Stage-Specific Co-expression Network Analysis for Cancer Biomarker Discovery

Abstract

Identification of conserved gene network modules in different stages of cancer may lead to uncovering mechanisms behind cancer initiation and progression. This work is based on two hypotheses. Hypothesis-l: the network modules conserved in all cancer stages are potential biomarkers related to the trajectory of cancer development or progression of cancer from initiation to stage-to-stage to metastasis. Hypothesis-2: The network modules from a stage, which are not conserved in other stages, can be considered as the stage-specific biomarkers for diagnosis.To test the hypotheses, gene expression and clinical data of Breast Invasive Carcinoma (BRCA) from The Cancer Genome Atlas (TCGA) were used for analysis. Gene expression data was divided into five groups- stage I to stage IV and normal tissue samples. First, the co-expression networks for each of the four stages and normal samples were generated. Second, the modules from each of the stage-specific networks were discovered using weighted gene co-expression network analysis (WGCNA). Third, survival analysis was performed to identify the prognostically significant modules. Fourth, module preservation analysis was performed to determine whether a module from one stage is preserved in other cancer stages as well as in normal stage. Finally, gene ontology and pathway enrichment analyses were performed for the prognostically significant and conserved modules.The present study discovered several gene-network modules for breast cancer preserved in all cancer stages and are significant in overall survival; hence, they can be considered potential biomarkers for cancers, related to the trajectory of cancer development. The modules that were found not to be conserved in different stages can be considered as stage-specific biomarkers.