A Combined four-mRNA Signature Associated with Lymphatic Metastasis for Prognosis of Colorectal Cancer.

Background: Colorectal cancer (CRC) is one of the most common malignant tumors in the world. Lymph node metastasis (LNM) is a common mode of metastasis of CRC. However, the combined mRNA biomarkers associated with LNM of CRC that can effectively predict CRC prognosis have not been reported yet. Methods: To identify biomarkers that are associated with LNM, we collected data from the The Cancer Genome Atlas (TCGA) database. The edgeR package was searched to seek LNM-related genes by comparisons between cancer samples and normal colorectal tissues and between LNM and non-LNM (NLNM) of CRC. Univariate and multivariate regression analysis of genes in the intersection to build gene signature associated with independent prognosis of CRC, and then verified by Kaplan-Meier curve and log-rank test, receiver operating characteristic (ROC) curve was used to determine the efficiency of survival prediction of our four-mRNA signature. Finally, the potential molecular mechanisms and properties of these gene signature were also explored with functional and pathway enrichment analysis. Results: 329 mRNAs were up-regulated in CRC tissues with LNM, and 8461 mRNAs were up-regulated in CRC tissues, the intersection is 100 mRNAs. After univariate and multivariate Cox regression analysis of 100 mRNAs, a novel four LNM related mRNAs (EPHA8, KRT85, GABRA3, and CLPSL1) were screened as independent prognostic indicators of CRC. Surprisingly, the four-mRNA signature can predict the prognosis of CRC patients independently of clinical factors andthe area under the curve (AUC) of the ROC is 0.730. The novel four-mRNA signature was used to identify high and low-risk groups. Stratified analysis indicated the risk score based on four-mRNA signature was an independent prognostic indicator for female, T3+T4, N1+N2 ,stage III+IV and patients with no new tumor event. Functional annotation of this risk model in high-risk patients revealed that pathways associated with neuroactive ligand-receptor interaction, estrogen signaling pathway, and steroid hormone biosynthesis. Conclusions: By conducting TCGA data mining, our study demonstrated that a four-mRNA signature associated with LNM can be used as a combined biomarker for independent prognosis of CRC.