Pre-clinical Strategies to Overcome Drug-Resistant Multiple Myeloma: Predictive Transcriptomics and Targeting the Myeloma Epigenome

Abstract

Multiple myeloma remains an incurable hematological malignancy due to the failure of standard-of-care therapies to broadly target a genetically heterogeneous disease and an inability overcome inevitable drug-resistant relapse. This dissertation will address this outstanding problem through two approaches: transcriptomic profiling to predict resistance to proteasome inhibitors and pre-clinical evaluation of epigenetic-targeting therapies to broadly target the myeloma epigenome. First, our goal was to develop a gene expression signature that predicts response specific to proteasome inhibitor (PI) treatment in MM. Using a well-characterized panel of human myeloma cell lines (HMCLs) representing the biological and genetic heterogeneity of MM, we created an in vitro chemosensitivity profile in response to treatment with the four PIs as single-agents. Through gene expression profiling and machine learning-based computational approaches we identified a 42-gene expression signature that could not only distinguish good and poor PI-response in the HMCL panel, but could also be successfully applied to four different clinical datasets on MM patients undergoing PI-based chemotherapy to distinguish between extraordinary (good and poor) outcomes. Our results demonstrate the use of in vitro modeling and machine learning-based approaches to establish predictive biomarkers of response and resistance to drugs that may serve to better direct myeloma patient treatment options. Epigenetic abnormalities are abundantly present in multiple myeloma and accumulating evidence suggests that the histone methyltransferase EZH2 is aberrantly active in MM. We tested the efficacy of EZH2 specific inhibitors in a large panel of human MM cell lines (HMCLs) and found that only a subset of HMCLs demonstrate single agent sensitivity despite ubiquitous global H3K27 demethylation. Pre-treatment with EZH2 inhibitors greatly enhanced the sensitivity of HMCLs to the pan-HDAC inhibitor panobinostat in nearly all cases regardless of single agent EZH2 inhibitor sensitivity. Transcriptomic profiling revealed large-scale transcriptomic alteration by EZH2 inhibition highly enriched for cancer-related pathways. Further analysis demonstrated that combination treatment further perturbed oncogenic pathways and signaling nodes consistent with an antiproliferative/pro-apoptotic state. We conclude that combined inhibition of HDAC and EZH2 inhibitors is a promising therapeutic strategy to broadly target the epigenetic landscape of aggressive MM.