Single-cell RNA sequencing defines prognostic subtypes and identifies AIF1L as a therapeutic target in colorectal cancer

Colorectal cancer (CRC) progression and therapy resistance are driven by heterogeneous tumor cell populations and microenvironmental interactions. However, a comprehensive single-cell atlas across patients that captures this heterogeneity, and its clinical implications has been lacking. Such an atlas could reveal rare tumor subpopulations that underpin disease aggressiveness and offer new prognostic biomarkers or therapeutic targets. We integrated two high-quality single-cell RNA sequencing datasets from 29 CRC patients to construct a cellular atlas encompassing immune, stromal and epithelial compartments. Malignant epithelial cells were distinguished via inferCNV-based copy number alteration analysis and reclustered, yielding seven transcriptionally distinct malignant subpopulations. One malignant epithelial cluster, marked by high expression of the long non-coding RNA ELFN1-AS1, exhibited the highest stemness signature. From this stem-like cluster, we derived a four-gene prognostic model (RPL21, GAL, ELFN1-AS1, AIF1L). In the TCGA-COAD cohort, this model stratified patients into high-risk and low-risk groups with significantly different survival outcomes, with the high-risk group experiencing significantly worse survival. High-risk tumors were enriched for metabolic and translational pathways and displayed distinct immune and genomic features. AIF1L was identified as a hub gene within the signature, and its knockdown in CRC cells enhanced migration and invasion, functionally validating its role in tumor progression. Our study provides a high-resolution single-cell atlas of CRC and identifies a previously unrecognized stem-like tumor cell subpopulation with prognostic significance. These findings highlight novel prognostic biomarkers and suggest potential therapeutic targets (such as AIF1L) that could inform patient stratification and the development of targeted therapies for CRC.