Integrative analysis of RiboSis-related gene expression in colorectal cancer: implications for prognosis and immunotherapy.

Colorectal cancer (CRC) is a prevalent and lethal malignancy that imposes significant burdens on patients and healthcare systems worldwide. This study aimed to explore the significance of ribosome biogenesis (RiboSis)-related genes (RRGs) in CRC and their clinical implications. The scRNA-seq data of three CRC tissues were sourced from the Gene Expression Omnibus (GEO) database. Nonnegative matrix factorization (NMF) was employed to categorize cell subtypes associated with RiboSis. An integrative machine learning approach encompassing ten algorithms was subsequently implemented to develop a prognostic signature. Our research revealed 295 differentially expressed RiboSis-related genes (DERRGs) associated with survival outcomes, with a notable RiboSis score that was markedly higher in CRC tissues than in normal counterparts. Univariate Cox analysis revealed 25 DERRGs with significant survival differences (P < 0.05). scRNA-seq of 26,961 cells from 13 CRC samples revealed eight major cell types, with T and B cells predominantly enriched in immune response pathways. InferCNV analysis distinguished malignant epithelial cells on the basis of copy number variations, and NMF identified four RiboSis-related cell subtypes. Our RiboSis-related prognostic model, validated across the TCGA, GSE17536, and GSE39582 datasets, demonstrated high predictive accuracy. Notably, low RiboSis signature scores were correlated with reduced immune evasion risk and upregulated immune checkpoint genes, suggesting enhanced responsiveness to immunotherapy. Among the 8 model genes, PFDN2 was considered the hub gene. The experimental results of PFDN2 in this RiboSis signature indicated that PFDN2 expression is elevated in CRC tissues and that PFDN2 knockdown promotes the proliferation, migration, and invasion of CRC cells. This study underscores the potential of RRGs as biomarkers and therapeutic targets, offering new avenues for personalized CRC management.