Genetic testing for cancer susceptibility became common in the mid-1990s with the availability of BRCA1/BRCA2 sequence-based testing, followed by Lynch syndrome and other more rare disorders. In the intervening 20 years, there has been an enormous growth in our knowledge of sequence variation in both disease and normal populations, compounded with several increasingly complex variant classification schemes (1,2). In this issue of the Journal, Slavin et al. report on their 20-year experience receiving hereditary cancer variant reclassification results from two large clinical cancer genetics programs with diverse patient populations in California (3). BRCA1/BRCA2 testing accounted for 46.7% of variants, with 87.6% of these from one large diagnostic testing lab, which were analyzed separately from all other variants tested among 33 different laboratories. These latter results were disproportionately from the last few years, with the widespread availability of panel testing. There were only 0.3% discordant variant reports across laboratories, although the study wasn’t designed to address this issue, particularly with the limited number of laboratories reporting early in this period. The article describes reclassification of variants, other than those starting as benign, to another category classification. This includes all nonbenign variants (pathogenic, likely pathogenic, variant of uncertain significance [VUS], and likely benign) for a total of 1816 nonbenign unrelated variant reports encompassing 1483 unique variants. Somewhat surprisingly, the overall rate of nonbenign variant reclassification was 18.1% (n = 268). Further highlighting the problem reclassification represents to clinicians and patients, there were 40 variants reclassified more than once, and some reclassification reports were received after the death of the proband. However, 18.1% does not reflect the proportion of patients with reclassification, as stable variants may be reported multiple times, and conversely, VUS often represent rare alleles. Somewhat surprisingly, the rates of reclassification of likely benign, VUS, and likely pathogenic variants were similar. However, the direction of reclassification was very asymmetric, in particular, only 26 of 268 reclassified (9.7%) or 26 of 1483 (1.8%) nonbenign variants were upgraded toward pathogenic; the remainder were reclassified toward benign. In addition, only 17 of the 209 VUS (8%) became either pathogenic or likely pathogenic. Another recent study (over a shorter time period) found that VUS were the variants predominantly reclassified, but again almost all variant reclassification was toward benign (4)—supporting counseling patients that VUS are more likely to remain uncertain or be benign. Conversely, Slavin et al. (3) report that only three pathogenic variants were reclassified toward benign. This may not be representative of all test situations as a substantial proportion of the data is derived from one laboratory testing only two genes in a large number of at-risk adults, in contrast to other testing situations with smaller numbers of individuals being tested for larger numbers of genes associated with rare disorders. Certainly, in our clinical experience, patients with pathogenic variants for rare syndromes who were first tested more than 10 years ago have been downgraded. Similarly, reclassification from pathogenic/likely pathogenic to more benign findings have been reported in African American patients undergoing testing for cardiomyopathy (5). Because testing laboratories vary in their reclassification policies, clinicians should consider a brief reassessment of patients’ pathogenic/likely pathogenic results (particularly missense or potential splice variants) reported prior to the availability of good population data. Public databases like ClinVar (6) often have current assertions submitted by clinical labs for older variants, or the original testing laboratory can be contacted for any change in assessment. The key focus of the analyses performed by Slavin et al. (3) was how patients’ race and/or ethnicity (referred to as ancestry) impacted the likelihood of reclassification. Prior studies on BRCA1/BRCA2 testing demonstrated that non-European patients had a higher likelihood of a VUS result (7), a fact often incorporated into pretest counseling. This is consistent with other disorders, for example, higher rates of VUS results in cardiomyopathy genes in underrepresented minorities (8). However, there has been little prior work on the likelihood of reclassification as a function of the patient’s ancestry. The overall rate of reclassification was higher for multiple different ancestries (except non-Chinese Asian and Hispanic) compared with non-Hispanic Europeans, although with some variation in relative rates depending on the time period and gene sequenced (3). The broad peak of increased reclassification by laboratories coincides with public access to large population databases (1000Genomes, ESP, ExAC). Further enrichment of population data sets, for example, increasing genomic data from different ancestries in ExAC/gnomAD (9) and ClinVar variants being genotyped as part of the multiethnic PAGE data set (10), facilitates clinical laboratory recognition of variants common in specific ancestries and therefore unlikely to convey high cancer risk. In addition, there is increasing public access to expert variant classification through disease-specific consortia (11,12) and the Clinical Genome Resource efforts (13). Despite the frequency of clinically relevant variant reclassification, recent professional guidelines (2,14) do not obligate laboratories to update past reports given lack of reimbursement for this activity. There is little consistency to the reclassification policies developed by individual laboratories (15). Solving this problem in a cost-effective manner that supports patient care yet does not burden laboratories with unpaid activities will undoubtedly require information technology–enabled approaches including systems that deliver updates to their customers (16); however, patients change providers and physicians do not want the liability of updates they cannot deliver. Therefore, centralized systems of knowledge sharing linked to structured genetic test reports in the electronic health record may prove useful. For example, ClinVar variant reclassification data could be managed by a health care system that generates notifications to a patient’s current physician or to the patients themselves that they should contact a health care provider. In the interim, patients with “likely” or uncertain genetic results should consider requesting updated information from their practitioners at subsequent encounters. In summary, it is clear that variant reclassification is not a rare event. Advances are needed in delivering updated genetic information to patients, and those in most need, such as minority populations with the highest reclassification rates, may be most disadvantaged if solutions are not developed soon. Funding SP and HR receive National Institutes of Health grant funding (eg, ClinGen grant numbers U41HG009649 and U41HG006834, respectively), which includes working with laboratories to classify and update the classification of variants in addition to the development of expert panels for variant classification. Notes Affiliations of authors: Departments of Pediatrics and Molecular and Human Genetics, Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, TX (SEP); Texas Children’s Cancer Center, Texas Children’s Hospital, Houston, TX (SEP); Center for Genomic Medicine and Departments of Medicine and Pathology, Massachusetts General Hospital, Boston, MA (HLR); The Broad Institute of MIT and Harvard, Cambridge, MA (HLR). The funder had no role in the writing of this editorial or the decision to submit it for publication. HR receives salary support from clinical laboratories (Partners Healthcare Laboratory for Molecular Medicine and the Broad Institute) that offer clinical sequencing and variant interpretation services. SP is a member of the scientific advisory board of Baylor Genetics. References 1 Plon SE, Eccles DM, Easton Det al. , Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum Mutat. 2008; 29( 11): 1282– 1291. Google Scholar CrossRef Search ADS PubMed 2 Richards S, Aziz N, Bale Set 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. 2015; 17( 5): 405– 424. Google Scholar CrossRef Search ADS PubMed 3 Slavin TP, Van Tongeren LR, Behrendt CEet al. , Prospective study of cancer genetic variants: Variation in rate of reclassification by ancestry. J Natl Cancer Inst. 2018; 110( 10): djy027. 4 Macklin S, Durand N, Atwal Pet al. , Observed frequency and challenges of variant reclassification in a hereditary cancer clinic. Genet Med. In press. 5 Manrai AK, Funke BH, Rehm HLet al. , Genetic misdiagnoses and the potential for health disparities. N Engl J Med. 2016; 375( 7): 655– 665. Google Scholar CrossRef Search ADS PubMed 6 Landrum MJ, Lee JM, Benson Met al. , ClinVar: Improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 2018; 46( D1): D1062– D1067. Google Scholar CrossRef Search ADS PubMed 7 Kurian AW. BRCA1 and BRCA2 mutations across race and ethnicity: Distribution and clinical implications. Curr Opin Obstet Gynecol. 2010; 22( 1): 72– 78. Google Scholar CrossRef Search ADS PubMed 8 Landry LG, Rehm HL. Association of racial/ethnic categories with the ability of genetic tests to detect a cause of cardiomyopathy. JAMA Cardiol. Feb 28. [Epub ahead of print]. 9 Lek M, Karczewski KJ, Minikel EVet al. , Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016; 536( 7616): 285– 291. Google Scholar CrossRef Search ADS PubMed 10 Bien SA, Wojcik GL, Zubair Net al. , Strategies for enriching variant coverage in candidate disease loci on a multiethnic genotyping array. PLoS One. 2016; 11( 12): e0167758. Google Scholar CrossRef Search ADS PubMed 11 Spurdle AB, Healey S, Devereau Aet 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. Hum Mutat. 2012; 33( 1): 2– 7. Google Scholar CrossRef Search ADS PubMed 12 Thompson BA, Spurdle AB, Plazzer JPet al. , Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database. Nat Genet. 2014; 46( 2): 107– 115. Google Scholar CrossRef Search ADS PubMed 13 Rehm HL, Berg JS, Brooks LDet al. , ClinGen—the Clinical Genome Resource. N Engl J Med. 2015; 372( 23): 2235– 2242. Google Scholar CrossRef Search ADS PubMed 14 Rehm HL, Bale SJ, Bayrak-Toydemir Pet al. , ACMG clinical laboratory standards for next-generation sequencing. Genet Med. 2013; 15( 9): 733– 747. Google Scholar CrossRef Search ADS PubMed 15 O'Daniel JM, McLaughlin HM, Amendola LMet al. , A survey of current practices for genomic sequencing test interpretation and reporting processes in US laboratories. Genet Med. 2017; 19( 5): 575– 582. Google Scholar CrossRef Search ADS PubMed 16 Aronson SJ, Clark EH, Varugheese Met al. , Communicating new knowledge on previously reported genetic variants. Genet Med. 2012; 14: 713– 719. Google Scholar CrossRef Search ADS © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: firstname.lastname@example.org This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)
JNCI: Journal of the National Cancer Institute – Oxford University Press
Published: May 10, 2018
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