Cancer Genetics Overview (PDQ®)–Health Professional Version

Levels of Cancer Risk

Different hereditary cancer genes are associated with varying levels of cancer risk. This cancer risk can also vary among pathogenic/likely pathogenic (P/LP) variants in the same gene. Rare genetic variants are generally associated with higher cancer risks than common genetic variants. This is depicted in Figure 1.

In some genes, P/LP variants increase an individual's risk of developing cancer at a younger age than that typically seen in the general population.

Cancer risk is multifactorial. It is influenced by genetic, environmental, medical, and lifestyle factors. These nongenetic factors impact cancer risk in individuals who carry a P/LP variant in genes like BRCA1 or BRCA2. For more information, see the Introduction and the Polygenic risk scores for breast and ovarian cancer sections in Genetics of Breast and Gynecologic Cancers.

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Available genetic testing expands as more genetic variants are identified and their associated cancer risks are characterized.

Associated Cancers

Cancer risks vary based on the hereditary cancer gene and pathogenic variant involved. For example, P/LP variants in BRCA1 and BRCA2 are associated with breast, ovarian, pancreatic, and other cancers.

Types of Genetic Variants in the Context of Cancer Genetics

[Note: Somatic variants have various nuances, like the concepts of mosaicism, gonadal mosaicism, and clonal hematopoiesis of indeterminate potential.]

For more information about germline genetic testing and somatic genetic testing, see the Clinical Applications section.

Variant Classifications for Hereditary Cancer Genetic Testing

Variants (i.e., genetic changes) are classified as pathogenic, likely pathogenic, of uncertain significance, benign, or likely benign.[1] Variant classification is based on whether a variant is associated with disease. Genetic variant studies research how variants are associated with specific diseases.

Variants may be referred to as secondary or incidental findings:

Inheritance Patterns for Hereditary Cancer Risk

Hereditary cancer risk is inherited differently, depending on the indicated gene. Most hereditary cancer risks are inherited in an autosomal dominant fashion. In autosomal dominant inheritance, an individual is at risk to develop cancer when he/she inherits one pathogenic variant (in one of the two copies of the gene). Some hereditary cancer syndromes have other inheritance patterns (e.g., MUTYH-associated polyposis is inherited in an autosomal recessive fashion).

For more information about how to recognize hereditary cancer inheritance patterns, see the Analysis of the family history section in Cancer Genetics Risk Assessment and Counseling.

Linkage Analyses

Since it was recognized that cancer clusters in families, investigators have collected data on families with multiple cancer cases. The investigators aimed to localize cancer susceptibility genes via linkage studies.

Linkage studies are typically performed on high-risk kindreds, in whom multiple cases of a particular disease have occurred, in an effort to identify disease susceptibility genes. Linkage analysis statistically compares the genotypes between affected and unaffected individuals. Linkage analysis also seeks evidence that known genetic markers are inherited along with the disease trait. If such evidence is found (linkage), it provides statistical data that the chromosomal region near the known genetic marker also harbors a disease susceptibility gene. Once a genomic region of interest has been identified through linkage analysis, additional studies are required to prove that there truly is a susceptibility gene at this position. Linkage analysis is affected by the following:

An additional issue in linkage studies is the background rate of sporadic cancer in the context of family studies. For example, because a man’s lifetime risk of prostate cancer is one in eight,[1] it is possible that families under study have both inherited and sporadic prostate cancer cases. Thus, a male may still develop prostate cancer, even if he does not inherit the prostate cancer susceptibility gene that is present in his family. Hence, studies have addressed inconsistencies between linkage data by requiring strict inclusion criteria that define clinically significant disease.[2-6] This approach attempts to define a homogeneous set of cases/families to increase the likelihood of identifying a linkage signal.

Genome-Wide Association Studies (GWAS)

GWAS are identifying common, low-penetrance susceptibility alleles for many complex diseases,[7] including cancer. This approach can be contrasted with linkage analysis, which searches for genetic-risk variants cosegregating within families that have a high prevalence of disease. While linkage analyses are designed to uncover rare, highly penetrant variants that segregate in predictable heritance patterns (e.g., autosomal dominant, autosomal recessive, X-linked, and mitochondrial), GWAS are best suited to identify multiple, common, low-penetrance genetic polymorphisms. GWAS are conducted under the assumption that the genetic underpinnings of complex phenotypes, such as prostate cancer, are governed by many alleles, each conferring modest risk. Most genetic polymorphisms genotyped in GWAS are common, with minor allele frequencies greater than 1% to 5% within a given population (e.g., men of European ancestry). GWAS capture a large portion of common variation across the genome.[8,9] The strong correlation between many alleles located close to one another on a given chromosome (called linkage disequilibrium) allows one to “scan” the genome without having to test all 10 million known single nucleotide variants (SNVs). With GWAS, researchers can test approximately 1 million to 5 million SNVs per study and ascertain almost all common inherited variants in the genome.

In a GWAS, allele frequency for each SNV is compared between cases and controls. Promising signals—in which allele frequencies deviate significantly in case compared to control populations—are validated in replication cohorts. To have adequate statistical power to identify variants associated with a phenotype, large numbers of cases and controls, typically thousands of each, are studied. Because up to 1 million SNVs are evaluated in a GWAS, false-positive findings are expected to occur frequently when using standard statistical thresholds. Therefore, stringent statistical rules are used to declare a positive finding, usually using a threshold of P < 1 × 10-7.[10-12]

To date, thousands of cancer-risk variants have been identified by well-powered GWAS and validated in independent cohorts.[13] These studies have revealed consistent associations between specific inherited variants and cancer risk. However, the findings should be qualified with a few important considerations:

Implications of these points and how they relate to polygenic risk scores are discussed further in the Polygenic risk scores for breast and ovarian cancer section in Genetics of Breast and Gynecologic Cancers, the Genetic Polymorphisms and CRC Risk section in Genetics of Colorectal Cancer, and the Common Risk Variants and Polygenic Risk Scores for Prostate Cancer section in Genetics of Prostate Cancer.

Introduction

Broad-scale genome sequencing approaches, including multigene (panel) testing, whole-exome sequencing (WES), and whole-genome sequencing (WGS), are rapidly being developed and incorporated into a spectrum of clinical oncologic settings, including cancer therapeutics and cancer risk assessment. Several institutions and companies offer tumor sequencing, and some are developing precision medicine programs that sequence tumor genomes to identify driver genetic alterations that are targetable for therapeutic benefit to patients.[1-3] Many of these tumor-based approaches use germline DNA sequences as a reference to discriminate between DNA changes only within the tumor and those that are potentially inherited. In the genetic counseling and cancer risk assessment setting, the use of multigene testing to evaluate inherited cancer risk is becoming more common and may become routine in the near future, with institutions and companies offering multigene testing to detect alterations in a host of cancer risk–associated genes.

These advances in gene sequencing technologies also identify variants in genes related to the primary indication for ordering genetic sequence testing, along with findings not related to the disorder being tested. The latter genetic findings, termed incidental or secondary findings, are currently a source of clinical, ethical, legal, and counseling debate. The American College of Medical Genetics and Genomics (ACMG) and the Presidential Commission for the Study of Bioethical Issues have published literature that address some of these issues and provide guidance and recommendations for their use.[4-7] However, controversy continues about when and what results to provide to patients and their health care providers. This section was created to provide information about genomic sequencing technologies in the context of clinical sequencing and highlights additional areas of clinical uncertainty for which further research and approaches are needed.

Background

DNA sequencing technologies have undergone rapid evolution, particularly since 2005 when massively parallel sequencing, or next-generation sequencing (NGS), was introduced.[8]

Automated Sanger sequencing is considered the first generation of sequencing technology.[9] Sanger cancer gene sequencing uses polymerase chain reaction (PCR) amplification of genetic regions of interest followed by sequencing of PCR products using fluorescently labeled terminators, capillary electrophoresis separation of products, and laser signal detection of nucleotide sequence.[10,11] While this is an accurate sequencing technology, the main limitations of Sanger sequencing include low throughput, a limited ability to sequence more than a few genes at a time, and the inability to detect structural rearrangements.[10]

NGS refers to high throughput DNA sequencing technologies that are capable of processing multiple DNA sequences in parallel.[11] Although platforms differ in template generation and sequence interrogation, the overall approach to NGS technologies involves shearing and immobilizing DNA template molecules onto a solid surface, which allows separation of molecules for simultaneous sequencing reactions (millions to billions) to be performed in a parallel fashion.[10,12] Thus, the major advantages of NGS technologies include the ability to sequence thousands of genes at one time, a lower cost, and the ability to detect multiple types of genomic alterations, such as insertions, deletions, copy number alterations, and rearrangements.[10] Limitations include the possibility that specific gene regions may be missed, turnaround time can be lengthy (although it is decreasing), and informatics support to handle massive amounts of genetic data has lagged behind the sequencing capability. A well-recognized bottleneck to utilizing NGS data is the lack of advanced computational infrastructure to preserve, process, and analyze the vast amount of genetic data. The magnitude of the variants obtained from NGS is exponential; bioinformatics approaches need to evaluate genetic variants for predicted functional consequence in disease biology. There is also a need for user-friendly bioinformatics pipelines to analyze and integrate genetic data to influence the scientific and medical community.[11,13]

Clinical Applications

NGS has multiple clinical applications. In oncology, the two dominant applications are: 1) the assessment of somatic alterations in tumors to inform prognosis and/or targeted therapeutics; and 2) the assessment of the germline to identify cancer risk alleles.

Governance, Interpretation, and Institutional Oversight of Next-Generation Sequencing (NGS)

The ACCE model uses four main components to evaluate new genetic tests: analytic validity; clinical validity; clinical utility; and ethical, legal, and social issues.[17]

The ACCE model's framework has been adopted worldwide for the evaluation of genetic tests.

Several layers of complexity exist in managing NGS in the clinical setting. At the purely technical level, improvements in the sequencing technique have allowed for sequencing across the entire genome, not merely the exome. As the costs decrease, exomic and genomic sequencing of tumor and normal tissue can be expected to become more routine.

With routine use of WGS, major challenges in interpretation emerge. Foremost is the matter of determining which sequence variations in known cancer predisposition genes are pathologic, which are harmless, and which variations require further evaluation as to their significance. This is not a new challenge. Various groups are developing processes for the interpretation and curation of a growing database of variants and their significance. For example, the International Society for Gastrointestinal Hereditary Tumors has developed such a process for the MMR genes in concert with the Human Variome Project and International Mismatch Repair Consortium.

These processes may serve as a framework for the emerging challenge of interpreting the significance of sequence variations in genes of uncertain or unknown function in regulation of neoplastic progression or other diseases. Larger cancer predisposition multigene tests have been developed by commercial laboratories, with their own process for interpretation. To the extent that increasingly larger multigene tests include genes of unknown significance, governance of the interpretation process requires that academic institutions offering their own multigene tests or using external proprietary panels develop a deliberative process for managing the quality assurance for test performance (including Clinical Laboratory Improvement Amendments [CLIA], where appropriate) and interpretation.

ACMG has issued the following updated guidelines for achieving accountability in interpreting and reporting secondary findings:[4,18]

Concerns remain that the routine reporting of germline variants in the context of tumor sequencing would require laboratories to conduct results review with germline and tumor genome expertise, which would be expected to increase costs, laboratory efforts, and turnaround time for results reporting. The nature of discussions between oncologists and patients would be altered to include the multiple facets involved with germline testing and potential results. Pre- and post-test discussions would also potentially require involvement of genetic counselors and geneticists, who are a limited resource in oncology practices. Recent expert comment stated that more data are needed about the benefits of return of secondary germline findings to cancer patients undergoing tumor sequencing, citing a need for recommendations by experts in the oncology and genetics communities.[19]

It is still very early in the development processes for oversight at the institutional level. As an example, at one high-volume cancer center, the following process has been used:

Informed Consent Issues Arising From the Application of NGS

Informed consent for the sequencing of highly penetrant disease genes has been conducted since the mid-1990s in the contexts of known or suspected inherited diseases within selected families. However, the best methods and approaches for educating and counseling individuals about the potential benefits, limitations, and harms of genetic testing to facilitate informed decisions have not been fully elucidated or adequately tested. New informed consent challenges arise as NGS technologies are applied in clinical and research settings. Challenges to facilitating informed consent include the following:

The increased availability and decreased cost of NGS technology are expanding the use of genome-wide testing of tumors, with the goal of identifying somatic variants as potential targets for cancer treatment. While identifying germline pathogenic variants may be considered secondary to the main purpose of testing tumors, the possibility of identifying actionable secondary findings of pathogenic variants in cancer predisposition genes supports the need for genetic counseling in this context. Approaches for genetic counseling and informed consent in the context of tumor sequencing have been proposed.[20,21]

Conclusion

Advances in genetic sequencing technologies have dramatically reduced the cost of sequencing an individual's full genome or exome. WGS and WES are increasingly being employed in the clinical setting in testing for both somatic variants and germline variants. In addition, multigene tests are now available commercially or within an institution. Considerable debate surrounds the clinical, ethical, legal, and counseling aspects associated with NGS and gene panels. Future research is warranted to address these issues.

Purpose of This Summary

This PDQ cancer information summary for health professionals provides comprehensive, peer-reviewed, evidence-based information about cancer genetics. It is intended as a resource to inform and assist clinicians in the care of their patients. It does not provide formal guidelines or recommendations for making health care decisions.

Reviewers and Updates

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Levels of Evidence

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PDQ® Cancer Genetics Editorial Board. PDQ Cancer Genetics Overview. Bethesda, MD: National Cancer Institute. Updated <MM/DD/YYYY>. Available at: https://www.cancer.gov/publications/pdq/information-summaries/genetics/overview-hp-pdq. Accessed <MM/DD/YYYY>. [PMID: 26389204]

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