Lessons learned from two decades of BRCA1 and BRCA2 genetic testing: the evolution of data sharing and variant classification

Nearly a generation (~24 years) has elapsed since the identification of the breast cancer susceptibility genes, BRCA1 (ref. 1.Miki Y. et al.A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1.1:CAS:528:DyaK2MXhtF2ns70%3D10.1126/science.7545954Science. 1994; 266: 66-71Google Scholar) and BRCA2 (ref. 2.Wooster R. et al.Identification of the breast cancer susceptibility gene BRCA2.1:CAS:528:DyaK28XltFWi10.1038/378789a0Nature. 1995; 378: 789-792Google Scholar). Over that time the norms and policies surrounding the sharing of human genetic data have evolved. In this commentary, we examine the lessons learned about how data sharing can facilitate an understanding of the scope and consequences of genetic variation. Through this experience, we explore these lessons and their application to understanding human genomic variation. The sharing of data among geneticists has waxed and waned through time. A notable nadir was reached during the race to identify the genes responsible for familial breast and ovarian cancer. The search for the BRCA1 gene was characterized by intense competition and shifting alliances.3.Davies K. White M. Breakthrough: the race to find the breast cancer gene. Wiley, New York1996Google Scholar During the “gene hunt” phase, data sharing between (and even within) groups was minimal. After the BRCA1 gene was identified in 1994 (ref. 1.Miki Y. et al.A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1.1:CAS:528:DyaK2MXhtF2ns70%3D10.1126/science.7545954Science. 1994; 266: 66-71Google Scholar), several of us called for a new, more open era to guide BRCA research in the future.4.Friend S. et al.Breast cancer information on the web.1:STN:280:DyaK28%2Fkt1Gluw%3D%3D10.1038/ng1195-238Nat Genet. 1995; 11: 238-239Google Scholar A tangible outcome of this call was the creation of an open access database, the Breast Cancer Information Core (BIC), in 1995 (ref. 5.Szabo C. Masiello A. Ryan J.F. Brody L.C. The breast cancer information core: database design, structure, and scope.1:CAS:528:DC%2BD3cXlvFKgt7k%3D10.1002/1098-1004(200008)16Hum Mutat. 2000; 16 (:2<123::AID-HUMU4>3.0.CO;2-Y): 123-131Google Scholar). The mission of the BIC was to accelerate research by gathering and freely sharing information related to breast cancer genes. In particular, the BIC was established as a repository of germline variants in BRCA1 and BRCA2 (collectively, BRCA) in an effort to record all sequence variants and ensure that this information was freely available to the research community. The BIC has been in continuous operation for over two decades and has been cited in more than 2700 publications (https://research.nhgri.nih.gov/bic/). From its inception, the BIC used the then-new World Wide Web to share data with anyone with an Internet connection. The inspiration for using the web to distribute human genetic variant data came from the cystic fibrosis gene pathogenic variant database established by Lap Chi Tsui in Toronto.6.Tsui L.C. Dorfman R. The cystic fibrosis gene: a molecular genetic perspective.10.1101/cshperspect.a009472Cold Spring Harb Perspect Med. 2013; 3: a009472Google Scholar Perhaps the most well-known single-gene database at the time, this list of CFTR variants was distributed by Dr. Tsui to subscribers each month via fax. One of us (L.C.B.) sat near the fax machine and collected page after page as the CFTR “database” streamed onto the floor. In addition to saving paper, we thought that sharing information digitally would allow investigators to import and analyze the data directly. The BIC website debuted in 1995. To place this event in context, the first widely used web browser, NCSA Mosaic, was introduced in the fall of 1993; Amazon, Inc. was established in 1994; and Google would not debut for another three years. The BIC was sharing data a year before the Human Genome Project proposed the Bermuda Principles, the plan that called for the prepublication release of genomic sequences (https://web.ornl.gov/sci/techresources/Human_Genome/research/bermuda.shtml). The earliest BRCA data deposits were provided by researchers conducting sequence analyses of research participants. BIC was one of the first databases that provided free access to individual level, unpublished data, enabling the community to advance research and clinical studies.4.Friend S. et al.Breast cancer information on the web.1:STN:280:DyaK28%2Fkt1Gluw%3D%3D10.1038/ng1195-238Nat Genet. 1995; 11: 238-239Google Scholar Later, as testing moved from research to clinical labs throughout the world, the latter became the main sources of data. For more than a decade, the main US testing lab, Myriad Genetics, freely shared their BRCA pathogenic variant data via the BIC. Myriad Genetics ceased contributing data to the BIC in 2006, and without Myriad, the volume of data being deposited decreased greatly and the main depositors were academic labs and non-US-based clinical labs. Data volume changed again in 2013 ("Shifting Landscapes" section below). In the last four years, more than 50 clinical testing laboratories have embraced an open access model and deposited tens of thousands of variants to public databases.7.Landrum M.J. et al.ClinVar: public archive of interpretations of clinically relevant variants.1:CAS:528:DC%2BC2sXhtV2nsrzI10.1093/nar/gkv1222Nucleic Acids Res. 2016; 44: D862-D868Google Scholar The collaborative relationship between the BIC, testing laboratories, and researchers demonstrated the importance of capturing unpublished data directly from clinical labs; that is, it facilitates and expedites the classification of variants. For example, even in the absence of data on formal control samples, it quickly became clear that some missense variants, originally thought to be pathogenic, were actually benign population variants.8.Mazoyer S. et al.A polymorphic stop codon in BRCA2.1:STN:280:DyaK2s%2FltF2itA%3D%3D10.1038/ng1196-253Nat Genet. 1996; 14: 253-254Google Scholar,9.Wagner T.M. et al.Global sequence diversity of BRCA2: analysis of 71 breast cancer families and 95 control individuals of worldwide populations.1:CAS:528:DyaK1MXhslKnt7o%3D10.1093/hmg/8.3.413Hum Mol Genet. 1999; 8: 413-423Google Scholar This practice of data sharing, pioneered by the BIC, has expanded to other loci as well, as clinical genetic testing laboratories recognize the value of data sharing in moving the field forward. During its first decade, the BIC’s main user base were scientists who found value in having easy access to BRCA variant data. Importantly, scientists were comfortable classifying variants as clinically significant, benign, or unknown. The BIC operating principles were to share data and have the scientific community determine the functional significance of each allele. This approach worked well until large numbers of clinicians, diagnostic laboratory staff, and even patients themselves registered to use BIC data. Of particular interest were variants of unknown significance (VUS), i.e., variants whose functional consequences were unknown. Such a clinical test result can be difficult to explain to patients and many clinicians are inexperienced in understanding the inherent uncertainty in genetic testing. The BIC Steering Committee recognized the VUS problem created by declaring a variant “uncertain” and developed a more consistent classification process managed by the steering committee. Classifications of clinical significance were made following discussions that weighed all available data and relied on member expertise and experience. This process was successful but resource-limited; therefore, a more robust and scalable approach was required.10.Goldgar D.E. et al.Integrated evaluation of DNA sequence variants of unknown clinical significance: application to BRCA1 and BRCA2.1:CAS:528:DC%2BD2cXnvFaktLg%3D10.1086/424388Am J Hum Genet. 2004; 75: 535-544Google Scholar, 11.Easton D.F. et al.A systematic genetic assessment of 1,433 sequence variants of unknown clinical significance in the BRCA1 and BRCA2 breast cancer-predisposition genes.1:CAS:528:DC%2BD2sXht1KmsL%2FP10.1086/521032Am J Hum Genet. 2007; 81: 873-883Google Scholar, 12.Greenblatt M.S. et al.Locus-specific databases and recommendations to strengthen their contribution to the classification of variants in cancer susceptibility genes.1:CAS:528:DC%2BD1cXhsFSjsLnO10.1002/humu.20889Hum Mutat. 2008; 29: 1273-1281Google Scholar The Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA)13.Spurdle A.B. et al.ENIGMA—evidence-based network for the interpretation of germline mutant alleles: an international initiative to evaluate risk and clinical significance associated with sequence variation in BRCA1 and BRCA2 genes.1:CAS:528:DC%2BC3MXhs1aju7%2FI10.1002/humu.21628Hum Mutat. 2012; 33: 2-7Google Scholar (https://enigmaconsortium.org) grew out of the BIC Steering Committee in 2009 to promote large-scale collaborative studies and standardized approaches to assess the clinical significance of BRCA1 and BRCA2 variants and other breast cancer susceptibility genes. The defining feature of the ENIGMA approach is the integration of multiple types of data.14.Whiley P.J. et al.Multifactorial likelihood assessment of BRCA1 and BRCA2 missense variants confirms that BRCA1:c.122A>G(p.His41Arg) is a pathogenic mutation.10.1371/journal.pone.0086836PLoS One. 2014; 9: e86836Google Scholar ENIGMA developed a set of likelihood-based rules for BRCA variant classification. These rules derive quantitative and qualitative measures by comparing the behavior of known pathogenic and nonpathogenic alleles with regard to multiple phenotypes, e.g., segregation in families, tumor pathology, associated cancers, and phylogenetic analysis. Conceptually, these are similar to the classification criteria for mismatch repair genes developed for inherited colon cancer15.Thompson B.A. et al.A multifactorial likelihood model for MMR gene variant classification incorporating probabilities based on sequence bioinformatics and tumor characteristics: a report from the Colon Cancer Family Registry.1:CAS:528:DC%2BC3sXit1ek10.1002/humu.22213Hum Mutat. 2013; 34: 200-209Google Scholar and formalized by the International Society for Gastrointestinal Hereditary Tumors (InSIGHT)16.Thompson B.A. et al.Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database.1:CAS:528:DC%2BC3sXhvFymurzM10.1038/ng.2854Nat Genet. 2014; 46: 107-115Google Scholar (http://www.insight-database.org/classifications/). A uniform structured classification criteria should result in objective variant classification. In this way, the hereditary breast and ovarian cancer and hereditary colon cancer research communities have been able to move beyond “expert opinion” as the main mode of variant classification. Open and transparent classification methods also create a community of professionals who initiate interlaboratory discussions when discordant classifications are reported. National organizations, such as the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP) have developed their own guidelines to serve as a more generic framework for variant classification of Mendelian diseases. These recommendations are based on a structured review of different types of qualitative evidence with preassigned weights.17.Richards 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.10.1038/gim.2015.30Genet Med. 2015; 17: 405-424Google Scholar,18.Tavtigian S.V. et al.Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework.10.1038/gim.2017.210Genet Med. 2018; 20: 1054-1060Google Scholar In the late spring of 2013, one technological advance and one judicial ruling irreversibly changed the landscape of genetic testing for susceptibility to inherited cancer. Technical progress came in the form of massively parallel sequencing technologies, which led to multiplexed DNA sequence-based testing. Tests could now easily include 5 to 50 putative cancer susceptibility genes for a lower cost than single-gene tests. The second event occurred in June 2013 when the US Supreme Court unanimously invalidated Myriad Genetics’ patents on the BRCA genes. In the United States, immediately after this ruling, new clinical labs entered the BRCA1 and BRCA2 test market. In this competitive environment, the cost of a combined BRCA1 and BRCA2 test dropped from ~US$4000 to less than US$400. These changes in the testing landscape greatly increased the amount of BRCA sequence data being generated.19.Chen Z. et al.Trends in utilization and costs of BRCA testing among women aged 18-64 years in the United States, 2003-2014.10.1038/gim.2017.118Genet Med. 2018; 20: 428-434Google Scholar Multiple commercial laboratories began sharing BRCA1 and BRCA2 variants from all patients with the BIC. The BIC curation pipeline could not process this volume. In response, the BIC began processing these new data in conjunction with the National Center for Biotechnology Information (NCBI). This represented a break from the past, when locus-specific databases (LSDBs) were curated by small groups of collaborators. Using the BIC as a model, NCBI created a new aggregation of LSDBs, dubbed ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/). ClinVar now contains variant data for many clinically relevant genes, and includes all historical BIC data as well as newly sequenced variants for BRCA1 and BRCA2. Transferring the data acquisition, archiving, and display from the BIC to ClinVar has two advantages. ClinVar employs dedicated staff to process, curate, and display large data sets. In addition, as an integral part of the NCBI, ClinVar has a commitment to archive data permanently. For patients undergoing clinical BRCA testing, the VUS rate ranges from 2% to 15% depending on the testing laboratory and patients’ ethnic background.20.Eccles D.M. et al.BRCA1 and BRCA2 genetic testing-pitfalls and recommendations for managing variants of uncertain clinical significance.1:STN:280:DC%2BC28%2FhsVCrtw%3D%3D10.1093/annonc/mdv278Ann Oncol. 2015; 26: 2057-2065Google Scholar–22.Lincoln, SE et al. Consistency of BRCA1 and BRCA2 variant classifications among clinical diagnostic laboratories. JCO Precis Oncol. 2017;1, https://doi.org/10.1200/PO.16.00020. [Epub ahead of print.]Google Scholar While the proportion of VUS results has substantially decreased since the early 2000s (due to research and classification efforts), a significant number of individuals are informed that they carry a VUS. Widespread data sharing can help to decrease the rate of VUS test results because increased knowledge about both phenotypes and allele frequencies contribute to variant classification. ClinVar is now the largest source of directly deposited BRCA variant data. ClinVar staff do not evaluate the biological or clinical impact of variants. Instead, ClinVar compiles and shares variant classifications performed both by labs submitting variants and by “expert panels” that evaluate variants deposited by others using as many resources as possible. ENIGMA serves as an expert panel for the BRCA1 and BRCA2 genes in ClinVar. Even for well-curated genes such as BRCA1 and BRCA2, the interpretation of variants is one of the largest hurdles in dealing with the massive amounts of data generated through gene panels as well as exome and genome sequencing. Successful VUS classification relies heavily on open access, transparent data. Open access data also allows other groups to download and redistribute data with significant enhancements. An example of this is the newly created BRCA Exchange (http://brcaexchange.org), which is striving to facilitate collection of variants and associated clinical data from around the world and display this information using a clinician- and patient-accessible interface. Twenty years ago, genetic testing for BRCA was offered in a limited number of academic clinical centers, and only to those who had a high prior probability of carrying a clinically significant variant. Today, hundreds of thousands of genetic tests are ordered annually in a variety of settings. Exome and genome sequencing are used clinically, particularly for undiagnosed pediatric patients and rare Mendelian disorders. Exome sequencing and gene panel testing is being used to find somatic pathogenic variants in tumors. Genetic testing of BRCA to guide treatment options such as poly ADP ribose polymerase (PARP) inhibitors is currently recommended for ovarian cancer and metastatic breast cancer and may become the standard of care for other cancers.23.Buchtel K.M. et al.FDA approval of PARP inhibitors and the impact on genetic counseling and genetic testing practices.10.1007/s10897-017-0130-7J Genet Couns. 2018; 27: 131-139Google Scholar There have also been calls for population-based screening of BRCA,24.Levy-Lahad E. Lahad A. King M.C. Precision medicine meets public health: population screening for BRCA1 and BRCA2.10.1093/jnci/dju420J Natl Cancer Inst. 2015; 107: 420Google Scholar,25.Foulkes W.D. Knoppers B.M. Turnbull C. Population genetic testing for cancer susceptibility: founder mutations to genomes.1:CAS:528:DC%2BC2MXhslaksLvO10.1038/nrclinonc.2015.173Nat Rev Clin Oncol. 2016; 13: 41-54Google Scholar but testing of unselected individuals is controversial. 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