Large numbers of individuals are required to classify and define risk for rare variants in known cancer risk genes

Clinical implications of conflicting variant interpretations in the cancer genetics clinic

PURPOSE

The aim of this study was to describe the clinical impact of commercial laboratories issuing conflicting classifications of genetic variants.

METHODS

Results from 2000 patients undergoing a multigene hereditary cancer panel by a single laboratory were analyzed. Clinically significant discrepancies between the laboratory-provided test reports and other major commercial laboratories were identified, including differences between pathogenic/likely pathogenic and variant of uncertain significance (VUS) classifications, via review of ClinVar archives. For patients carrying a VUS, clinical documentation was assessed for evidence of provider awareness of the conflict.

RESULTS

Fifty of 975 (5.1%) patients with non-negative results carried a variant with a clinically significant conflict, 19 with a pathogenic/likely pathogenic variant reported in APC or MUTYH, and 31 with a VUS reported in CDKN2A, CHEK2, MLH1, MSH2, MUTYH, RAD51C, or TP53. Only 10 of 28 (36%) patients with a VUS with a clinically significant conflict had a documented discussion by a provider about the conflict. Discrepant counseling strategies were used for different patients with the same variant. Among patients with a CDKN2A variant or a monoallelic MUTYH variant, providers were significantly more likely to make recommendations based on the laboratory-reported classification.

CONCLUSION

Our findings highlight the frequency of variant interpretation discrepancies and importance of clinician awareness. Guidance is needed on managing patients with discrepant variants to support accurate risk assessment.

Modeling the impact of data sharing on variant classification

OBJECTIVE

Many genetic variants are classified, but many more are variants of uncertain significance (VUS). Clinical observations of patients and their families may provide sufficient evidence to classify VUS. Understanding how long it takes to accumulate sufficient patient data to classify VUS can inform decisions in data sharing, disease management, and functional assay development.

MATERIALS AND METHODS

Our software models the accumulation of clinical evidence (and excludes all other types of evidence) to measure their unique impact on variant interpretation. We illustrate the time and probability for VUS classification when laboratories share evidence, when they silo evidence, and when they share only variant interpretations.

RESULTS

Using conservative assumptions for frequencies of observed clinical evidence, our models show the probability of classifying rare pathogenic variants with an allele frequency of 1/100 000 increases from less than 25% with no data sharing to nearly 80% after one year when labs share data, with nearly 100% classification after 5 years. Conversely, our models found that extremely rare (1/1 000 000) variants have a low probability of classification using only clinical data.

DISCUSSION

These results quantify the utility of data sharing and demonstrate the importance of alternative lines of evidence for interpreting rare variants. Understanding variant classification circumstances and timelines provides valuable insight for data owners, patients, and service providers. While our modeling parameters are based on our own assumptions of the rate of accumulation of clinical observations, users may download the software and run simulations with updated parameters.

CONCLUSIONS

The modeling software is available at https://github.com/BRCAChallenge/classification-timelines.

An Algorithm for Optimal Testing in Co‐segregation Analysis

Clinical genetic sequencing tests often identify variants of uncertain significance. One source of data that can help classify the pathogenicity of variants is familial cosegregation analysis. Identifying and genotyping relatives for cosegregation analysis can be time consuming and costly. We propose an algorithm that describes a single measure of expected variant information gain from genotyping a single additional relative in a family. Then we explore the performance of this algorithm by comparing actual recruitment strategies used in 35 families who had pursued cosegregation analysis with synthetic pedigrees of possible testing outcomes if the families had pursued an optimized testing strategy instead. For each actual and synthetic pedigree, we calculated the likelihood ratio of pathogenicity as each successive test was added to the pedigree. We analyzed the differences in cosegregation likelihood ratio over time resulting from actual versus optimized testing approaches. Employing the testing strategy indicated by the algorithm would have led to maximal information more rapidly in 30 of the 35 pedigrees (86%). Many clinical and research laboratories are involved in targeted cosegregation analysis. The algorithm we present can facilitate a data driven approach to optimal relative recruitment and genotyping for cosegregation analysis and more efficient variant classification.

Patient goals, motivations, and attitudes in a patient-driven variant reclassification study

Family studies to reclassify clinically ascertained variants of uncertain significance (VUS) can impact risk assessment, medical management, and psychological outcomes for patients and their families. There are limited avenues for patients and their families to actively participate in VUS reclassification, and access to family studies at most commercial laboratories is restricted by multiple factors. To explore patient attitudes about participation in family studies for VUS reclassification, we conducted semistructured pre- and post-participation telephone interviews with 38 participants in a family-based VUS reclassification study that utilized a patient-driven approach for family ascertainment and recruitment. Participants had VUS from multigene panel testing performed at multiple clinical laboratories for cancer or other disease risk. Inductive thematic analysis of transcribed interviews highlighted four major themes: (a) Participants' study goals were driven by the desire to resolve uncertainty related to the VUS, (b) Participants had mixed reactions to the VUS reclassification outcomes of the study, (c) Personal, public, and familial knowledge increased through study participation and (d) Participants used study participation to actively cope with the uncertainty of a VUS. As personalized genomic medicine becomes more prevalent, clinicians, clinical laboratories, and researchers could consider creating more opportunities for active partnership with patients and families, who are motivated to contribute data to familial VUS studies.

Power of pedigree likelihood analysis in extended pedigrees to classify rare variants of uncertain significance in cancer risk genes

Rare and private variants of uncertain significance (VUS) are routinely identified in clinical panel, exome, and genome sequencing. We investigated the power of single family co-segregation analysis to aid classification of VUS. We simulated thousands of pedigrees using demographics in China and the United States, segregating benign and pathogenic variants. Genotypes and phenotypes were simulated using penetrance models for Lynch syndrome and breast/ovarian cancer. We calculated LOD scores adjusted for proband ascertainment (LODadj), to determine power to yield quantitative evidence for, or against, pathogenicity of the VUS. Power to classify VUS was higher for Chinese than United States pedigrees. The number of affected individuals explained the most variation in LODadj (21-38%). The distance to the furthest affected relative (FAR) from the proband explained 1-7% of the variation for the benign VUS and Lynch associated cancers. Minimum age of onset (MAO) explained 5-13% of the variation in families with pathogenic breast/ovarian cancer variants. Random removal of 50% of the phenotype/genotype data reduced power and the variation in LODadj was best explained by FAR followed by the number of affected individuals and MAO when the founder was only two generations from the proband. Power to classify benign variants was ~2x power to classify pathogenic variants. Affecteds-only analysis resulted in virtually no power to correctly classify benign variants and reduced power to classify pathogenic variants. These results can be used to guide recruitment efforts to classify rare and private VUS.

EXAMINING EVIDENCE IN U.S. PAYER COVERAGE POLICIES FOR MULTI-GENE PANELS AND SEQUENCING TESTS

OBJECTIVES

The aim of this study was to examine the evidence payers cited in their coverage policies for multi-gene panels and sequencing tests (panels), and to compare these findings with the evidence payers cited in their coverage policies for other types of medical interventions.

METHODS

We used the University of California at San Francisco TRANSPERS Payer Coverage Registry to identify coverage policies for panels issued by five of the largest US private payers. We reviewed each policy and categorized the evidence cited within as: clinical studies, systematic reviews, technology assessments, cost-effectiveness analyses (CEAs), budget impact studies, and clinical guidelines. We compared the evidence cited in these coverage policies for panels with the evidence cited in policies for other intervention types (pharmaceuticals, medical devices, diagnostic tests and imaging, and surgical interventions) as reported in a previous study.

RESULTS

Fifty-five coverage policies for panels were included. On average, payers cited clinical guidelines in 84 percent of their coverage policies (range, 73-100 percent), clinical studies in 69 percent (50-87 percent), technology assessments 47 percent (33-86 percent), systematic reviews or meta-analyses 31 percent (7-71 percent), and CEAs 5 percent (0-7 percent). No payers cited budget impact studies in their policies. Payers less often cited clinical studies, systematic reviews, technology assessments, and CEAs in their coverage policies for panels than in their policies for other intervention types. Payers cited clinical guidelines in a comparable proportion of policies for panels and other technology types.

CONCLUSIONS

Payers in our sample less often cited clinical studies and other evidence types in their coverage policies for panels than they did in their coverage policies for other types of medical interventions.

Power to the People: Data Citizens in the Age of Precision Medicine

Twentieth-century bioethics celebrated individual autonomy but framed autonomy largely in terms of an individual's power to make decisions and act alone. The most pressing challenges of big data science in the twenty-first century can only be resolved through collective action and common purpose. This Article surveys some of these challenges and asks how common purpose can ever emerge on the present bioethical and regulatory landscape. The solution may lie in embracing a broader concept of autonomy that empowers individuals to protect their interests by exercising meaningful rights of data citizenship. This Article argues that twentieth-century bioethics was a paternalistic, top-down affair in which self-proclaimed ethics experts set standards to protect research subjects portrayed as autonomous yet too vulnerable and disorganized to protect themselves. The time may be ripe for BioEXIT, a popular uprising of regular people seeking a meaningful voice in establishing citizen-led ethical and privacy standards to advance big-data science while addressing the concerns people feel about the privacy of their health data.

Whole-Genome Sequencing in Healthy People

Recent technological advances have radically changed genetic testing from an expensive and burdensome undertaking to a rapid and less costly option for many purposes. The utility of "next-generation" sequencing has been found to establish the diagnosis for hundreds of genetic disorders, to assess pharmacogenomic variants, and to identify treatable targets within malignant neoplasms. The ready availability of genomic information has led to the question of whether there would be clinical benefit of sequencing the genome of individuals who are not seeking a diagnosis, that is, genomic screening in generally healthy people, to provide anticipatory insights for their health care. Little research has been conducted in this area. We examine the considerable unresolved scientific and ethical issues encountered when considering whole-genome sequencing of healthy people.

Barbarians at the Gate: Consumer-Driven Health Data Commons and the Transformation of Citizen Science

"The expression 'barbarians at the gate' was … used by the Romans to describe foreign attacks against their empire." ¹ "[It] is often used in contemporary English within a sarcastic, or ironic context, when speaking about a perceived threat from a rival group of people, often deemed to be less capable or somehow 'primitive.'" ².

Family-Specific Variants and the Limits of Human Genetics

Every single-nucleotide change compatible with life is present in the human population today. Understanding these rare human variants defines an extraordinary challenge for genetics and medicine. The new clinical practice of sequencing many genes for hereditary cancer risk has illustrated the utility of clinical next-generation sequencing in adults, identifying more medically actionable variants than single-gene testing. However, it has also revealed a linear relationship between the length of DNA evaluated and the number of rare 'variants of uncertain significance' reported. We propose that careful approaches to phenotype-genotype inference, distinguishing between diagnostic and screening intent, in conjunction with expanded use of family-scale genetics studies as a source of information on family-specific variants, will reduce variants of uncertain significance reported to patients.

Family Studies for Classification of Variants of Uncertain Classification: Current Laboratory Clinical Practice and a New Web-Based Educational Tool

Multi-gene cancer panels often identify variants of uncertain clinical significance (VUS) that pose a challenge to health care providers in managing a patient's cancer risk. Family segregation analysis can yield powerful data to re-classify a VUS (as either benign or pathogenic). However, financial and personnel resources to coordinate these studies are limited. In an informal assessment we found that family studies for variant classification are done by most clinical genetics laboratories that offer hereditary cancer panel testing. The process for family studies differs substantially across laboratories. One near universal limitation is that families usually have too few individuals for an informative co-segregation analysis. A unique and potential resource-saving approach is to engage patients and their families in expanding their own pedigrees for segregation analysis of their VUS. We describe a novel public educational tool ( FindMyVariant.org ) designed to inform patients and genetic counselors about strategies to improve the probability of variant classification using familial segregation. While the web tool is designed to be useful for any gene, the project was primarily focused on VUS's returned in cancer risk genes. FindMyVariant.org is a resource for genetic providers to offer motivated families who are willing to gather information about their family relationships and history. Working alongside clinical or research genetic laboratories, the information they collect may help reclassify their VUS using segregation analysis.

Genetic architecture of colorectal cancer

Colorectal cancer (CRC) is a complex disease that develops as a consequence of both genetic and environmental risk factors. A small proportion (3-5%) of cases arise from hereditary syndromes predisposing to early onset CRC as a result of mutations in over a dozen well defined genes. In contrast, CRC is predominantly a late onset 'sporadic' disease, developing in individuals with no obvious hereditary syndrome. In recent years, genome wide association studies have discovered that over 40 genetic regions are associated with weak effects on sporadic CRC, and it has been estimated that increasingly large genome wide scans will identify many additional novel genetic regions. Subsequent experimental validations have identified the causally related variant(s) in a limited number of these genetic regions. Further biological insight could be obtained through ethnically diverse study populations, larger genetic sequencing studies and development of higher throughput functional experiments. Along with inherited variation, integration of the tumour genome may shed light on the carcinogenic processes in CRC. In addition to summarising the genetic architecture of CRC, this review discusses genetic factors that modify environmental predictors of CRC, as well as examples of how genetic insight has improved clinical surveillance, prevention and treatment strategies. In summary, substantial progress has been made in uncovering the genetic architecture of CRC, and continued research efforts are expected to identify additional genetic risk factors that further our biological understanding of this disease. Subsequently these new insights will lead to improved treatment and prevention of colorectal cancer.

The challenge of comprehensive and consistent sequence variant interpretation between clinical laboratories

PURPOSE

Genetic testing has shifted from academic laboratories with expertise in specific genes to commercial laboratories that offer tests of a diverse array of genes. The purpose of this comparative study was to determine whether one academic laboratory's model of variant interpretation is similar to that of several commercial laboratories.

METHODS

The Collagen Diagnostic Laboratory (CDL) received, over a 14-month period, 38 requests to interpret variants originally identified by an outside laboratory (OL). The interpretations by the OL and CDL were compared and discrepancies were assessed.

RESULTS

Interpretations from the OL and CDL were concordant in 11 inquiries (29%); discrepancies were moderate in 11 instances (29%) and significant in 16 (42%). Factors that caused discrepancies included the following: (i) private data were not shared in a public database (n = 9); (ii) publicly available allele frequency data were not referenced and used as evidence (n = 5); and (iii) important aspects of protein structure and function were not taken into account (n = 13).

CONCLUSION

Comprehensive interpretation of sequence variants depends on good functional tests and well-curated variant databases. Provision of clinical information to the clinical laboratory, mandatory submission of identified variants with phenotype data to common resources, and collaboration between clinical laboratories and recognized experts is likely to improve consistency in variant interpretation among clinical laboratories.Genet Med 18 1, 20-24.

Pragmatic and Ethical Challenges of Incorporating the Genome into the Electronic Medical Record

Recent successes in the use of gene sequencing for patient care highlight the potential of genomic medicine. For genomics to become a part of usual care, pertinent elements of a patient's genomic test must be communicated to the most appropriate care providers. Electronic medical records may serve as a useful tool for storing and disseminating genomic data. Yet, the structure of existing EMRs and the nature of genomic data pose a number of pragmatic and ethical challenges in their integration. Through a review of the recent genome-EMR integration literature, we explore concrete examples of these challenges, categorized under four key questions: What data will we store? How will we store it? How will we use it? How will we protect it? We conclude that genome-EMR integration requires a rigorous, multi-faceted and interdisciplinary approach of study. Problems facing the field are numerous, but few are intractable.

Economic regulation of next-generation sequencing

Next-generation sequencing broadens the debate about appropriate regulatory oversight of genetic testing and may force scholars to move beyond familiar privacy and health and safety regulatory issues to address new problems with industry structure and economic regulation. The genetic testing industry is passing through a period of profound structural change in response to shifts in technology and in the legal environment. Making genetic testing safe and effective for consumers increasingly requires access to comprehensive genomic data infrastructures that can support accurate, state-of-the-art interpretation of genetic test results. At present, there are significant barriers to access and there is no sector-specific regulator with power to ensure appropriate data access. Without it, genetic testing will not be safe for consumers even when it is performed at CLIA-certified laboratories using tests that have been FDA-cleared or approved. This article explores the emerging structure of the genetic testing industry and describes its present economic regulatory vacuum. In view of this gap in regulation, the article explores whether generally applicable law, particularly antitrust law, may offer solutions to the industry's data access problems. It concludes that courts may have a useful role to play, particularly in Europe and other jurisdictions where the essential facilities doctrine enjoys continued vitality. After Verizon Communications v. Law Offices of Curtis V. Trinko, the role of U.S. federal courts is less certain. Congress has demonstrated willingness to address access issues as they emerged in other infrastructure industries in recent decades. This article expresses no preference between legislative and judicial solutions. Its aim is simply to highlight an emerging economic regulatory issue which, if left unresolved, presents real health and safety concerns for consumers who receive genetic tests.