Background: The N6-methyladenosine (m6A) RNA modification can modify long non-coding RNAs (lncRNAs), thereby affecting the tumorigenesis and progression of tumors. However, the underlying role of m6A-modified lncRNAs in colorectal cancer (CRC) remains largely unknown. Therefore, our aim was to assess the prognostic value of m6A-modified lncRNAs in CRC patients. Methods: The gene expression and clinicopathological data of CRC were extracted from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was used to investigate the m6A-modified lncRNAs. Consensus clustering was conducted to identify molecular subtypes of CRC, and the clinical significance of molecular subtypes was identified. The least absolute shrinkage and selection operator analysis (LASSO) was applied to establish a risk signature. Finally, a prognostic nomogram with risk score and clinicopathological variables was established. Results: In total, 29 m6A-modified lncRNAs were identified as prognostic lncRNAs. Two molecular clusters were identified and significant differences were found with respect to clinicopathological features and prognosis. Cluster1 is associated with poor overall survival (OS), down-regulation of Programmed cell death ligand-1 (PD-L1) expression, lower immune score, and less immune cell infiltration. Then, an m6A-modified lncRNA signature for predicting OS was constructed in the TCGA training cohort. The signature demonstrated favorable prediction performance in both training and validation sets. Compared with low-risk patients, patients with high risk showed worse clinical outcomes, lower immune scores, and downregulated PD-L1 expression. Further analysis indicated that the signature was an independent prognostic indicator, and then a prognostic nomogram based on risk score, tumor location, and tumor stage was established. Conclusions: Our study identified a seven m6A-modified lncRNA signature and established a prognostic nomogram that reliably predicts OS in CRC. These findings may improve the understanding of m6A modifications in CRC and provide insights into the prognosis and treatment strategy of CRC.

Background: Detection of colorectal cancer (CRC) currently relies mainly on invasive procedures such as colonoscopy. In experimental models, tumor hypoxia induces epigenetic, metabolic, and immune changes via hypoxia-inducible factor (HIF) signaling. Building on these published insights, this study evaluated whether a panel of biomarkers previously associated with hypoxia-related processes, plasma methylated SEPT9 (mSEPT9), urinary N¹, N¹²-diacetylspermine (DiAcSpm), and systemic inflammatory indices (NLR, PLR, and LMR)—could be combined into a non-invasive diagnostic panel and compared with standard serum tumor markers. This study focused solely on diagnostic performance; it did not directly assess tumor hypoxia or HIF expression in patients. This study was conducted in a clinical diagnostic setting (patients with confirmed CRC, polyps, or benign surgical conditions) and does not represent a population-based screening cohort. Limitations include the lack of an external validation cohort; all analyses were performed on a single dataset, and the reported performance metrics may be optimistic. Independent validation is required before clinical implementation. Methods: This prospective single-center study enrolled 382 participants: 142 with CRC, 62 with colorectal polyps, and 178 non-malignant controls. Plasma mSEPT9 was quantified by real-time PCR, urinary DiAcSpm by ELISA, and inflammatory indices from blood counts. Serum tumor markers (CEA, CA19-9, CA125, and AFP) were measured by immunoassay. Diagnostic accuracy was assessed using ROC analysis and multivariable logistic regression. Results: mSEPT9 (AUC 0.843) and DiAcSpm (AUC 0.831) demonstrated significantly higher diagnostic accuracy than CEA (AUC 0.660) and CA19-9 (AUC 0.649). A combined panel including mSEPT9, DiAcSpm, NLR, PLR, and LMR achieved an AUC of 0.947, with 85.9% sensitivity and 92.9% specificity. This panel also showed strong performance for early-stage CRC (AUC 0.905). Conclusions: A multimarker panel of biomarkers (mSEPT9, DiAcSpm, NLR, PLR, and LMR) provides a non-invasive diagnostic approach for CRC detection in a clinical case–control setting. Validation in asymptomatic screening populations is required before any screening claim can be made. These findings are associative; direct evidence that tumor hypoxia drives these biomarker changes was not obtained and requires future investigation.

Background: Early detection of colorectal cancer (CRC) still relies mainly on invasive screening. Tumor hypoxia induces epigenetic, metabolic, and immune changes via hypoxia-inducible factor (HIF) signaling in experimental models. Building on these insights, this study evaluated whether hypoxia pathway biomarkers—plasma methylated SEPT9 (mSEPT9), urinary N¹, N¹² diacetylspermine (DiAcSpm), and systemic inflammatory indices (NLR, PLR, LMR)—could be combined into a noninvasive diagnostic panel compared with standard serum tumor markers. The study focused solely on diagnostic performance; it did not directly assess tumor hypoxia or HIF expression in patients. Methods: This prospective single-center study enrolled 382 participants: 142 with CRC, 62 with colorectal polyps, and 178 non-malignant controls. Plasma mSEPT9 was quantified by real-time PCR, urinary DiAcSpm by ELISA, and inflammatory indices from blood counts. Serum tumor markers (CEA, CA19-9, CA125, AFP) were measured by immunoassay. Diagnostic accuracy was assessed using ROC analysis and multivariable modeling. Results: mSEPT9 (AUC 0.843) and DiAcSpm (AUC 0.831) demonstrated significantly higher diagnostic accuracy than CEA (AUC 0.660) and CA19-9 (AUC 0.649). A combined panel including mSEPT9, DiAcSpm, NLR, PLR, and LMR achieved an AUC of 0.947, with 85.9% sensitivity and 92.9% specificity. This panel also showed strong performance for early-stage CRC (AUC 0.905).” Conclusions: A multimarker panel of previously reported hypoxia-associated biomarkers (mSEPT9, DiAcSpm, NLR, PLR, and LMR) provides a scalable, noninvasive approach for CRC detection with high diagnostic accuracy. These findings are associative; direct evidence that tumor hypoxia drives these biomarker changes in patients was not obtained and requires future investigation.