Characterization of pathways involved in colorectal cancer using real-time RT-PCR gene expression data.

Aim: Efforts to explore biomarkers and biological pathways involved in the disease are needed to improve colorectal cancer (CRC) diagnosis and alternative treatments.

Background: The fourth common malignancy in the world is colorectal cancer. The over-all burden is predicted to rise by 2030.

Methods: In the current study, nine genes were selected. Previously, a panel of genes by Agendia, a classifier of robust gene expression (ColoPrint), was determined to significantly improve the prognostic accuracy of pathologic factors in stage II and III colorectal cancer patients. Five genes, including , and from this panel and four other genes which were not in this panel but were cited abundantly in the literature were selected. Then, expression levels of the selected genes in CRC tissue were compared with levels in adjacent normal tissue. To identify the pathways involved in CRC, gene set enrichment analysis was subsequently performed. Furthermore, to illustrate the relationship between genes in this disease, the cross-shaped co-expression pattern and gene regulatory network were determined using computational methods.

Results: This research found that the pairs of genes: {}, {, }, {}, and {} are functionally related. Furthermore, two differentially expressed gene pairs ({} and {}) are involved in the vascular endothelial growth factor receptor signaling pathway and the purine ribonucleoside diphosphate metabolic process, respectively.

Conclusion: This research found that the combination of computational analysis and laboratory data provided the opportunity to better characterize the relation between central colorectal cancer genes as well as possible pathways involved in the colorectal cancer.