Investigation of a common gene expression signature in gastrointestinal cancers using systems biology approaches

Mol Biosyst. 2017 Oct 24;13(11):2277-2288. doi: 10.1039/c7mb00450h.

Abstract

According to GLOBOCAN 2012, the incidence and the mortality rate of colorectal, stomach and liver cancers are the highest among the total gastrointestinal (GI) cancers. Here we aimed to find the common genes and pathways that are simultaneously deregulated in these three malignancies using systems biology approaches. Here we conducted a differential expression analysis on high-quality gene expression datasets of gastric cancer (GC), colorectal cancer (CRC) and hepatocellular carcinoma (HCC). To address the inter gene correlations that were neglected in differential expression studies, we also applied differential co-expression analysis on the understudied datasets. The common significant differentially expressed genes (DEGs) among the three cancers were used for further regulatory and PPI network construction. In parallel the regulatory roles of miRNAs and lncRNAs in the common DEGs were investigated. 23 common DEGs were detected between GC, CRC and HCC. Two cases of potential feed forward loops were identified in the constructed TF-target regulatory network, indicating the probable cross-talk between biological pathways. The result of a vulnerability test on the common PPI network resulted in the finding of three candidates, the simultaneous targeting of which will disintegrate the main parts of the network. The results of the differential co-expression study led to the identification of respectively 7 and 1 common differentially co-expressed pairs of genes between GC and CRC and between CRC and HCC. The results of the differential expression study introduced new common players in CRC, GC and HCC and provided better insights into the molecular characteristics of these GI malignancies. Moreover, we concluded that differential co-expression studies are an essential complement for differential expression studies that just take single differentially expressed genes into account.

MeSH terms

  • Computational Biology / methods
  • Databases, Genetic
  • Gastrointestinal Neoplasms / genetics*
  • Gene Expression Profiling*
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks
  • Humans
  • MicroRNAs / genetics
  • RNA Interference
  • RNA, Long Noncoding / genetics
  • RNA, Messenger / genetics
  • Systems Biology* / methods
  • Transcriptome*

Substances

  • MicroRNAs
  • RNA, Long Noncoding
  • RNA, Messenger