Colorectal cancer (CRC) has become the second most common digestive tract tumor. Even though the means to treat colon cancer have improved, patients prognosis is low due to the lack of accurate molecular targets. Hence, it urgently demanded better biomarkers for prognosis and progression of colon cancer. This study explores the hub gene associated with the prognosis of colorectal cancer and further analyzes the hub gene function. In this study, all genes mRNA expression data were from the cancer genome atlas (TCGA) colon cancer database and the Gene Expression Omnibus (GEO). These databases were used to screen the differentially expressed co-genes between colon cancer tissue and normal tissue. Weighted Gene Co-expression Network Analysis screened out a total of 103 differential co-expression genes (WGCNA). According to the R cluster profile package annotation analysis, these genes biological functions mainly concentrate on energy metabolism. Moreover, in the protein-protein interaction (PPI) network, the CytoHubba plugin of Cytoscape was used to screen out ten genes (CLCA1, ZG16, GUCA2B, GUCA2A, CLCA4, SLC26A3, MS4A12, GCG, SI, and NR1H4). According to the survival analysis results, high expression of CLCA1has better overall survival and disease-free survival in patients with CRC. Simultaneously, the mRNA expression of CLCA1 in normal tissues was higher than that in CRC tissues. Besides, there were significant differences in the expression of CLCA1 in pathological stage, T stage, and M stage. By using a gene set enrichment analysis, we found several considerable enrichment pathways in the high-groups. CIBERSORT analysis for the proportion of TICs revealed that B-cell naive, dendritic cells, plasma cells, and CD4+ T cells were positively correlated with CLCA1 expression, suggesting that CLCA1 might be responsible for the preservation of immune-dominant status for TME. Finally, in the Human Protein Atlas (HPA) database, the protein level of CLCA1 in the colorectal cancer samples decreased, consistent with the down-regulation of the mRNA expression level CLCA1. To sum up, by integrating WGCNA with differential gene expression analysis, this research generated a significant survival correlative gene called CLCA1 that can predict prognosis prediction in colon cancer.