Abstract
Colorectal cancer (CRC) ranks as the second leading cause of cancer-related mortality worldwide. Regulatory T cells (Tregs) are a key constituent of immune cells in the tumor microenvironment (TME) and are significantly associated with patient outcomes. Our study aimed to construct a Treg-associated signature to predict the prognosis of CRC patients. The genes' expression values and patients' clinicopathological features were downloaded from TCGA and gene expression omnibus (GEO) databases. The single-cell RNA (scRNA) sequencing data of CRC were analyzed through the Deeply Integrated human Single-Cell Omics database. WGCNA analysis was used to select Tregs-associated genes (TrAGs). The infiltrated levels of immune and stromal cells were accessed through the ESTIMATE algorithm. Cox regression analysis and the LASSO algorithm were implemented to construct prognostic models. Gene set enrichment analysis (GSEA) was performed to annotate enriched gene sets. Based on scRNA sequencing data, our study uncovered that more Tregs were significantly enriched in the TME of CRC. Then we identified 123 differentially expressed TrAGs which mainly participated in immune regulation. Given that CRC patients were reclassified into 2 subgroups with distinct overall survival based on 26 differentially expressed TrAGs with prognostic values, we subsequently constructed a signature for CRC. After training and validating in independent cohorts, we proved that this prognostic model can be well applied to predict the prognosis of CRC patients. Further analysis exhibited that more tumor-suppressing immune cells and higher immune checkpoint genes were enriched in CRC patients with high-risk scores. Moreover, immunohistochemistry analysis validated that the genes in the prognostic model were significantly elevated in CRC tissues. We were the first to construct a prognostic signature for CRC based on TrAGs and further revealed that the poor prognosis of patients was mainly attributed to the tumor-suppressing microenvironment and upregulated immune checkpoint genes in tumor tissues.