Multivariant Transcriptome Analysis Identifies Modules and Hub Genes Associated with Poor Outcomes in Newly Diagnosed Multiple Myeloma Patients

SIMPLE SUMMARY: Multiple myeloma (MM) is a cancer of plasma cells with a five-year survival rate of 53%. MM is a heterogeneous disease with diverse clinical courses, consistent with the variable efficacy of therapeutic strategies and the development of chemoresistance. We used bioinformatic tools to better understand the molecular mechanisms that underlie failures in the standard treatment of MM with RVD (revlimid, velcade, and dexamethasone). Using an RNA-seq dataset from the MMRF CoMMpass study downloaded from the GDC portal, we identified modules positively correlated to MM vital status. Hub genes from these modules were further grouped based on their biological function and evaluated for association to patient survival. ABSTRACT: The molecular mechanisms underlying chemoresistance in some newly diagnosed multiple myeloma (MM) patients receiving standard therapies (lenalidomide, bortezomib, and dexamethasone) are poorly understood. Identifying clinically relevant gene networks associated with death due to MM may uncover novel mechanisms, drug targets, and prognostic biomarkers to improve the treatment of the disease. This study used data from the MMRF CoMMpass RNA-seq dataset (N = 270) for weighted gene co-expression network analysis (WGCNA), which identified 21 modules of co-expressed genes. Genes differentially expressed in patients with poor outcomes were assessed using two independent sample t-tests (dead and alive MM patients). The clinical performance of biomarker candidates was evaluated using overall survival via a log-rank Kaplan–Meier and ROC test. Four distinct modules (M10, M13, M15, and M20) were significantly correlated with MM vital status and differentially expressed between the dead (poor outcomes) and the alive MM patients within two years. The biological functions of modules positively correlated with death (M10, M13, and M20) were G-protein coupled receptor protein, cell–cell adhesion, cell cycle regulation genes, and cellular membrane fusion genes. In contrast, a negatively correlated module to MM mortality (M15) was the regulation of B-cell activation and lymphocyte differentiation. MM biomarkers CTAG2, MAGEA6, CCND2, NEK2, and E2F2 were co-expressed in positively correlated modules to MM vital status, which was associated with MM’s lower overall survival.