Selective Metabolic Vulnerabilities in Multiple Myeloma

Multiple myeloma (MM) is a hematological cancer characterized by a heterogeneous clinical presentation and an abnormal accumulation of clonal plasma cells in the bone marrow. MM is the second most common cancer worldwide and accounts more than 30,000 new diagnoses cases in 2016 just in United States. Immunomodulatory drugs and proteasome inhibitors are the main existing treatments against MM, which significantly improves the life expectancy of patients; however, MM remains an incurable disease.

In order to identify novel therapeutic strategies in MM, we systematically search for selective metabolic vulnerabilities using the concept of genetic Minimal Cut Sets (gMCSs), recently introduced in Apaolaza et al. 2017. To that end, we first enumerated 20,000 gMCSs from Recon3D (Brunk et al. 2018), the most recent reconstruction of the human metabolism. Secondly, RNA-seq data from the CoMMpass (Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile) project, the largest study performed to date by the Multiple Myeloma Research Foundation (MMRF), was mapped onto the gMCSs to discover metabolic targets in MM. Third, in order to identify selective target for MM cells, we also analyzed an unpublished RNA-seq study that includes healthy samples for different cell types arising from the B-cell differentiation: bone marrow plasma cells, tonsil plasma cells, memory B cells, centrocytes, centroblasts, naïve B cells. Fourth, the same analysis was repeated in different MM cell lines in order to identify suitable candidates for in-vitro experimental validation. Main results and future directions are presented and discussed.

[1] Apaolaza, Iñigo, et al. "An in-silico approach to predict and exploit synthetic lethality in cancer metabolism." Nature communications 8.1 (2017): 459.

[2] Brunk, Elizabeth, et al. "Recon3D enables a three-dimensional view of gene variation in human metabolism." Nature biotechnology 36.3 (2018): 272.