Characterizing the effects of cis-regulatory variation on patient outcomes and treatment response in Multiple Myeloma

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ABSTRACT Multiple Myeloma (MM) is a malignancy of plasma cells and the second most common hematological cancer accounting for 2% of cancer deaths. MM is associated with a poor prognosis, and while new therapies have improved survival rates, most patients still experience relapses. MM shows a strong hereditary genetic component as relatives of MM patients have a two- to four-fold higher risk of disease development. Moreover, MM displays a disparity in occurrence and mortality among sexes with males having a higher risk than females. Many risk loci associated with MM susceptibility identified by genome-wide association studies (GWAS) and meta-analysis are located within or adjacent to the regulatory regions, indicating a role in transcriptional regulation. However, how these risk loci contribute to tumor etiology, progression and outcome are poorly understood. To accelerate the discovery of novel treatments for MM patients, the Multiple Myeloma Research Foundation’s (MMRF) developed the longitudinal CoMMpass study. This work, led by Dr. Jonathan Keats at TGen, has identified novel MM subtypes using somatic mutation and transcription profile. Nevertheless, the genetic architecture underlying gene regulation contributing to patient outcomes has not been examined. Using the CoMMpass data, we identified 7,737 variants associated with changes in gene expression (expression quantitative trait locus; eQTL); among these 1,764 are male-specific and 847 are female-specific eQTLs. Furthermore, 1,034 of the identified eQTLs are associated with survival in the CoMMpass cohort. However, functional validation is necessary to confirm the regulatory effects and better assess the functional consequences of this variation. To this end, I propose using a multiplex high throughput CRISPR activator/interference (CRISPRa/i) screen followed by single-cell RNA sequencing to validate the role of putative cis-regulatory loci on gene expression levels. To determine how these loci modulate tumor etiology, I will perform assays investigating the effects of these perturbations on tumor fitness and response to treatment. The proposed study will provide valuable insights into the regulatory landscape underlying MM occurrence, progression, and response to treatment, and potential candidates for developing more targeted treatments for MM patients. Furthermore, the training I will receive in this study on cancer genetics and cancer genomics will open up new opportunities for my future research directions as an independent investigator.