An Interlaboratory Study Of Complex Mutation Detection In Genes Associated With Hereditary Breast And Ovarian Cancer Highlights Both Successes And Current Challenges

Background: Established laboratory methods, including next-generation sequencing (NGS), can accurately and inexpensively detect certain classes of clinically important mutations in readily accessible protein coding regions of a patient9s DNA. These events include single nucleotide variants (SNVs), small insertions/deletions (indels), and sometimes medium sized copy-number deletions or duplications (del/dups). However, other mutation types with clinical relevance are known, and indeed data on over 80,000 patients show that pathogenic, medically important variants of other, more technically challenging types are prevalent in genes related to hereditary breast and ovarian cancer (see associated abstract by Lincoln et al.). We sought to develop and evaluate a reference standard by which laboratories may be able to assess and improve their performance on representative examples of complex, technically “hard” mutations in medically important genes associated with breast, ovarian, and other cancers. Methods: We selected a diverse set of 23 challenging alterations, uncovered by the aforementioned clinical study, all of which are considered pathogenic and potentially actionable under ACMG and NCCN guidelines when uncovered in the germline DNA of a patient. These mutations are in the BRCA1, BRCA2, MLH1, MSH2, MSH6, and PMS2 genes. We generated a single synthetic DNA specimen with all 23 mutations introduced into a known genomic background. Following presentation of this general strategy at a 2016 meeting, 7 laboratories volunteered to collaboratively evaluate this approach. This DNA was created, validated, blinded and provided to these laboratories who sequenced it using a total of 9 different NGS based workflows, including 5 validated clinical tests with customized methods and two sequencing technology vendor (Illumina, Ion Torrent) default pipelines. Multiple target capture biochemical methods were used, as was whole genome sequencing. Results: Twelve of the 23 variants were detected by all 9 laboratory workflows, but just 2 workflows detected all 23. Many, but not all, of these test limitations were previously known. Importantly, evidence of each variant was present in the raw data, suggesting that this strategy is compatible with the diverse biochemical methods used in NGS laboratories today. Raw data for the synthetic variants mimicked that of the endogenous ones (including presenting similar technical artifacts which make these variants “hard”) demonstrating that controls such as these may be useful in the development of methods with improved sensitivity. The vendor-supplied bioinformatics pipelines fared the worst, reinforcing the importance of carefully selecting bioinformatics algorithms and parameters in any laboratory developed test. Discussion: Medically important but technically challenging mutations are prevalent in genes involved in hereditary breast, ovarian, and other cancers. Although patient specimens are also critical, synthetic controls may help efficiently assess the analytic range of any clinical test, highlighting certain strengths and limitations, and can help laboratories develop new methods to improve sensitivity for these challenging variants. Citation Format: Lincoln S, Zook J, Truty R, Chowdhury S, Fellowes A, Mahamdallie S, Ferber M, Cleveland M, Huang C, Tomson F, Klee E, DeSilva W, Seal S, Aradhya S, Nussbaum R, Garlick R, Kingsmore S, Rahman N, Salit M, Shirts B. An interlaboratory study of complex mutation detection in genes associated with hereditary breast and ovarian cancer highlights both successes and current challenges [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-06-08.