Adenomatous polyps of the colon are the most common neoplastic
polyps. Although most of
adenomatous polyps do not show malign transformation, majority of
colorectal carcinomas originate from neoplastic
polyps. Therefore, understanding of this transformation process would help in both preventive
therapies and evaluation of
malignancy risks. This study uncovers alterations in gene expressions as potential
biomarkers that are revealed by integration of several network-based approaches. In silico analysis performed on a unified microarray cohort, which is covering 150 normal colon and
adenomatous polyp samples. Significant gene modules were obtained by a weighted gene co-expression network analysis. Gene modules with similar profiles were mapped to a colon tissue specific functional interaction network. Several clustering algorithms run on the colon-specific network and the most significant sub-modules between the clusters were identified. The
biomarkers were selected by filtering differentially expressed genes which also involve in significant biological processes and pathways.
Biomarkers were also validated on two independent datasets based on their differential gene expressions. To the best of our knowledge, such a cascaded network analysis pipeline was implemented for the first time on a large collection of normal colon and
polyp samples. We identified significant increases in TLR4 and MSX1 expressions as well as decrease in
chemokine profiles with mostly pro-tumoral activities. These
biomarkers might appear as both preventive targets and
biomarkers for risk evaluation. As a result, this research proposes novel molecular markers that might be alternative to endoscopic approaches for diagnosis of
adenomatous polyps.