SEPTIN9 (Septin 9)

Key tumor markers with diagnostic, prognostic, and predictive value, including CEA, CA19-9, mSEPT9, ctDNA, TPS, TAG-72, CTCs, and circulating microRNAs, as well as p53 and PTEN proteins, are reviewed in the context of their clinical utility in early detection, disease monitoring, and treatment response assessment. The analysis also highlights the epidemiological situation in Poland and underscores the growing importance of integrating molecular biomarkers with traditional diagnostic methods, which may ultimately support the development of more precise and individualized clinical management strategies in the future.

Multivariate regression identified mSEPT9, CEA, CA19-9, FOBT, RDW-CV, and PLR as independent CRC-related factors. Notably, their combined model achieved an area under the curve (AUC) of 0.939, with a sensitivity of 0.920 and specificity of 0.839, offering a valuable non-invasive strategy to enhance CRC diagnosis.

Multivariate analysis further identified tumor size (OR = 1.974, 95% CI: 1.321-2.950, P = 0.005) and TNM stage (OR = 2.117, 95% CI: 1.452-3.087, P = 0.002) as independent predictors of multi-gene methylation positivity. Multi-gene methylation detection showed high diagnostic value for CRC and may serve as a valuable adjunct tool in CRC screening strategies.

This method effectively distinguishing colorectal cancer cells from human colonic epithelial cells and colorectal cancer patients from healthy individuals, showing excellent performance in real sample analysis. The proposed method provides a dependable tool for site-specific methylation detection with promising applications in biological research and clinical diagnosis.

The diagnostic sensitivities of the model for CRC of different stages were 85.71% for stage Ⅰ, 92.86% for stage Ⅱ, 78.95% for stage Ⅲ, and 87.50% for unstaged cases. A diagnostic model based on the methylation levels of the SEPTIN9, BCAT1, IKZF1, BCAN, and VAV3 genes in plasma demonstrates good diagnostic performance for CRC, particularly in early-stage cases.

DNA methylation and microRNA biomarkers hold strong promises for non-invasive CRC screening. Multi-marker panels demonstrate superior diagnostic accuracy and may provide a cost-effective, scalable approach for early CRC detection in resource-limited settings.

These findings indicate a potential association between SEPT9 methylation and radiotherapy response in ESCC. While promising, further validation is needed before SEPT9 methylation can be established as a reliable clinical biomarker or therapeutic target.

Cytological examination combined with methylation detection can greatly improve the diagnosis rate of malignant ascites. The methylation status of SHOX2 and SEPTIN9 genes is significantly correlated with the prognosis of patients with ascites.

This study demonstrates the potential of AI/ML models for predicting CRC risk in resource-limited and culturally diverse populations like American Samoa. However, significant barriers, including cultural, financial, and logistical factors, limit patient follow-up and the broader implementation of these technologies. Future research should focus on addressing these barriers, enhancing community engagement, and integrating culturally appropriate interventions to improve CRC screening and outcomes in underserved populations.

QUADAS-2 illustrated a potential high risk of bias in patient selection and flow/timing domains, which underscores the need for more standardized diagnostic workflows and assay protocols. Future research should focus on multi-marker panels, adherence to regulatory thresholds, cost-effectiveness analyses, and clear clinical management pathways to facilitate the widespread implementation of plasma-based CRC screening.

These findings suggest that the DNA methylation biomarkers panel could revolutionize HCC diagnostics by enabling earlier, more accurate, and cost-effective detection, particularly in high-risk populations.

Additionally, decitabine treatment induced a reduction in SEPT9 methylation levels, which affects microtubule stability, suggesting a potential mechanistic link to tumor invasion. These findings indicate that SEPT9 methylation is a promising biomarker for distinguishing invasive breast cancer from DCIS and for identifying high-risk DCIS lesions with greater potential for progression.