T-cell exhaustion indicator characterizes the tumor microenvironment landscape and predicts colon adenocarcinoma prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing.

[BACKGROUND] Colon adenocarcinoma (COAD) is the most common type of colon cancer, posing a significant threat to public health. In the tumor microenvironment (TME), T cells differentiate into terminally exhausted T cells (TEX), but the relationship between TEX and COAD has not been fully elucidated.

[METHODS] To identify TEX-related signatures, we integrated transcriptomic data from TCGA and GEO databases (GSE103479, GSE17536). A prognostic model was constructed using GSVA, univariate Cox, LASSO, and random forest algorithms. The tumor immune microenvironment was characterized using CIBERSORTx and GSEA. The functional role of FAT4 was validated in vitro using FAT4-knockdown COAD cell lines assessed by flow cytometry and RT-qPCR.

[RESULTS] We developed a prognostic signature based on five TEX-related genes (IL21R, FCRL3, TIFAB, TNFSF14, SLAMF1). Patients in the high-risk group showed significantly poorer overall survival and distinct immune cell infiltration patterns, characterized by decreased CD8 + T cells and M1 macrophages. At single-cell resolution, CD8 + TEX cells exhibited high expression of immune checkpoints like LAG3. Furthermore, in vitro experiments demonstrated that knockdown of FAT4, a frequently mutated gene in COAD, promoted apoptosis and induced G0/G1 cell cycle arrest in COAD cells.

[CONCLUSION] We proposed a non-invasive prediction method based on TEX-related genes, which effectively predicts survival outcomes and therapeutic responses in COAD patients. Additionally, FAT4 was found to regulate proliferative and apoptotic phenotypes in COAD.