Abstract

Abstract Multiple myeloma (MM) is a malignancy of plasma cells in the bone marrow and the second most common hematological malignancy. MM is characterized by a high degree of heterogeneity and has a hereditary genetic component with relatives of MM patients having a higher risk of disease development. Additionally, MM displays a disparity in occurrence and mortality among sexes with males having a higher risk than females. Although new therapies have significantly improved survival rates, MM remains incurable as most patients experience relapses. Therefore, understanding the genetic control underlying complex outcomes is important for the development of better treatments for MM patients. While the majority of research has been focusing on protein-coding regions of the genome, recent studies have started to illuminate the role of non-coding variations on MM. For example, many of the 176 GWAS risk loci associated with MM susceptibility are located within or adjacent to regulatory regions, indicating a role in transcriptional regulation. However, how the non-coding genetic variations affect gene expression, tumor etiology and outcome is poorly understood. To better understand the genetic and biological underpinnings of MM, we utilize genomic approaches to examine non-coding germline and somatic effects on gene expression and cancer outcome. First, we analyzed whole-genome sequencing (WGS) from peripheral blood and WGS and RNA-seq from baseline tumor specimens of 607 participants from the CoMMpass longitudinal study of the Multiple Myeloma Research Foundation. Using both joint and sex-stratified analyses, we detected 6,504 unique germline variants associated with changes in gene expression, i.e. expression quantitative trait loci (eQTLs), corresponding to 4,598 unique eGenes. Among the identified eQTLs, 33.76% exhibit sex-specific effects and 654 variants are associated with genes that influence survival in the CoMMpass cohort. In addition to the germline eQTLs, we identified 266 somatic eQTLs, corresponding to 208 eGenes. Among the identified eQTLs, 566 germline and 88 somatic eQTLs overlap with an ATACseq peak in MM cell lines. Second, we selected a set of eQTLs to validate their functions in transcriptional activity in MM cell lines (2 females, 2 males) using CRISPR interference screens (CRISPRi) with a scRNA-seq readout. By analyzing global transcriptional changes, we identify potential downstream targets that may play essential roles in MM genesis and progression. In conclusion, using computational and functional genomics approaches, we have identified germline and somatic eQTLs that are associated with gene expression and survival in MM, thus providing insights into how these non-coding variations contribute to tumor etiology and outcome. Citation Format: Linh T. Bui, Heini M. Natri, Lance M. Peter, Bianca Argente, Austin J. Gutierrez, Arnold Federico, Mei-I Chung, Jonathan Keats, Nicholas E. Banovich. Functions of genetic variation on gene expression and survival in multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5780.

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