Gene Co-expression Network and Copy Number Variation Analyses Identify Transcription Factors Associated With Multiple Myeloma Progression - Yu, Christina Y.; Xiang, Shunian; Huang, Zhi; Johnson, Travis S.; Zhan, Xiaohui; Han, Zhi; Abu Zaid, Mohammad; Huang, Kun (Frontiers in Genetics, 2019)
Multiple myeloma (MM) has two clinical precursor stages of disease: monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). However, the mechanism of progression is not well understood. Because gene co-expression network analysis is a well-known method for discovering new gene functions and regulatory relationships, we utilized this framework to conduct differential co-expression analysis to identify interesting transcription factors in two publicly available datasets. We then used copy number variation data from a third public dataset to validate these transcription factors. First, we identified co-expressed gene modules in two publicly available datasets each containing three conditions: normal, MGUS, and SMM. These modules were assessed for condition-specific gene expression, and then enrichment analysis was conducted on condition-specific modules to identify their biological function and upstream transcription factors. Transcription factors were assessed for differential gene expression between normal and MM precursors, then validated with copy number variation analysis to identify candidate genes. Functional enrichment analysis reaffirmed known functional categories in MM pathology, the main one relating to immune function. Enrichment analysis revealed a handful of differentially expressed transcription factors between normal and either MGUS or SMM in gene expression and/or copy number variation (CNV). Overall, we identified four genes of interest (MAX, TCF4, ZNF148, and ZNF281) that aid in our understanding of MM initiation and progression.