Network Modeling Reveals CDC42BPA and CLEC11A As Novel Driver Genes of t(4; 14) Multiple Myeloma

Multiple Myeloma (MM) is a genetically complex malignancy arising from bone marrow plasma cells with 30,000 new cases reported every year in the US. It is characterized by heterogeneity in clinical presentation and response to treatment. Next generation sequencing (NGS) technologies have enabled a deeper insight into cancer genomes and transcriptomes at an unprecedented level of detail. MMRF CoMMpass is a longitudinal, prospective observational study that aims to collect and analyze sequencing and clinical data from >1,000 MM patients at initial diagnosis and at relapse. Such effort providesa unique opportunity to improve our knowledge of MM pathogenesis and identify novel mechanisms that drive disease progression as well as genomic aberrations that underlie them.

We have developed MMnet, an integrative network model of MM based on 450 RNA-Seq samples from the IA7 release of CoMMpass. By using Weighted Gene Co-expression Network Analysis (WGCNA), we defined 37 modules of co-expressed genes, that were further characterized by functional enrichment analysis and correlation with genetic alterations inferred from Whole-Exome (WXS) and Whole-Genome data (WGS) and with clinical traits. For each module, we calculated intra-module connectivity to identify highly connected "hub" genes that represent likely control points for biological processes. The results of our analysis revealed several module hub genes that were not previously associated to MM. Specifically, CDC42BPA and CLEC11A were hub genes of a module strongly up-regulated in patients carrying t(4;14) translocation involving MMSET and FGFR3, and associated to rISS stage III and FGFR3 mutations. The t(4;14) translocation observed in ~15% of newly diagnosed MM patients is associated with very poor prognosis. This translocation was observed in 48/450 patients in the CoMMpass cohort (≈10%). MMSET and FGFR3 are considered oncogenic drivers in t(4;14) myeloma and are currently being investigated as therapeutic targets. Given the prognostic and therapeutic importance of these genes and the unknown role of hub genes in MM pathogenesis, we sought to determine the biological significance of CDC42BPA and CLEC11A and whether they played a regulatory role in t(4;14) myeloma.

CDC42BPA encodes serine/threonine protein kinase MRCK, which is a downstream effector of CDC42, a protein involved in cell cycle regulation. CLEC11A is a member of the C-type lectin superfamily, which includes several genes responsible for modulation of specific immune response to pathogens in dendritic cells and is involved in cell adhesion and cell communication. We selected two MM cell lines expressing MMSET and whose profile was concordant with module activation: KMS-11 and KMS-26. KMS-11 also carried t(4;14) and an activating mutation in FGFR3 (Y373C). We depleted CDC42BPA and CLEC11A by transient transfection of siRNA and assayed protein levels as well as cell viability. In both cell lines, western blot confirmed depletion of siRNA target proteins and revealed decreased expression of MMSET and its interactor NFkB as compared to scrambled controls. Cell viability (CellTitre Blue) assay showed a decrease in the number of viable cells by 60% at 72h following depletion of CLEC11A and by 55% at 72h following depletion of CDC42BPA as compared to control cells. As knockdown of MMSET was previously reported to induce apoptosis in MM cells, we next asked whether knockdown of CDC42BPA and CLEC11A had a similar impact. There was a significant increase of about 30-60% in the fraction of Annexin V-positive cells in siRNA-transfected cells compared with controls, consistent with the induction of apoptosis as examined by AnnexinV/PI staining. These results confirmed the central role of CDC42BPA and CLEC11A as potential regulators of MMSET in MM cell survival and regulation. These genes are therefore novel drug targets for treating t(4;14) myeloma. Future investigations will aim at determining the biological mechanisms by which CDC42BPA and CLEC11A regulate MMSET.

In summary, our network analysis of the CoMMpass dataset uncovered novel and complex patterns of genomic perturbation, specifically novel key driver genes of myeloma network modules with further implications for identification and targeting of hub genes in gene co-expression networks.