Circulating lncRNAs as Early Diagnostic Biomarkers for Colorectal Cancer: A case-control diagnostic accuracy study

Purpose This study aimed to identify and validate long non-coding RNAs (lncRNAs) as diagnostic biomarkers for Colorectal cancer (CRC) and its precursors, focusing on early-stage risk stratification. Methods We performed bioinformatics analysis of public datasets and in-house RNA-sequencing data to identify dysregulated lncRNAs in the adenoma–carcinoma sequence. Plasma samples were collected from patients with non-advanced adenomas, advanced adenomas, CRC, and healthy controls. Candidate lncRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR). Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis, and lncRNA combinations were assessed to improve accuracy. Integration with CEA was also explored. Results We identified 37 differentially expressed lncRNAs, of which four—FOXP4-AS1, CRNDE, UCA1, and SNHG17—showed significant dysregulation in plasma. ROC analysis indicated that UCA1 and SNHG17 effectively distinguished advanced adenomas from healthy controls (area under the curve = 0.835 and 0.812, respectively). The three-lncRNA panel FOXP4-AS1 + UCA1 + SNHG17 achieved an area under the curve of 0.906 for CRC detection and 0.861 for advanced adenomas. Combining lncRNAs with CEA further enhanced diagnostic performance, reaching area under the curve values of 0.950 for CRC and 0.893 for advanced adenomas. Conclusion FOXP4-AS1, CRNDE, UCA1, and SNHG17 are promising plasma-based biomarkers for CRC and adenoma detection. When combined into multi-lncRNA panels, they offer a non-invasive, high-performance approach for early CRC screening and risk-based stratification. Further large-scale, multi-center validation is needed to establish their clinical applicability and integration into routine screening.