Abstract
Colon adenocarcinoma (COAD) is the most common histologic subtype of colorectal cancer (CRC), and its prognosis is poor. Unlike traditional research in molecular biology, which is limited to analyzing the function of a single gene or protein in malignant tumors. The Weighted gene correlation network analysis (WGCNA) technique is used to describe the gene association model among different samples in order to identify highly collaborative genes. In this study, a computational strategy was used to conduct a systematic study of prognosis-related genes (PRGs) of COAD from the TCGA database. PRGs were subsequently used for WGCNA, which included 379 COAD patient expression profiles and 39 controls. As a consequence, nine gene modules were built. Among these, the brown module had not only a negative relationship with COAD, but also simultaneously in inverse relationship with the clinical stage, stage T, stage M and stage N. C4orf19, which was identified as one of the DEG and hub genes in the brown module by calculating modular connectivity, has a negative correlation with the clinical stage and TMN stage. In addition, the downward-regulated C4orf19 protein was detected in COAD clinical specimens. Finally, in vitro experiments have confirmed that regulated C4orf19 can promote COAD cell proliferation, invasion and migration, and the biological mechanism of C4orf19 perhaps by influencing the nitrogen metabolic pathway.