Nussbaum, RL

Purpose: Neuroendocrine neoplasms (NENs) are increasingly recognized to have a hereditary predilection, yet the prevalence and clinical relevance of pathogenic germline variants (PGVs) in unselected patients with NEN remain poorly defined. This prospective, multicenter study aimed to evaluate the prevalence and clinical utility of PGVs through universal multigene panel testing in a diverse cohort of patients with NENs. Patients and Methods: Between 2018 and 2024, we enrolled unselected patients with NENs from 3 Mayo Clinic Cancer Centers. Germline genetic testing was performed using a next-generation sequencing panel of up to 84 cancer predisposition genes. Patients were not selected based on age, disease stage, ethnicity, or family history. Variants were classified as PGVs, variants of uncertain significance (VUS), or negative. Clinical and demographic data were analyzed descriptively. Results: Among 88 patients, PGVs were identified in 15.9% (n=14), most frequently in high- or moderate-penetrance genes including MEN1 , CHEK2 , MITF , and MUTYH . PGVs were most commonly found in pancreatic NENs [n=12/55 (21.8%)], followed by small bowel NENs [n=2/20 (10%)], with no PGVs detected in lung NENs. Mismatch repair (MMR) gene alterations were identified in 5.7% of patients, including 1 MLH1 PGV and 4 MSH2/MSH6 VUS, 2 of which demonstrated MMR deficiency by protein testing. VUS were reported in 34.1% of patients. Notably, 35.7% of PGV-positive patients did not meet current NCCN or ACMG testing criteria, and 53.9% had PGVs in genes outside of cancer-specific guideline recommendations. Conclusions: Universal germline testing in unselected patients with NEN identified clinically relevant PGVs in over 15% of cases. These findings support broader genetic testing approaches to guide treatment, enhance familial risk assessment, and inform cascade testing—regardless of traditional clinical selection criteria.

Abstract 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 patient's 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.