Pathogenic Germline Variants in Multiple Myeloma

BACKGROUND: There is growing evidence supporting inherited predisposition to multiple myeloma (MM). Epidemiologic studies have shown that 1st-degree relatives of MM patients (pts) have a 2-4 fold increase in risk of developing MGUS or MM. Genome-wide association studies (GWAS) have identified common...

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Veröffentlicht in:Blood 2021-11, Vol.138 (Supplement 1), p.399-399
Hauptverfasser: Thibaud, Santiago, Etra, Aaron, Subaran, Ryan, Soens, Zachry, Newman, Scott, Chen, Rong, Chari, Ajai, Cho, Hearn Jay, Jagannath, Sundar, Madduri, Deepu, Melnekoff, David T., Richard, Shambavi, Richter, Joshua, Sanchez, Larysa, Huang, Kuan-lin, Lagana, Alessandro, Parekh, Samir, Onel, Kenan
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Sprache:eng
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Zusammenfassung:BACKGROUND: There is growing evidence supporting inherited predisposition to multiple myeloma (MM). Epidemiologic studies have shown that 1st-degree relatives of MM patients (pts) have a 2-4 fold increase in risk of developing MGUS or MM. Genome-wide association studies (GWAS) have identified common SNPs as well as rare high-penetrance variants that collectively explain ~16% of the estimated heritability of multiple myeloma (PMID 30213928). Pathogenic/likely-pathogenic germline variants (PGV) in hereditary cancer genes (HCG) are common in adult cancer patients (~8%, PMID 29625052), but prevalence in MM is not known. The aim of our study is to investigate the occurrence of PGV in newly-diagnosed MM (NDMM), and to describe clinical characteristics & outcomes of carriers. METHODS: We analyzed MMRF CoMMpass data (version IA16) and identified 895 NDMM pts for whom whole-exome sequencing of germline DNA was available. We used the clinical annotation pipeline from Sema4, a CLIA/CAP certified genetic testing laboratory, to identify pts with PGV according to ACMG variant classification guidelines. We compared clinical characteristics & disease phenotypes of PGV carriers vs non-carriers. We used Chi-Square and Fisher's Exact tests to assess statistical significance, which we defined as a two-sided p value < 0.05. Logistic regression models were used for multivariate analyses. Kaplan-Meier method and Cox proportional-hazards models were used for uni- and multivariate survival analysis, respectively. Bonferroni method was used to account for multiple testing. RESULTS: We identified 83 PGV in 31 distinct HCG in 79 (8.8%) of 895 NDMM pts (83% European ancestry) [Figure 1A]. Most PGV involved DNA damage repair (DDR) genes (78%), and homologous recombination (HR) genes were the most commonly mutated (34%). PGV in CHEK2 were the most common (n=10, 1.1% of all MM pts). 2 pts carried PGV in TP53 and reported extensive family history of Li-Fraumeni-associated cancers (breast, sarcoma, gastric & melanoma). 6 pts had germline mismatch repair (MMR) gene defects (1:149, considerably higher than the estimated prevalence of Lynch syndrome in Western populations). 4 pts carried PGV in BRCA2 (previously identified in a family study as a potential MM predisposition gene, PMID 11904319). MM pts with a family history of hematologic malignancy (leukemia, lymphoma or MM) in a 1st or 2nd-degree relative were significantly more likely to carry PGV (22 vs 7.6%, OR=3.3, p
ISSN:0006-4971
1528-0020
DOI:10.1182/blood-2021-151495