Pathogenic Germline Variants in Multiple Myeloma
Authors: 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 
Published: November 2021

Abstract
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 &lt; 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&lt;0.001), an association that remained significant in MVA (OR=4.1, p&lt;0.001). CHEK2 variants emerged as leading drivers of this correlation (OR 18.2, 95% CI 4.1-75, adjusted p&lt;0.01), & especially protein-truncating founder variant c.1100delC. Likelihood of being diagnosed w/ MM before age 40 was significantly higher in PGV carriers (6.3 vs 1.8%, OR=3.7, p=0.025). 25% of those younger than 40 y/o carried PGV, but none of these were in DDR-HR genes, a notable difference with other age groups (0 vs 41%, p=0.02). 2/6 MMR PGV were detected in pts diagnosed before age 40. In univariate survival analysis, DDR-PGV carriers had a significant PFS1 advantage over non-carriers (median 52 vs 35 months, p=0.008), as well as a non-significant OS advantage (p=0.08). PFS1 difference remained significant in MVA after adjusting for age, ISS stage, high-risk cytogenetics, treatment type & transplant status (OR 0.65, 95% CI 0.44-0.97, p=0.03) [Figure 1B].
CONCLUSIONS: PGV in HCG were common (8.8%) in this large cohort of NDMM pts of predominantly European ancestry, especially in those with a family history of hematologic malignancy (1:4, with high prevalence of CHEK2 variants & particularly protein-truncating founder variant c.1100delC), and in those diagnosed before age 40 (1:4). Routine screening in high-prevalence subgroups might be warranted, as carriers may benefit from counseling and enrollment in early cancer detection programs. We observed a clinically and statistically significant PFS1 advantage in carriers of PGV in DDR genes, possibly due to increased sensitivity to MM therapies, a well-described phenomenon in other cancer types (PMID 33158305). Prospective validation of these findings is needed to better understand prognostic & therapeutic implications of PGV in MM.
Figure 1 Figure 1.

Disclosures
Chari: Karyopharm: Consultancy; Takeda Pharmaceutical Company: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy, Research Funding; Sanofi Genzyme: Consultancy; Oncopeptides: Consultancy; Antegene: Consultancy; Glaxosmithkline: Consultancy; Secura Bio: Consultancy. Richard: Karyopharm, Janssen: Honoraria. Richter: Sanofi: Consultancy; Antengene: Consultancy; Karyopharm: Consultancy; BMS: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Adaptive Biotechnologies: Speakers Bureau; Celgene: Speakers Bureau; Janssen: Speakers Bureau; X4 Pharmaceuticals: Consultancy; Oncopeptides: Consultancy; Adaptive Biotechnologies: Consultancy; Secura Bio: Consultancy; Astra Zeneca: Consultancy. Parekh: Foundation Medicine Inc: Consultancy; Amgen: Research Funding; PFIZER: Research Funding; CELGENE: Research Funding; Karyopharm Inv: Research Funding.