Integrative transcriptomic analysis identifies miR-642a-5p as a regulator of POFUT1 expression in colon cancer

BackgroundColorectal cancer (CRC) is one of the most common and deadly cancers worldwide, underscoring the urgent need for novel biomarkers and therapeutic targets. Protein O-fucosyltransferase 1 (POFUT1) is increasingly recognized as an oncogenic driver in CRC, but the upstream regulatory mechanisms responsible for its overexpression remain poorly understood. ObjectiveWe aimed to identify a reproducible miRNA signature potentially regulating POFUT1 in colon cancer by combining multiple computational approaches and intersecting their outcomes to retain the most significant candidates and to validate biologically the most promising miRNA to confirm its regulatory potential. MethodsWe implemented an integrative, multi-step bioinformatics framework that combined multiple linear regression with stepwise selection, penalized regression models (LASSO and Elastic Net), and Random Forest analysis for non-linear feature evaluation. miRNAs showing a consistent inverse association with POFUT1 across these complementary methods were retained as final candidates. The most significant miRNA was then validated in vitro by mimic transfection, real-time quantitative PCR, and dual-luciferase reporter assays performed in colon cancer cell lines. ResultsFive miRNAs (miR-92b, miR-484, miR-574, miR-642a, and miR-3940) were consistently identified as negative contributors to POFUT1 expression across all analytical approaches. Among these, miR-642a exhibited the strongest negative correlation (r = - 0.44) with POFUT1. It was therefore selected for biological validation to confirm its regulatory interaction. Overexpression of miR-642a-5p through mimic transfection significantly reduced POFUT1 transcript levels by approximately 46 % in HCT 116, 50 % in SW480, and 22 % in SW620 cells compared with controls. Dual-luciferase reporter assays confirmed direct binding of miR-642a-5p to two predicted sites within the POFUT1 3'UTR, resulting in a decrease of luciferase activity by 40-50 %. ConclusionThis study combines bioinformatics screening based on multiple linear regression and machine learning models, with experimental validation to identify miRNAs regulating POFUT1 expression in colon cancer. This integrative strategy allows the identification of a miRNA signature related to POFUT1 and provides novel insights into its post-transcriptional control. It may serve as a foundation for future diagnostic or therapeutic strategies in CRC.