Abstract
Background/Objectives: Patients with ulcerative colitis (UC) carry a substantially elevated risk of developing colorectal cancer (CRC); yet, the transcriptional intermediates that bridge chronic mucosal inflammation and colorectal malignancy remain poorly characterized. A related question is whether any genes shared between the two conditions actually help drive transformation, or whether they represent downstream responders. Methods: We integrated two UC microarray cohorts (totalling 227 samples) and the TCGA-COAD dataset (n = 524), combining weighted gene co-expression network analysis (WGCNA) with directional differential expression to define shared candidate genes. Three machine-learning approaches—LASSO, random forest, and SVM-RFE—were applied to that candidate set, and the stability of their intersection was assessed by bootstrap resampling. The resulting panel was then examined by replication in an independent UC cohort, two-sample Mendelian randomization, immune deconvolution, survival modelling, and Visium spatial transcriptomics. Results: WGCNA and directional differential expression together yielded 91 shared candidate genes, and the three algorithms converged on four: CXCL1, S100P, THY1, and TRIM29. Bootstrap resampling showed that this convergence is a property of one particular fit rather than a reproducible selector (all four recovered together in 0.3% of 1000 resamples), so we treated the ensemble as a hypothesis-generating step and made our case for the panel based on independent downstream evidence. This evidence was consistent, as, in an independent UC cohort (GSE92415, n = 183), all four genes moved in the same direction as in discovery, and a four-gene model separated inflamed from control mucosa with a cross-validated AUC of 0.986 (95% CI 0.965–1.000). Two-sample Mendelian randomization using strong blood cis-eQTL instruments (F = 345 for CXCL1, F = 2423 for S100P) returned null estimates; for S100P, the design had 80% power to detect an odds ratio of 1.07 per standard deviation, so this is an informative null rather than an absence of data, while THY1 and TRIM29 had no cis-eQTLs in eQTLGen and remain untestable. Each gene showed a distinct pattern of immune cell correlation in TCGA-COAD. LASSO-Cox retained only CXCL1, whose higher expression was associated with a better rather than worse overall survival (HR 0.79 per SD, p = 0.020); its discrimination was weak (optimism-corrected C-index 0.56 for the score alone) and did not reach significance in an external cohort (GSE39582, n = 573; p = 0.11), so we reported no prognostic model. In Visium spatial data from four colonic sections, a three-compartment structure was reproducible between UC sections—CXCL1 near the neutrophil and interferon signals, THY1 within the stroma and anticorrelated with the epithelium, and S100P and TRIM29 alongside the epithelium—although, with two sections per group, the difference in module scores between the UC and control mucosa was not resolvable. Conclusions: Collectively, these four genes describe a spatially structured epithelial–stromal–immune module of the inflamed mucosa; however, the findings are hypothesis-generating and are not sufficient for prognostic or stratification use.