Construction and Validation of a Coagulation Factor-Related Prognostic Model for Colorectal Cancer Based on the Public Database

Abstract

Abstract Background:Colorectal cancer is one of the most common malignant cancers in the world, which is a serious threat to human health with increasingly diagnosed cases every year.It has been reported that coagulation factors play an important role in various cancer. However, the role of coagulation factor-related genes in colorectal cancer remains unknown. Methods: Gene expression data with clinical information of colorectal cancer samples were downloaded from the TCGA (The Cancer Genome Atlas) database and Gene Expression Omnibus (GEO) database, respectively. The coagulation factor-related prognostic model was constructed based on univariate, LASSO, and multivariate Cox regression analysis. In addition, colorectal cancer patients were classified into different subtypes according to non-negative matrix factorization (NMF) analysis. The nomogram and calibration curves were plotted to validate the accuracy of the coagulation factor-related prognostic model.Finally, the proportion of the infiltrating immune cells in different risk groups was analyzed by using immune cell infiltration Results: Seven coagulation factor-related genes were screened out to establish a prognostic model. The risk score of each colorectal cancer sample was calculated by the product of each prognostic coagulation factor-related gene with prognostic value and the corresponding gene expression of each prognostic coagulation factor-related gene. Patients with colorectal cancer were classified into high- and low-risk groups according to the median risk score. Survival curves indicated that colorectal cancer patients in the high-risk group had a worse prognosis both in the training set, internal validation set, and external validation set. Colorectal cancer patients were divided into three subtypes (subtype C1, subtype C2, and subtype C3) according to the optimal number of clusters. The nomogram we established was accurate to predict the overall survival of colorectal cancer patients. The Sankey plot suggested that colorectal cancer patients in the subtype C2 and low-risk group had a better prognosis. Finally, immune cell infiltration analysis indicated that macrophages might play an important role in the development of colorectal cancer. Conclusion: The coagulation factor-related prognostic model was established based on STIM1, PLCB1, MAPK12, F2RL2, C8G, C9, and ADCY5. The colorectal cancer patients were divided into three subtypes, including subtype C1, subtype C2, and subtype C3. These findings might provide novel therapeutic strategies for the treatment of patients with colorectal cancer.