Navigating colorectal cancer prognosis: A Treg-related signature discovered through single-cell and bulk transcriptomic approaches.

ABSTRACT

BACKGROUND: The significance of regulatory T cells (Tregs) in colorectal cancer is unclear. METHODS: The single-cell sequencing data for colorectal cancer, specifically GSE132465 and GSE188711, were retrieved from the GEO database. Simultaneously, bulk transcriptome data were obtained from the UCSC Xena website. To delve into the heterogeneity of Treg cells and identify key genes at the single-cell sequencing level, we employed dimensionality reduction techniques alongside clustering and conducted differential expression gene analysis. For the bulk transcriptome data, we utilized weighted co-expression network analysis to investigate critical gene modules. Additionally, we employed COX regression and Lasso regression methodologies to construct prognostic models, thereby assessing patient outcomes. To facilitate outcome evaluation, nomograms were constructed. The integration of these diverse approaches aims to comprehensively study colorectal cancer, encompassing single-cell heterogeneity, key gene identification, and prognosis modeling using both single-cell and bulk transcriptome data. Polymerase chain reaction (PCR) experiments are used to verify mRNA expression levels of key genes. The analysis software was R software (version 4.3.2). RESULTS: Through single-cell sequencing analysis and bulk transcriptome analysis, we constructed a prognostic model composed with Treg-associated signatures. The high-risk group demonstrated significantly worse prognosis compared with the low-risk group, highlighting the clinical relevance of our models. PCR confirmed that the key gene DEAH-box helicase 15 (DHX15) was significantly overexpressed in colorectal cancer. CONCLUSIONS: The prognostic models developed in this study offer a potential tool for risk assessment, guiding treatment decisions for colorectal cancer patients.