Integrative Bioinformatics of Bulk and Single-Cell Transcriptomes Identifies Predictive Molecular Features of Ulcerative Colitis-Associated Colorectal Cancer

Ulcerative colitis (UC) is a chronic inflammatory disease that increases the risk of colorectal cancer (CRC), yet the molecular features linking these conditions remain unclear. Here, we integrated bulk RNA sequencing with single-cell transcriptomic data to investigate shared transcriptional programs between UC and CRC. UC-associated differentially expressed genes (DEGs) were mapped onto UC and sporadic CRC single-cell datasets, allowing cell type-resolved analysis of conserved alterations. We found that a subset of UC DEGs displayed consistent dysregulation in sporadic CRC, with strong cell specificity. Myeloid cells-particularly macrophages, neutrophils, and dendritic cells-showed coordinated upregulation of inflammatory genes in both diseases, whereas epithelial cells exhibited convergent downregulation of protective gene modules. These patterns suggest that persistent immune activation and epithelial dysfunction represent shared pathological axes that may contribute to inflammation-driven tumorigenesis. Using bulk data from UC-associated CRC, machine-learning analysis identified four genes with predictive value for UC-to-CRC progression. Overall, this study provides a refined cellular framework for understanding UC-CRC molecular convergence and highlights candidate biomarkers for early detection.