Identification of Prognostic Genes for Colon Cancer through Gene Co-expression Network Analysis

Abstract

Objective

The present study was aimed to identify novel key genes, prognostic biomarkers and molecular pathways implicated in tumorigenesis of colon cancer.

Methods

The microarray data GSE41328 containing 10 colon cancer samples and 10 adjacent normal tissues was analyzed to identify 4763 differentially expressed genes. Meanwhile, another microarray data GSE17536 was performed for weighted gene co-expression network analysis (WGCNA).

Results

In present study, 12 co-expressed gene modules associated with tumor progression were identified for further studies. The red module showed the highest association with pathological stage by Pearson’s correlation analysis. Functional enrichment analysis revealed that genes in red module focused on cell division, cell proliferation, cell cycle and metabolic related pathway. Then, a total of 26 key hub genes were identified, and GEPIA database was subsequently selected for validation. Holliday junction-recognizing protein (HJURP) and cell division cycle 25 homolog C (CDC25C) were identified as effective prognosis biomarkers, which were all detrimental to prognosis. Gene set enrichment analyses (GSEA) found the two hub genes were enriched in “oocyte meiosis”, “oocyte maturation that are progesterone-mediated”, “p53 signaling pathway”, and “cell cycle”. Furthermore, the immunohistochemistry and western blotting showed that HJURP was highly expressed in colon cancer tissue.

Conclusion

HJURP was identified as a key gene associated with colon cancer progression and prognosis by WGCNA, which might influence the prognosis by regulating cell cycle pathways.

Keywords

colon cancer / biomarkers / weighted gene co-expression network analysis / prognosis / pathological stage

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