Network cluster analysis of protein-protein interaction network identified biomarker for early onset colorectal cancer.

Colorectal cancer (CRC) is a major cause of morbidity and mortality throughout the world. However, the genetic alterations and molecular mechanism of the early onset CRCs are not fully investigated. The present study aimed to characterize early onset CRC by analyzing its gene expression compared with normal controls and to identify network-based biomarkers of early onset CRC. The gene expression profiles of early onset CRC were downloaded from Gene Expression Omnibus and the differentially expressed genes (DEGs) in CRC patients were identified. Then, a protein-protein interaction (PPI) network was constructed and the clusters in PPI were analyzed by ClusterONE. Furthermore, the gene ontology functional analysis and pathway enrichment analysis were conducted to the modules in PPI network. A systems biology approach integrating microarray data and PPI was further applied to construct a PPI network in CRC. Total 631 DEGs were identified from the early onset CRC compared to healthy controls. These genes were found to be involved in several biological processes, including cell communication, cell proliferation, cell shape and apoptosis. Five functional modules which may play important roles in the initiation of early onset CRC were identified from the PPI network. Functional annotation revealed that these five modules were involved in the pathways of signal transduction, carcinogenesis and metastasis. The hub nodes of these five modules, CDC42, TEX11, QKI, CAV1 and FN1, may serve as the biomarkers of early onset CRC and have the potential to be targets for therapeutic intervention. However, further investigations are still needed to confirm our findings.