if there is reduced penetrance or variability of expression, or if the condition is frequently the result of a de novo variant, as in many conditions with X-linked and autosomal dominant inheritance. Laboratory tests that give uncertain results can add further complications. Under these circumstances, mendelian risk estimates can sometimes be modified by means of applying the method of bayesian probability to the pedigree (see later), which considers information about the family that may increase or decrease the underlying mendelian risk. In fact, bayesian probability is widely used across all domains of the medical diagnostic process. Here we show the application of this fundamental principle to genetic risk assessment and diagnosis for conditions with mendelian inheritance. In contrast to single-gene conditions, the underlying mechanisms of inheritance for most chromosomal or medical conditions cannot be calculated through use of basic genetic principles because of many unknown factors that are involved. For most complex genetic conditions, risk also cannot be assessed in this way, although rapid advances in polygenic risk scores will lead to advances in the near future. For these conditions, estimates of recurrence risk are based on previous experience, known as empirical risk (Fig. 17.2). This approach to risk assessment is useful if there are reliable data on the frequency of recurrence of the condition in families and if the phenotype is not heterogeneous. However, if a phenotype has etiologic heterogeneity and phenocopies with widely different risks, estimation of the recurrence risk is hazardous at best. In a later section, the estimation of recurrence risk in some typical clinical situations, both straightforward and more complicated, is considered. GENERAL PRINCIPLES OF RISK ESTIMATION Risk estimations are calculations based on the family and medical history information from the consultand and other family members, diagnostic and testing data, and the state of current knowledge. While the soundness of the fundamental principles of genetics and probability upon which such estimates are based is assured, it is essential for the clinician to recognize the limitations of such risk estimates. Family history recall is rarely complete or completely correct. Diagnostic and test data may be historical with little documentation. Knowledge of genetic conditions is changing constantly. Therefore it is essential when calculating risk estimates to make reasonable assumptions about these source data. The clinician should specify these assumptions and limitations so that changes in such understanding can lead to revised estimates in the future. Risk Estimation by Use of Mendel’s Laws When Genotypes Are Fully Known The simplest risk estimates pertain to conditions with simple mendelian inheritance patterns and apply to families in which the relevant genotypes of all family members are known or can be inferred. For example, if both members of a couple are known to be heterozygous carriers of a condition with autosomal recessive inheritance because of carrier testing, the risk (probability) is one in four with each pregnancy that the child will inherit two pathogenic alleles and manifest the condition (Fig. 17.3A). Even if the couple were to have six unaffected children (see Fig. 17.3B), the risk in the seventh, eighth, or ninth, pregnancy would still be one in four for each pregnancy.? Figure 17.2 Empirical risk estimates in genetic counseling. A family with no other positive family history has one child affected with a condition known to be multifactorial or chromosomal. What is the recurrence risk? If the child is affected with spina bifida, the empirical risk to a subsequent child is ~4%. If the child has Down syndrome, the empirical risk for recurrence would be ~1% if the karyotype is trisomy 21, but it may be substantially higher if one of the parents is a carrier of a robertsonian translocation involving chromosome 21 (see Chapter 6). 1/88 1 2 2 1/476 6 1/4 1/4 6 1 C D A B Figure 17.3 Series of pedigrees showing autosomal recessive inheritance with contrasting recurrence risks. (A, B) The genotypes of the parents are known. (C) The genotype of the consultand’s second partner is inferred from the carrier frequency in the population. (D) The inferred genotype is modified by additional pedigree information. Arrows indicate the consultand. Numbers indicate recurrence risk in the consultand’s next pregnancy. ▶

CHAPTER 17 — Genetic Counseling and Risk Assessment 377 if there is reduced penetrance or variability of expression, or if the condition is frequently the result of a de novo variant, as in many condi...

Ch17 · Pt6 378 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE Risk Estimation by Use of Conditional Probability When Alternative Genotypes Are Possible In contrast to the simple case just described, situations arise in which the genotypes of the relevant individuals in the family are not definitively known; the risk for recurrence will be very different, depending on whether the consultand is a carrier of a pathogenic allele of a gene. For example, the chance that a woman, who has an offspring with cystic fibrosis (CF), with her first partner might have a subsequent affected child depends on the chance that her next partner is a carrier of a pathogenic allele in the gene that causes CF, CFTR (see Fig. 17.3C). The likelihood that the partner is a carrier depends on his ancestry (see Chapter 10). For the general US non- Hispanic white (a US census category) population, this likelihood is ~1 in 22. Therefore the chance that a known carrier and her unrelated partner would have an affected first child is the product of these probabilities, or 122 × 14 = 188 (~1.1%). Of course, if the second partner actually were a carrier, the chance that the child of two carriers would be a homozygote or a compound heterozygote for the pathogenic CF alleles is one in four. If the second partner were not a carrier, then the chance of having an affected child is very low < (<<1%). Suppose, however, that one cannot test the second partner’s carrier status directly. A carrier risk of 1 in 22 is the best estimate one can make for individuals of his ancestry who have no family history of CF, when carrier testing is not possible. This person either is a carrier or is not, but the problem is that we do not know. In this situation, the more opportunities the male in Fig. 17.3C (who may or may not be a carrier of a pathogenic allele) has to pass on the pathogenic allele and fails to do so, the less likely it would be that he is indeed a carrier. Thus if the couple were to come for counseling already with six children, none of whom is affected (see Fig. 17.3D), it would seem reasonable, intuitively, that the man’s chance of being a carrier should be less than the 1 in 22 risk that the childless male partner in Fig. 17.3C was assigned based on the population carrier frequency. In this situation, we apply bayesian analysis (based on Bayes’s theorem on probability published in 1763), a method that measures the likelihood of a proposition before and after accounting for a piece of evidence that bears on that likelihood. In this particular application, the second partner’s likelihood of being a carrier before considering the six unaffected children is 1/22. To calculate his likelihood of being a carrier after accounting for the six unaffected children, we use bayesian analysis. In Fig. 17.3D, after taking the six unaffected children into account, the chance that the second partner is a carrier is 1 in 119, and the chance that this couple would have a child with CF is therefore 1 in 476, not 1 in 88, as calculated in Fig. 17.3C. Some examples of the use of bayesian analysis for risk assessment in pedigrees are examined in the following section. Bayesian Analysis Using Conditional Probability To illustrate the application of bayesian analysis, consider the pedigrees shown in Fig. 17.4. In Family A, the mother II-1 is an obligate carrier for the bleeding disorder hemophilia A, which is inherited in an X-linked recessive pattern because her father was affected. Her risk for transmitting the pathogenic factor VIII (F8) allele responsible for hemophilia A is 1 in 2, and the fact that she has already had four unaffected sons does not reduce this risk. Bayesian analysis cannot be used to adjust the mother’s risk since her genotype is known. Thus the risk that the consultand (III-5) is a carrier of a pathogenic F8 allele is 1 in 2 because she is the daughter of a known carrier In Family B, however, the consultand’s mother (individual II-2) may or may not be a carrier, depending on whether she has inherited a pathogenic F8 allele from her mother, I-1. Bayesian analysis can be used to adjust the consultand’s risk since the mother’s genotype is not known and alternative genotypes are possible. If III-5 were the only child of her mother, III-5’s risk for being a carrier would be 1 in 4, calculated as 12 (her mother’s risk for being a carrier) × 12 (her risk for inheriting the pathogenic allele from her mother). Short of testing III-5 directly for the pathogenic allele, we cannot tell whether she is a carrier. In this case, however, the fact that III-5 has four unaffected brothers is relevant because every Carrier risk 50% Family A Carrier risk ~3% Family B 1 2 I II III 1 2 1 2 3 4 5 I II III 1 2 3 4 5 1 2 1 2 3 4 Figure 17.4 Modified risk estimates in genetic counseling. The consultands in the two families are at risk for having a son with hemophilia A. In Family A, the consultand’s mother is an obligate heterozygote; in Family B, the consultand’s mother may or may not be a carrier. Application of bayesian analysis reduces the risk for being a carrier to only ~3% for the consultand in Family B but not the consultand in Family A. See text for derivation of the modified risk. ▶

378 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE Risk Estimation by Use of Conditional Probability When Alternative Genotypes Are Possible In contrast to the simple case just described, sit...

Ch17 · Pt7 CHAPTER 17 — Genetic Counseling and Risk Assessment 379 time II-2 had a son, the chance that the son would be unaffected is only 1 in 2 if II-2 were a carrier, whereas it is a near certainty (probability = 1) that the son would be unaffected if II-2 were, in fact, not a carrier at all. With each son, II-2 has, in effect, tested her carrier status by placing herself at a 50% risk for that son to be affected. To have four unaffected sons is a conditional probability that reduces the likelihood that her mother is a carrier. Bayesian analysis allows one to take this kind of indirect information into account in calculating whether II-2 is a carrier, thus modifying the consultand’s risk for being a carrier. In fact, as we show in the next section, her carrier risk is far lower than 50%. Identify the Possible Scenarios To translate this intuition into actual risk calculation, we use a bayesian probability calculation. First, we list all possible alternative genotypes that may be present in the relevant individuals in the pedigree (Fig. 17.5). In this case there are three scenarios, each reflecting a different combination of alternative genotypes: A. II-2 is a carrier, but the consultand is not. B. II-2 and the consultand are both carriers. C. II-2 is not a carrier, which implies that the consultand could not be one either because there is no variant allele to inherit. Why do we not consider the possibility that the consultand is a carrier even though II-2 is not? We do not list this scenario because it would require the occurrence of two de novo pathogenic variants in the same gene independently in the same family, one inherited by the affected males (II-1 and II-4) and one in the consultand, a scenario that is so unlikely that it does not significantly change the resulting risk estimate. First, we draw the three possible scenarios as pedigrees (as in Fig. 17.5) and write down the probability of individual II-2’s being a carrier or not. This is referred to as her prior probability because it depends simply on her risk for carrying a variant allele inherited from her known carrier mother, I-1, and it has not been modified (conditioned) at all by her own reproductive history. Next, we write down the probabilities that individuals III-1 through III-4 would be unaffected under each scenario. These probabilities are different, depending on whether II-2 is a carrier or not. If she is a carrier (situations A and B), then the chance that individuals III-1 through III-4 would all be unaffected is the chance that each did not inherit II-2’s variant F8 allele, which is 1 in 2 for each of her sons or ( 12)4 for all four. In situation C, however, II-2 is not a carrier, so the chance that her four sons would all be unaffected is 1 because II-2 does not have a variant F8 to pass on to any of them. These are called conditional probabilities because they are probabilities based on the conditions of each scenario, II-2 is a carrier or II-2 is not a carrier. Similarly, we can write down the probability that the consultand (III-5) is a carrier. In A, she did not inherit the variant allele from her carrier mother, with a probability of 1 in 2. In B, she did inherit the variant allele (probability = 12). In C, her mother is not a carrier, and so III-5 has essentially a 100% chance of not being a carrier. Multiply the prior and conditional probabilities together to form the joint probabilities for each situation, A, B, and C. Finally, we determine what fraction of the total joint probability is represented by any scenario of interest; this is called the posterior probability of each of the three situations. Because III-5 is the consultand and Prior probabilities Conditional probabilities Joint probabilities 1/2 × (1/2)4 × 1/2 = 1/64 Posterior probabilities 1/64 1/64 1 1/64 1 1/2 = 1/34 A. II-2 is a carrier, but the consultand did not inherit the mutant allele 1/2 (1/2)4 4 (1/2) 5 1–4 1/2 × (1/2)4 × 1/2 = 1/64 1/64 1/64 1 1/64 1 1/2 = 1/34 B. II-2 is a carrier, and the consultand did inherit the mutant allele 1/2×14×1=1/2 1/2 1/64 1 1/64 1 1/2 = 16/17 C. II-2 is not a carrier and so the consultand could not have inherited the mutant allele I II III 1 2 3 4 I II III 1 2 3 4 1/2 (1/2)4 (1/2) I II III 1 2 3 1/2 14 4 1 5 1–4 4 5 1–4 4 Figure 17.5 Conditional probability used to estimate carrier risk for a consultand in a family with hemophilia in which the prior probability of the carrier state is determined by mendelian inheritance from a known carrier at the top of the pedigree. These risk estimates, based on genetic principles, can be further modified by considering information obtained from family history, carrier detection testing, or molecular genetic methods for direct detection of the pathogenic variant in the affected boy, with use of bayesian calculations. (A–C) The three mutually exclusive situations that could explain the pedigree. ▶

CHAPTER 17 — Genetic Counseling and Risk Assessment 379 time II-2 had a son, the chance that the son would be unaffected is only 1 in 2 if II-2 were a carrier, whereas it is a near certainty (probab...

Ch17 · Pt8 380 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE wants to know her risk for being a carrier, we need the posterior probability of situation B, which is: 1 64 1 64 1 64 1 2 1 34 3 + + = = ≈ % If we wish to know the chance that II-2 is a carrier, we add the posterior probabilities of the two situations in which she is a carrier, A and B, to get a carrier risk of 1 in 17, or ~6%. If III-5 were also to have unaffected sons, her carrier risk could also be modified downward by a bayesian calculation. However, if II-2 were to have an affected child, then she would have proved herself a carrier, and III-5’s risk would thus become 1 in 2. Similarly, if III-5 were to have an affected child, then she must be a carrier, and bayesian analysis would no longer be necessary. Bayesian analysis may seem to some like mere statistical maneuvering. However, the analysis allows the clinician to quantify what seemed to be intuitively likely from inspection of the pedigree: the fact that the consultand had four unaffected brothers provides support for the hypothesis that her mother is not a carrier. The analysis having been performed, the final risk that III-5 is a carrier can be used in genetic counseling. The risk that her first child will have hemophilia A is 134 × 14, or less than 1%. This risk is appreciably below the prior probability estimated without considering the genetic evidence provided by her brothers and demonstrates the importance of using all available information to assess the risk. Bayesian Probability in Zero Reproductive Fitness and X-Linked Inheritance Because conditions with X-linked recessive inheritance are manifested in the hemizygous male, an isolated occurrence (no family history) of such a condition may represent either a de novo pathogenic variant (in which case the mother is not a carrier) or inheritance of a pathogenic allele from his unaffected carrier mother; we do not consider the chance of gonadal mosaicism for the pathogenic variant in the mother (see Chapter 7). Estimation of the recurrence risk depends on knowing the chance that she could be a carrier. Bayesian analysis can be used to estimate carrier risks in X-linked conditions that have zero reproductive fitness such as Duchenne muscular dystrophy (DMD) and severe ornithine transcarbamylase deficiency. Consider the family at risk for DMD shown in Fig. 17.6. The consultand, III-2, wants to know her risk for being a carrier. There are three possible scenarios, each with dramatically different risk estimates for the family: A. III-1’s condition may be the result of a de novo pathogenic variant. In this case, his sister and maternal aunt are not at significant risk for being a carrier. B. His mother, II-1, is a carrier, but her condition is the result of a de novo pathogenic variant. In this case, his sister (III-2) has a ~1 in 2 risk for being a carrier, but his maternal aunt is at population risk for being a carrier because his grandmother, I-1, is not a carrier. C. His mother is a carrier who inherited a pathogenic allele from her carrier mother (I-1). In this case, all the female relatives have either a 1 in 2 or a 1 in 4 risk for being carriers. How can we use conditional probability to determine the carrier risks for the female relatives of III-1 in this pedigree? If we proceed as we did previously with the hemophilia family in Fig. 17.4, what do we use as the prior probability that individual I-1 is a carrier? We do not have pedigree information, as we did in the hemophilia pedigree, from which to calculate these prior probabilities. We can, however, use some simple assumptions that the frequency of the condition is unchanging (see Chapter 10), and the de novo mutation rate per chromosome is equal in males and females to estimate the prior probability (see Box 17.2). H H H = × + + = + () / 1 2 2 2 µ µ µ BOX 17.2 PRIOR PROBABILITY THAT A FEMALE IN THE POPULATION IS A CARRIER OF A GENETICALLY LETHAL CONDITION WITH X-LINKED RECESSIVE INHERITANCE Suppose H is the population frequency of female carriers of an X-linked lethal condition. Assume H is constant from generation to generation. Suppose the mutation rate at this X-linked locus in any one gamete = µ. Assume µ is the same in males and females. Mutation rate µ is a small number, in the range of 10−4 to 10−6 (see Chapter 4). Then, there are three mutually exclusive ways that any female could be a carrier: 1. She inherits a variant allele from a carrier mother = 12 × H. or 2. She receives a newly pathogenic allele on the X she receives from her mother = µ. or 3. She receives a newly pathogenic allele on the X she receives from her father = µ. The chance a randomly ascertained female is a carrier is the sum of the chance that she inherited a preexisting variant and the chance that she received a new pathogenic variant from her mother or from her father. H H H = × + + = + () / 1 2 2 2 µ µ µ Solving for H, you get the chance that a random female in the population is a carrier of a particular X-linked condition = 4 µ. Note that half of this 4 µ, 2 µ, is the probability she is a carrier by inheritance, and the other 2 µ is the probability that she is a carrier by a de novo pathogenic variant. The chance a random female in the population is not a carrier is 1 − 4 µ ≅ 1 (because µ is a very small number). ▶

380 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE wants to know her risk for being a carrier, we need the posterior probability of situation B, which is: 1 64 1 64 1 64 1 2 1 34 3 + + = = ≈...

Ch17 · Pt9 CHAPTER 17 — Genetic Counseling and Risk Assessment 381 Now we can use this value 4 µ from the Box as the prior probability that a woman is a carrier of an X-linked lethal condition (see Fig. 17.6). For the purpose of calculating the chance that II-1 is a carrier, we ignore the female relatives II-3 and III-2 because there is nothing known about them, such as phenotype, laboratory testing, or reproductive history, that could serve as a conditional probability that would affect the likelihood that II-1 is a carrier. A. III-1 is a de novo pathogenic variant with probability µ. His mother and grandmother are both noncarriers, each of which has a probability of 1 − 4 µ ≅ 1. The joint probability is µ × 1 × 1 = µ. B. I-1 is a noncarrier, and so II-1 must be the product of a maternal or paternal de novo pathogenic variant and not a carrier by inheritance because we are specifying in scenario B that I-1 is not a carrier. The chance that a female will be a carrier by de novo pathogenic variant only is µ + µ = 2 µ (and not 4 µ). The joint probability is therefore 2 µ × 12 = µ. C. Individuals I-1 and II-1 are both carriers. As explained in the Box, the chance that I-1 is a carrier has a prior probability of 4 µ. For II-1 to be a carrier, she must have inherited the variant allele from her mother, which has probability 1 in 2. In addition, the chance that II-1 has passed the variant allele on to her affected son is also 1 in 2. The joint probability is therefore 4 µ × 12 × 12 = µ. The posterior probabilities are now easy to calculate as µ/(µ + µ + µ) = 13 each for scenarios A, B, and C. A key feature of this calculation is that since µ is in both the numerator and the denominator, they cancel and thus the fact that µ varies among various genes does not matter—the 1/3 risk of being a carrier is the same. The affected boy has a 1 in 3 chance of being affected because of a de novo pathogenic variant (situation A), whereas his mother II-1 is a carrier in both B and C and therefore has a 13 + 13 = 23 chance of being a carrier. The grandmother, I-1, is a carrier only in C, and so her chance of being a carrier is 1 in 3. Joint probabilities Posterior probabilities µ (µ/3µ) = 1/3 2µ31/2=µ (µ/3µ) = 1/3 4µ31/231/2=µ (µ/3µ) = 1/3 I II III???? 1 2 1 2 3 2 1 I II III 1 1 2 1 2 1 µ 1 I II III 1/2 I II III 2 1/2 1 1 2 1 2 2µ 1 1 2 4µ 1 1/2 1 B A C Figure 17.6 Conditional probability used to determine carrier risks for females in a family with an X-linked genetic lethal condition in which the prior probability of being a carrier has to be calculated by assuming that the carrier frequency is not changing from generation to generation, and that the mutation rates are the same in males and females. (Top) Pedigree of a family with an X-linked genetic lethal condition. (Bottom) The three mutually exclusive situations that could explain the pedigree. (A) The proband is a new pathogenic variant. (B) The mother of the proband is a new pathogenic variant. (C) The mother of the proband inherited the pathogenic variant from her carrier mother, the grandmother of the proband. ▶

CHAPTER 17 — Genetic Counseling and Risk Assessment 381 Now we can use this value 4 µ from the Box as the prior probability that a woman is a carrier of an X-linked lethal condition (see Fig. 17.6)....

Ch17 · Pt10 382 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE With these risk figures for the core individuals in the pedigree, we can then calculate the carrier risks for the female relatives II-3 and III-2. III-2’s risk for being a carrier is 12 × [the chance II-1 is a carrier] = 12 × 23 = 13. The risk that II-3 is a carrier is 12 × [the chance I-1 is a carrier] = 12 × 13 = 16. In all of these calculations, for the sake of simplicity, we do not include the small but very real possibility of germline or somatic mosaicism. In a real genetic counseling situation, however, the possibility of mosaicism must be communicated to the family. Conditions With Incomplete Penetrance To estimate the recurrence risk for conditions with incomplete penetrance, the probability that an apparently unaffected person is heterozygous for the gene variant in question must be considered. Fig. 17.7 shows a pedigree of split hand malformation, which has autosomal dominant inheritance with incomplete penetrance (discussed in Chapter 7). An estimate of penetrance can be made from a single pedigree if it is large enough, or from a review of published pedigrees; we use 70% in our example. Thus a heterozygote for a pathogenic variant that causes split hand malformation has a 30% chance of not showing the phenotype. The pedigree shows several people who must be heterozygous for the variant gene but do not manifest it (i.e., in whom the condition is not penetrant), I-1 or I-2 (assuming no somatic or germline mosaicism) and II-3. The other unaffected family members may or may not be heterozygous for the variant gene. If III-4, the daughter of a known affected heterozygote, is the consultand, there are two possibilities (Fig. 17.8). First, she may have not inherited the variant allele from her affected mother or, second, she may have inherited it but is not manifesting the phenotype because of incomplete penetrance. In A, III-4 has a prior probability of 1 in 2 of not being heterozygous for the variant. If she is not heterozygous for the variant, she has an essentially 100% chance of not manifesting the phenotype, so the joint probability for A is ½ × 1 = ½ or 0.5. In B, III-4 is heterozygous for the variant, also with prior probability 1 in 2. Here, we must apply the conditional probability that she is heterozygous for the variant but does not manifest the phenotype, which has probability of 1 − penetrance = 1 − 0.7 = 0.3, so the joint probability for B is 12 × 0.3 = 0.15. The posterior probability that III-4 is heterozygous for the variant without manifesting the phenotype is therefore (0.15)/ (0.15 + 0.5) = 313 = ≈23%. Conditions With Age-Specific Penetrance Many conditions with autosomal dominant inheritance show a late age at onset, beyond the age of reproduction. Thus, it is not uncommon in risk assessment to ask whether a person of reproductive age, who is at risk though asymptomatic for such a condition, harbors the pathogenic variant. One example of such a condition is a rare, familial form of Parkinson disease (PD) inherited in an autosomal dominant pattern with age-specific penetrance. Consider the pedigree in Fig. 17.9 in which the consultand, an asymptomatic 35-year-old man, wishes to know his risk for PD. His prior risk for having inherited the PD pathogenic variant from his affected grandmother is 1 in 4. Considering that perhaps only 5% of persons with this rare form of PD have symptoms at his age, he would not be expected to have signs of the condition even if he had inherited the variant allele. The more significant aspect of the pedigree, however, is that the consultand’s I II III 1 2 1 2 3 2 3 4 5 6 1 Figure 17.7 Pedigree of family with split hand deformity and lack of penetrance in some individuals. II III 2 4 4 1/2 1/2 10/13 2 1/2 0.3 1 Prior Conditional 3/20 3/13 Joint Posterior A B Figure 17.8 Conditional probability calculation for the risk for the carrier state in the consultand in Fig. 17.7. There are two possibilities: either she is not a carrier (A) or she is a carrier (B). Her failure to demonstrate the phenotype lowers her carrier risk from the prior probability of 1 in 2 (50%) to 3 in 13 (23%). Age 60 Age 35 I II III 1 2 1 1 2 Figure 17.9 Age-modified risks for genetic counseling in dominant Parkinson disease. That the consultand’s father is asymptomatic at the age of 60 years reduces the consultand’s final risk for carrying the gene to ~12.5%. That the consultand himself is asymptomatic reduces the risk only slightly because most patients carrying the pathogenic allele for this disease will be asymptomatic at the age of 35 years. ▶

382 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE With these risk figures for the core individuals in the pedigree, we can then calculate the carrier risks for the female relatives II-3 and...

Ch17 · Pt11 CHAPTER 17 — Genetic Counseling and Risk Assessment 383 father (II-2) is also asymptomatic at the age of 60 years, an age by which perhaps two-thirds of persons with this form of PD have symptoms and one-third do not. As shown in Fig. 17.10, there are three possibilities: A. His father did not inherit the variant allele, so the consultand is not at risk. B. His father inherited the pathogenic variant and is asymptomatic at the age of 60 years, but the consultand did not. C. His father inherited the variant allele and is asymptomatic. The consultand inherited it from his father and is asymptomatic at the age of 35 years. The father’s chance of having the variant allele (situations B and C) is 25%; the consultand’s chance of having the variant allele (situation C only) is 12%. Providing these recurrence risks in genetic counseling requires careful follow-up. If, for example, the consultand’s father were to develop symptoms of PD, the risks would change dramatically. EMPIRICAL RECURRENCE RISKS Counseling for Complex Conditions Genetic counselors deal with many conditions that are not single-gene diseases. Instead, counselors may be called on to provide risk estimates for complex medical condition with a strong genetic component and familial clustering, such as cleft lip and palate, congenital heart disease, meningomyelocele, psychiatric illness, and coronary artery disease (see Chapter 9). In these situations the risk for recurrence in first-degree relatives of affected individuals may be increased over the background incidence of the condition in the population. For most of these conditions, however, knowledge is still emerging about the relevant underlying genetic variants or how they interact with each other or with the environment to cause these conditions. As the information gained through the Human Genome Project is applied to the problem of medical conditions with complex inheritance, physicians, genetic counselors, and other health professionals will have more of the information they need to provide accurate molecular diagnosis and risk assessment and to develop rational preventive and therapeutic measures. In the meantime, however, clinicians must rely on empirically derived risk figures to give patients and their relatives some answers to their questions about their risk and how to manage that risk. Recurrence risks are estimated empirically by studying as many families with the condition as possible and observing how frequently the condition recurs. The observed frequency of a recurrence is taken as an empirical recurrence risk. With time, research should make empirical recurrence risks obsolete, replacing them with individualized assessments of risk based on knowledge of a person’s polygenic risk score and environmental exposures. Another area in which empirical recurrence risks must be applied is for chromosomal abnormalities (see Chapter 6). When one member of a couple is carrying a chromosomal or genome abnormality, such as a balanced translocation or a chromosomal inversion, the risk for a liveborn, chromosomally unbalanced child depends on a number of factors. These include the following: Whether the couple was ascertained through a previous liveborn child with a chromosome abnormality, in which case a viable offspring with the chromosome abnormality is clearly possible, or the ascertainment was through chromosome or genome studies for infertility or recurrent miscarriage The chromosomes involved, which region of the chromosome was affected, and the size of the regions that could be potentially trisomic or monosomic in the fetus Whether the mother or father is the carrier of the balanced translocation or inversion I II III 1 2 1 1/2 I II III 1 2 1 1/2 3 1/3 1/2 0.75 I II III 1 2 1 1/2 3 1/3 1/2 1/2 x 0.95 1/2 × 1/3 × 1/2 = 1/12 0.13 1/2 × 1/3 × 1/2 × 0.95 = 0.08 0.12 Joint Posterior A B C Figure 17.10 Three scenarios pertaining to the Parkinson disease pedigree in Fig. 17.9. Individual II-2 is a nonpenetrant carrier (vertical line inside the symbol) in scenarios B and C. Individual III-1 is a nonpenetrant carrier in scenario C. ▶

CHAPTER 17 — Genetic Counseling and Risk Assessment 383 father (II-2) is also asymptomatic at the age of 60 years, an age by which perhaps two-thirds of persons with this form of PD have symptoms an...

Ch17 · Pt12 384 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE These factors must all be considered when empirical recurrence risks are determined for a couple in which one member is carrying a balanced translocation or a seemingly normal genomic copy number variant. Empirical recurrence risks are also applied when both parents are chromosomally normal but have a child with, for example, trisomy 21. In this case, the age of the mother plays a major role in that, in a woman younger than 30 years, recurrence risk for trisomy 21 is ~5 per 1000 and the risk for any chromosome abnormality is ~10 per 1000 as opposed to the population risk of ~1.6 per 1000 live births. Over age 30, however, the age-specific risk becomes the dominant factor, and the fact of a previously affected child with trisomy 21 plays much less of a role in determining recurrence risk. Clinicians must use caution in applying empirical risk figures to a particular family. First, empirical estimates are an average over what is undoubtedly a group of heterogeneous conditions with different mechanisms of inheritance. In any one family, the real recurrence risk may be higher or lower than the average. Second, empirical risk estimates use history to make predictions about future occurrences; if the underlying biologic causes are changing through time, data from the past may not be accurate for the future. For example, neural tube defects (myelomeningocele and anencephaly) occur in ~3.3 per 1000 live births in the US of European ancestry. If, however, a couple has a child with a neural tube defect, the risk in the next pregnancy has been shown to be 40 per 1000 (13 times higher). The risks remained elevated compared with the general population risk for more distantly related individuals; a second-degree relative (e.g., a nephew or niece) of an individual with a neural tube defect was found to have a 1.7% chance of a similar birth defect. Thus, as we saw in Chapter 9, neural tube defects manifest many of the features typical of multifactorial inheritance. However, these empirical recurrence risks were calculated before widespread folic acid supplementation. With folate supplementation before conception and during early pregnancy, these recurrence risk figures have fallen dramatically (see Chapter 9). This is not because the allelic variants in the families have changed but rather because a critical environmental factor has changed. Finally, it is important to emphasize that empirical figures are derived from a particular population, and so the data from one ancestry group, socioeconomic class, or geographic location may not be accurate for an individual from a different background. Nonetheless, such figures are useful when patients ask genetic counselors to give a best estimate for recurrence risk for conditions with complex inheritance. Genetic Counseling for Consanguinity In counseling a consanguineous couple, in the absence of a family history for a known condition with autosomal recessive inheritance, we use empirical risk figures for the offspring, based on population surveys of congenital anomalies in children born to first-cousin couples compared with nonconsanguineous couples (Table 17.4). These results provide empirical risk figures in the counseling of first cousins. The relative risk for a genetic condition in the offspring is higher for related than for unrelated parents: approximately double in the offspring of first cousins, compared with baseline risk figures for any abnormality of 15 to 20 per 1000 for any child, regardless of consanguinity. This increased risk is not exclusively for single-gene conditions with autosomal recessive inheritance but includes the entire spectrum of single-gene and complex conditions. However, any couple, consanguineous or not, who has a child with a congenital anomaly is at greater risk for having another affected child in a subsequent pregnancy. These risk estimates for consanguinity may be slightly inflated given they are derived from communities in which first-cousin marriages are widespread and encouraged. These are societies in which the degree of relationship (coefficient of inbreeding) between two first cousins may be greater than the theoretical 116 due to multiple other lines of relatedness (see Chapter 10). Furthermore, these same societies may also limit marriages to individuals from the same clan, leading to substantial population stratification, which also increases the rate of conditions with autosomal recessive inheritance beyond what might be expected based on variant allele frequency alone (see Chapter 10). REPRODUCTIVE OPTIONS Many families seek genetic counseling to ascertain the risk for heritable conditions in their children and to learn about possible options. All reproductive options available to the family should be stated, though the discussion may be focused on one or two of the options depending on the family’s desires and values. Prenatal diagnosis is an option when the pathogenic variant(s) of the genetic condition are known or for conditions that can be diagnosed by biochemical or cytogenetic tests (see Chapter 18). Similarly, preimplantation genetic TABLE 17.4 Incidence of Birth Defects in Children Born to Nonconsanguineous and First-Cousin Couples Incidence of First Birth Defect in Sibship (per 1000) Incidence of Recurrence of Any Birth Defect in Subsequent Children in Sibship (per 1000) First-cousin marriage 36 68 Nonconsanguineous marriage 15 30 Data from Stoltenberg C, Magnus P, Skrondal A, et al: Consanguinity and recurrence risk of birth defects: a population-based study, Am J Med Genet 82:424–428, 1999. ▶

384 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE These factors must all be considered when empirical recurrence risks are determined for a couple in which one member is carrying a balanced...

Ch17 · Pt13 CHAPTER 17 — Genetic Counseling and Risk Assessment 385 testing is an option when the pathogenic variant(s) causing a genetic condition in a family are known (see Chapter 18). When a parent has an autosomal dominant or X-linked condition, use of a gamete donor can significantly reduce the chance to have a child with a genetic condition. Use of a sperm donor for couples at risk to have a child with an autosomal recessive is a viable reproductive option, assuming that the sperm donor, whether anonymous or designated, has been screened for the genetic condition in question, with negative test results. Use of an egg donor can also be offered to reduce the risk for chromosome abnormality in families who are concerned about maternal age- related aneuploidy or in families with mitochondrial conditions caused by pathogenic variants in the mitochondrial DNA. Adoption is also an option for families that want a child or more children. Similarly, for couple’s wanting to experience pregnancy, receipt of an embryo donated by another couple is an available family planning option. Lastly, if the parents do not plan to have additional children, contraception may be the best option, and they may need information about possible procedures or an appropriate referral. Discussions around family planning can elicit strong emotions, so discussions are best approached in a sensitive manner that elicits the family’s personal and cultural desires and values. GENETIC COUNSELING IN THE ERA OF GENOMIC MEDICINE Molecular and Genome-Based Diagnostics Recent advances in molecular technology have led to increased diagnostic rates across all areas of clinical genetics allowing providers to make more accurate/ precise diagnoses and perform more specific risk assessment. With our expanding knowledge of the genes involved in hereditary conditions and the rapidly falling cost of DNA sequencing, direct detection of pathogenic variants in a patient’s or family member’s genomic DNA to make a molecular diagnosis has become standard of care for many conditions. DNA samples for analysis are available from such readily accessible tissues as a blood sample, buccal swab or saliva sample, but also from tissues obtained by more invasive testing, such as chorionic villus sampling or amniocentesis (see Chapter 18). Genetic test results for mendelian disorders generally report the identified variants as being pathogenic, likely pathogenic, variant of uncertain significance (VUS), likely benign, or benign. This five-category scale is in fact a probabilistic assertion by the testing laboratory of the likelihood that the variant is causally associated with the condition. Specifically: Pathogenic means ≥99% likely Likely pathogenic means ≥90% to <99% likely VUS means ≥10% to <90% likely Likely benign means ≥1% to <10% Benign means <1% These likelihoods of pathogenicity are in fact also derived from bayesian probability. Clinical genetic and genomic laboratory analysts start their analysis with a prior probability of pathogenicity and then evaluate a host of distinct variant attributes (e.g., the frequency in affected cases vs controls, computer modeling of the effect of variant, inheritance patterns in affected families), which serve as conditional probabilities to yield a posterior probability of pathogenicity, expressed in terms of the five-category scale just described. Pretest Counseling and Informed Consent For the purpose of informed consent, molecular genetic testing can generally be divided into two categories based on the reporting criteria of a particular test: genome- wide testing and targeted/focused testing. Although this is an artificial distinction and does not account for differences in genomic technology, this categorization is useful to highlight the unique and overlapping elements of pre- and posttest genetic counseling. Examples of genome-wide testing include chromosomal microarrays, clinical exome sequencing, and clinical genome sequencing. Pretest informed consent and counseling for this type of genomic test result should include a review of the five possible testing results and likelihood of each outcome: positive, negative, VUS, expected secondary findings, and unexpected secondary, or incidental, findings. Positive Results A positive result means that a pathogenic variant was identified in a gene that corresponds to the patient’s phenotype or genetic condition. In some cases, a positive result may only be a partial positive, meaning that only part of the patients’ phenotype or clinical presentation can be attributed to the identified gene and variant(s). The likelihood of a positive result depends on the detection rate of the test, though this may be adjusted to account for differences in detection among certain categories of conditions and patient populations. Chromosome microarrays identify a pathogenic copy number variant in about 15% to 20% of individuals with developmental delay, intellectual disability, and/or multiple congenital anomalies. Studies of clinical exome sequencing have found detection rates ranging between 25% and 40% with childhood-onset neurologic disease having closer to 40% detection rate and adults with nonneurologic indications having lower detection rates of 11% to 14%. Depending on the setting and circumstances of the patient and family, a positive result can be perceived as good news or bad news, though many individuals and families will show a combination of evolving positive and negative psychological reactions. A positive result typically allows the genetics provider to counsel on specific recurrence risk and offer targeted familial testing, as appropriate, to family members. A positive result also allows the genetics provider to share ▶

CHAPTER 17 — Genetic Counseling and Risk Assessment 385 testing is an option when the pathogenic variant(s) causing a genetic condition in a family are known (see Chapter 18). When a parent has an aut...

Ch17 · Pt14 386 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE medical management and preventive or screening recommendations as well as provide anticipatory guidance about the natural history of the condition. Negative Results A negative result means that no pathogenic or likely pathogenic variant(s) were detected in a gene that corresponds to the patient’s phenotype or genetic condition. The most important point for patients and families to understand about a negative test result is that this does not exclude a genetic etiology for the condition presenting in the individual or family. Explanations for negative genome-wide test results can include (1) technical limitations in the ability to detect certain variants (e.g., noncoding or intronic variants or intermediate size deletions/duplications), (2) knowledge-based limitations, specifically the phenotypic result of pathogenic variants is only known for ~5000 of our ~20,000 genes, or (3) complex genetic etiologies, such as multifactorial and epigenetic conditions. Like a positive result, a negative result can be perceived as good news or bad news depending on the setting and circumstances. Recurrence risk counseling after a negative result relies on assessment of the family history and applying mendelian inheritance patterns and empiric recurrence risks as appropriate. Clinical exome and genome sequencing generate large amounts of sequence data with the final report highlighting variants in genes associated with the clinical phenotype. Negative genome-wide tests offer the opportunity for ongoing analysis or timed reanalysis of the sequence data generated. As sequencing technologies improve, it often becomes necessary to repeat sequencing to maximize detection rates. However, some studies suggest that negative results are more likely due to our incomplete knowledge of gene-phenotype relationships, such that over time, reanalysis of existing data is more likely to result in a positive test result than utilizing new sequencing technologies. Variants of Uncertain Significance (VUS) As the number of genes being tested increases, the number of differences between an individual’s sequence and that of a reference sequence also increases; consequently, many variants will be found whose pathogenetic significance is unknown (i.e., VUS). This is particularly the case for missense variants that result in the substitution of one amino acid for another in the encoded protein. Exome sequencing and genome sequencing find more than 100,000 variants, many of which will not have enough evidence to be classified as benign or pathogenic. The identification of a VUS alone should not be used to inform clinical management or decision making (e.g., a prophylactic mastectomy should not be considered based on the finding of a VUS in the BRCA2 gene alone). In some circumstances, testing of family members can aid in segregation and analysis of the suspected pathogenicity of the variant. Absent that, it is not recommended to test family members for a VUS to determine whether they inherited the genetic predisposition to the condition in the family or for prenatal diagnosis to determine whether a fetus has or does not have a genetic condition. Although these are guiding principles, there are some instances when additional clinical information is available that may change the clinicians’ classification of variant even when the laboratory classification may not change. These cases require careful consideration with multidisciplinary input from the care team, laboratory, and family. It is important to inform individuals about the likelihood and clinical significance of finding a VUS as individuals naturally assume that if a variant was reported that it must be clinically significant. It is also important to encourage families to follow up with their provider(s) and the laboratory since, over time, additional population, familial segregation studies, and functional data become available that allow for reclassification of VUSs. Reclassification of a variant may change management and familial testing recommendations. Secondary Findings Secondary findings refer to the generation of information from sequencing that is not related to the indication for testing. This can occur due to the agnostic nature of the sequence generation and is inherent to the process of genome-wide testing. Clinical exome and genome sequencing can identify variants in all genes, not just those that are relevant to the reported phenotype. Therefore, the American College of Medical Genetics and Genomics (ACMG) has provided a policy statement for reporting of secondary findings. These guidelines state that during informed consent, individuals undergoing testing should be given the choice whether to receive secondary findings. The ACMG provides a list of genes that meet criteria for actionability and updates the list periodically. Additionally, ACMG recommends limiting reporting to variants that are classified as likely pathogenic and pathogenic. In pretest discussions with families, it is important to review the benefits and implications of such findings on the individual’s and family’s medical care, potential for negative psychological impacts (e.g., stress, anxiety), altered family dynamics, and insurance implications. It is important to highlight that the variants that are recommended for reporting are known to have effective medical interventions that can significantly reduce morbidity and mortality. Incidental Findings Secondary findings that result inherently from the process, sometimes referred to as incidental findings, include the potential to identify consanguinity and misattributed maternity or paternity. Consanguinity can be identified on chromosome microarrays that use single nucleotide polymorphism–based methods through the identification of multiple regions with loss of heterozygosity (also known as regions or runs of homozygosity) as well as exome and genome sequencing, which will show an ▶

386 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE medical management and preventive or screening recommendations as well as provide anticipatory guidance about the natural history of the con...

Ch17 · Pt15 CHAPTER 17 — Genetic Counseling and Risk Assessment 387 increased rate of homozygous variants. When parental samples are submitted for duo or trio exome/genome sequencing, which is preferred to augment interpretation and reduce the number of VUSs, misattributed paternity or maternity will be identified. Discussion of these possible outcomes of testing prior to testing allows individuals and families to be fully informed about the advantages and risks associated with this testing to make a truly informed choice to proceed with or decline testing. Verbalizing these possible findings also allows the individual or family to share with the provider any concerns, and in some cases testing strategy or results disclosure planning may be adjusted. Phenotype-driven tests interrogate a subset of genes and variants that are limited to those genes and variants associated with the phenotype of interest. Examples include multigene panels, single-gene sequencing, and targeted variant and familial variant testing. Pretest consent for this category of testing still requires a review of the detection rate, possible outcomes, and limitations. A major difference between genome-wide testing and targeted phenotype-driven testing is that secondary findings are unlikely to be reported in targeted testing; however, as technology advances and laboratory reporting criteria evolve, secondary findings may be reported more frequently. With phenotype-driven tests, it is important to review that an individual may have a pathogenic variant in a gene not included on the panel and that each testing technology will have technical limitations that could cause a variant within a gene included on the panel to be missed. Additionally, since new gene-phenotype relationships are constantly being described, testing may need to be repeated in the future. Cascade Testing When a pathogenic variant has been identified in a family, it is recommended to offer at-risk relatives targeted testing for the variant identified, a process called cascade testing. Targeted testing of family members who have the phenotype or genetic condition is often done to confirm the presumed presence of the pathogenic variant in that individual. Family members who are not known to have the phenotype or genetic condition (i.e., asymptomatic individuals) are identified through risk assessment and are offered presymptomatic testing. As is true for any medical test, individuals should be offered as a choice whether to undergo genetic testing and should be engaged in a discussion of the positive implications of such findings on the individual’s medical care, the small but real potential for negative psychological impacts (e.g., stress, anxiety), altered family dynamics, and insurance implications. Alternatives to testing, including the risks and benefits of each alternative, should be explored. Alternative options to presymptomatic testing may include delaying or deferring testing to a later time and/or following medical management or surveillance guidelines based on family history without a confirmation of the pathogenic variant. Special consideration should be taken when the at-risk individual is a minor. It is generally recommended to defer pre symptomatic testing of a minor until the age that medical intervention is recommended to begin and to engage the minor in the decision-making process at a level that is developmentally appropriate. Another important aspect of how to use molecular and genome-based diagnostic testing in families is the selection of the best person(s) to test. If the consultand is also the affected proband, then molecular testing is appropriate. If, however, the consultand is an unaffected, at-risk individual, with an affected relative serving as the indication for having genetic counseling, it is best to test the affected person rather than the consultand, if logistically possible. This is because a negative test in the unaffected consultand is an uninformative negative; that is, we do not know if the test was negative because (1) the gene or variant responsible for the condition in the proband was not covered by the test, or (2) the consultand in fact did not inherit a variant that could have been detected had the pathogenic variant been identified in the affected proband in the family. Once the variant or variants responsible for a particular condition are found in the proband, then the other members of the family no longer need comprehensive gene sequencing to assess that particular risk. The DNA of family members can be assessed with less expensive testing only for the presence or absence of the specific pathogenic variants already found in the family. If a family member tests negative under these circumstances, the test is a true negative that eliminates any elevated risk due to this person having an affected relative. Proper Interpretation of Genetic and Genomic Testing The key to proper interpretation and use of genetic and genomic testing is to recognize its probabilistic nature (see earlier). Unfortunately, genetic and genomic testing have been mischaracterized by some as being deterministic: that one’s fate is wholly determined by one’s gene variants. In fact, genetic and genomic testing performance characteristics are exactly analogous to any other medical test. All medical tests have higher positive predictive values in diagnostic settings as opposed to screening settings. This is another implication of bayesian probability because in a diagnostic setting, the prior probability of disease is much higher than it is in a screening setting. Just as for any other medical test, genetic and genomic testing are context dependent, and the clinician must take that context into account when determining the next steps for their patient. Genetic and genomic testing is a powerful tool, and when coupled with proper risk assessment and genetic counseling, patients can be provided with medical information that can be life saving and life altering. ▶

CHAPTER 17 — Genetic Counseling and Risk Assessment 387 increased rate of homozygous variants. When parental samples are submitted for duo or trio exome/genome sequencing, which is preferred to augme...

Ch17 · Pt16 388 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE GENERAL REFERENCES Buckingham L: Molecular diagnostics: fundamentals, methods and clinical applications, ed 2, Philadelphia, 2011, F. A. Davis and Co. Clarke A, Murray A, Sampson J: Harper’s practical genetic counselling, ed 8, Boca Raton, 2019, CRC Press. http://doi.org/10.1201/ 9780367371944 Gardner RJM, Sutherland GR, Shaffer LG: Chromosome abnormalities and genetic counseling, ed 4, Oxford, 2011, Oxford University Press. Le Roy BS, Mc Carthy P, Veach NP: Genetic counseling practice, advanced concepts and skills, ed 2, New York, 2021, Wiley Blackwell. Uhlmann WR, Schuette JL, Yashar B: A guide to genetic counseling, ed 2, New York, 2009, Wiley-Liss. Young ID: Introduction to risk calculation in genetic counseling, ed 3, New York, 2007, Oxford University Press. REFERENCES FOR SPECIFIC TOPICS Alfares A, Aloraini T, Subaie LA, et al: Whole-genome sequencing offers additional but limited clinical utility compared with reanalysis of whole-exome sequencing, Genet Med 20(11):1328–1333, 2019. https://doi.org/10.1038/gim.2018.41 Biesecker LG, Green RC: Diagnostic clinical genome and exome sequencing, N Engl J Med 370:2418–2425, 2014. Borle K, Morris E, Inglis A, et al: Risk communication in genetic counseling: exploring uptake an perceptions of recurrence numbers, and their impact on patient outcomes, Clin Genet 94(2): 239–245, 2018. Brock JA, Allen VM, Keiser K, et al: Family history screening: use of the three generation pedigree in clinical practice, J Obstet Gynaecol Can 32:663–672, 2010. Guttmacher AE, Collins FS, Carmona RH: The family history—more important than ever, N Engl J Med 351:2333–2336, 2004. Miller DT, Adam MP, Aradhya S, et al: Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies, Am J Hum Genet 86:749–764, 2010. Miller DT, Lee K, Chung WK, et al: ACMG SF v 3.0 list for reporting of secondary findings in clinical exome and genome sequencing: a policy statement of the American College of Medical Genetics and Genomics (ACMG), Genet Med 23(8):1381–1390, 2021. https://doi. org/10.1038/s 41436-021-01172-3 National Society of Genetic Counselors: Genetic testing of minors for adult-onset conditions, position statement. https://www.nsgc. org/Policy-Research-and-Publications/Position-Statements/Position- Statements/Post/genetic-testing-of-minors-for-adult-onset-conditions Online Mendelian Inheritance in Man, OMIM®. Mc Kusick-Nathans Institute of Genetic Medicine, Johns Hopkins University (Baltimore, MD), {date}. World Wide Web. https://omim.org/statistics/gene Map Posey JE, Rosenfeld JA, James RA, et al: Molecular diagnostic experience of whole-exome sequencing in adult patients, Genet Med 18(7):678–685, 2016. https://doi.org/10.1038/gim.2015.142 Resta R, Biesecker BB, Bennett RL, et al: A new definition of genetic counseling: National Society of Genetic Counselors’ Task Force Report, J Genet Couns 15(2):77–83, 2006. Retterer K, Juusola J, Cho MT, et al: Clinical application of whole- exome sequencing across clinical indications, Genet Med 18(7): 696–704, 2016. https://doi.org/10.1038/gim.2015.148 Richards S, Aziz N, Bale S, et al: Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology, Genet Med Off J Am Coll Med Genet 17(5):405–424, 2015. https://doi.org/10.1038/gim.2015.30 Sheridan E, Wright J, Small N, et al: Risk factors for congenital anomaly in a multiethnic birth cohort: an analysis of the Born in Bradford study, Lancet 382:1350–1359, 2013. Yang Y, Muzny DM, Reid JG, et al: Clinical whole-exome sequencing for the diagnosis of mendelian disorders, N Engl J Med 369: 1502–1511, 2013. Zhang VW, Wang J: Determination of the clinical significance of an unclassified variant, Methods Mol Biol 837:337–348, 2012. PROBLEMS 1. Meera’s maternal grandfather, Dhruv, had congenital stationary night blindness (CSNB), which also affected Dhruv’s maternal uncle, Jay; the family history appears to fit an X-linked inheritance pattern. (There are also autosomal dominant and recessive forms.) Whether Dhruv’s mother was affected is unknown. Meera and Steven have a daughter, Elsie, and sons, Zack and Peter, all unaffected by CSNB. Elsie is planning to have children and wonders whether she might be a carrier of a serious eye condition. Sketch the pedigree, and answer the following. a. What is the chance that Elsie is a carrier of X-linked CSNB? b. An ophthalmologist reviews the clinical notes from the affected individuals and considers that they were more likely to have had an autosomal form of the disorder, rather than X-linked. There is no evidence that Meera’s mother, Rosemary, was affected. On this basis, what is the chance that Elsie is a carrier for an autosomal form of CSNB? 2. A deceased boy, Nathan, was the only member of his family with Duchenne muscular dystrophy (DMD). He is survived by two sisters, Norma (who has a daughter, Olive) and Nancy (who has a daughter, Odette). His mother, Molly, has two sisters, Maud and Martha. Martha has two unaffected sons and two daughters, Nora and Nellie. Maud has one daughter, Naomi. No carrier tests are available because the variant in the affected boy remains unknown. a. Sketch the pedigree, and calculate the posterior risks for all these females, using information provided in this chapter. b. Suppose prenatal diagnosis by DNA analysis is available only to women with more than a 2% risk that a pregnancy will result in a son with DMD. Which of these women would not qualify? 3. What is the probability of 13 successive male births? What is the probability of 13 successive births of a single sex? What is the probability that after 13 male births, the 14th child will be a boy? 4. Let H be the population frequency of carriers of hemophilia A. The incidence of hemophilia A in males (I) equals the chance that a maternal F8 gene has a new pathogenic variant (µ) plus the chance it was inherited as a preexisting variant from a carrier mother ( 12 × H). Adding these two terms gives I = µ + ( 12 × H). H is the sum of the chance a reproducing affected father (I × f) (where f is the fitness of hemophilia) transmits his variant plus the chance of a new paternal pathogenic variant (µ) plus the chance of a new maternal pathogenic variant (µ) plus ▶

388 THOMPSON AND THOMPSON GENETICS AND GENOMICS IN MEDICINE GENERAL REFERENCES Buckingham L: Molecular diagnostics: fundamentals, methods and clinical applications, ed 2, Philadelphia, 2011, F. A. Dav...

Ch17 · Pt17 CHAPTER 17 — Genetic Counseling and Risk Assessment 389 the chance of inheriting a variant from a carrier mother ( 12 × H). Adding these four terms gives H = (I × f) + µ + µ + ( 12)H. a. If hemophilia A has a fitness (f) of ~0.70—that is, hemophiliacs have ~70% as many offspring as do controls—then what is the incidence of affected males? Of carrier females? (Answer in terms of multiples of the mutation rate.) If a woman has a son with an isolated case of hemophilia A, what is the risk that she is a carrier? What is the chance that her next son will be affected? b. For DMD, f = 0. What is the population frequency of affected males? Of carrier females? c. Color blindness is thought to have normal fitness (f = 1). What is the incidence of carrier females if the frequency of color blind males is 8%? 5. Ira and Margie each have a sibling affected with cystic fibrosis. a. What are their prior risks for being carriers? b. What is the risk for their having an affected child in their first pregnancy together? c. They have had three unaffected children and now wish to know their risk for having an affected child before considering genetic testing. Using bayesian analysis to take into consideration that they have already had three unaffected children, calculate the chance that their next child will be affected. I II III IV?? 1 2 1 2 3 2? 2 3 2 1? 6. A 30-year-old woman with myotonic dystrophy comes in for genetic counseling. Her son, age 14 years, shows no symptoms, but she wishes to know whether he will be affected with this autosomal dominant condition later in life. Approximately half of individuals carrying the gene with a pathogenic variant are asymptomatic before the age of 14 years. What is the risk that the son will eventually develop myotonic dystrophy? Should you test the child for the expanded repeat in the gene for myotonic dystrophy? 7. A couple arrives in your clinic with their 7-month-old son, who has been moderately developmentally delayed from birth. The couple is contemplating having additional children, and you are asked whether this could be a genetic condition. a. Is this possible, and if so, what pattern or patterns of inheritance would fit this story? b. On taking a detailed family history, you learn that both parents’ families were originally from the same small village in northern Italy. How might this fact alter your assessment of the case? c. You next learn that the mother has two sisters and five brothers. Both sisters have developmentally delayed children. How might this alter your assessment of the case? 8. A couple returns for genetic counseling to discuss their genetic test results for Tay Sachs disease. Their daughter (Ananya) has symptoms consistent with Tach-Sachs disease. Additionally, Ananya had near-absent HEX A enzymatic activity and HEXA sequencing that identified one pathogenic variant and one variant of unknown significance (VUS). Parental testing revealed that both the pathogenic variant and VUS were maternally inherited. What is the interpretation of this result? ▶

CHAPTER 17 — Genetic Counseling and Risk Assessment 389 the chance of inheriting a variant from a carrier mother ( 12 × H). Adding these four terms gives H = (I × f) + µ + µ + ( 12)H. a. If hemophili...

🧬 Part 9: Cancer Genetics and Genetic Counseling English

Chapter 16: Cancer Genetics and Genomics

Chapter 17: Genetic Counseling and Risk Assessment