Share:
Peer-Reviewed Publication
Blood Cancer Discov2024;5(6):428-441.November 1, 2024Journal Article

Multiple Myeloma Risk and Outcomes Are Associated with Pathogenic Germline Variants in DNA Repair Genes.

Santiago Thibaud1, Ryan L Subaran2, Scott Newman2, Alessandro Lagana3,4,5, David T Melnekoff3, Saoirse Bodnar1, Meghana Ram3, Zachry Soens2, William Genthe3, Tehilla Brander3, Tarek H Mouhieddine1, Oliver Van Oekelen3, Jane Houldsworth6, Hearn Jay Cho1, Shambavi Richard1, Joshua Richter1, Cesar Rodriguez1, Adriana Rossi1, Larysa Sanchez1, Ajai Chari1, Erin Moshier5,7, Sundar Jagannath1, Samir Parekh1, Kenan Onel8
1Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, New York.
2Sema4, Stamford, Connecticut.
3Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.
4Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.
5Icahn School of Medicine at Mount Sinai, Tisch Cancer Institute, New York, New York.
6Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.
7Department of Population Health Science and Policy, Tisch Cancer Institute, New York, New York.
8Clinical Genetics Service, Roswell Park Comprehensive Cancer Center, Buffalo, New York.

Abstract

First-degree relatives of patients with multiple myeloma are at increased risk for the disease, but the contribution of pathogenic germline variants (PGV) in hereditary cancer genes to multiple myeloma risk and outcomes is not well characterized. To address this, we analyzed germline exomes in two independent cohorts of 895 and 786 patients with multiple myeloma. PGVs were identified in 8.6% of th…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.