ArticleJournal of advanced research2026
Clinical validation of a multi-model blood cfDNA methylation assay for early-stage gastrointestinal cancer screening.
Article in Journal of advanced research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Biomarkers in Gastric Cancer: Blood Biomarkers, Liquid Biopsy, Artificial Intelligence, and Risk-Stratified Care.Cancers · 2026Review
- Early detection of multiple cancers: the era of methylation-based liquid biopsy.Frontiers in oncology · 2026Review
- The research progress of the synergistic effect of Epstein-Barr virus andFrontiers in oncology · 2026Review
Corrections and comments
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Authors and funding
28 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastrointestinal (GI) tract cancers are the second leading cause of cancer-related mortality, often due to late detection. There is a critical need for non-invasive, highly sensitive biomarkers for early-stage cancer and precancerous lesion detection to enable timely intervention. This study aimed to develop a blood-based method specifically optimized for early GI cancer detection and population-level screening.
methodsUsing large-scale public tissue methylation data and the Twist probe cfDNA profiles, we developed SPOGIT (Screening for the Presence of Gastrointestinal Tumors), a multi-algorithm model (Logistic Regression/Transformer/MLP/Random Forest/SGD/SVC) for early GI cancer detection. The model was rigorously validated through an internal (n = 83) and multicenter external validation (386 cancers/113 controls/580 precancers), with an interception model assessing its clinical potential.
resultsSPOGIT demonstrated high accuracy in detecting GI cancers, with a sensitivity of 88.1 % and a specificity of 91.2 %. Notably, it effectively identified early-stage (0-II) cancers with 83.1 % sensitivity. The model also showed significant potential for intercepting premalignant progression, detecting advanced adenomas (AA) and gastric precancerous lesions with sensitivities of 56.5 % and up to 62.4 %, respectively. In the external independent validation cohort, a complementary model CSO (Cancer Signal Origin) demonstrated an accuracy of 83 % for colorectal cancer and 71 % for gastric cancer. Most importantly, simulation analyses projected that SPOGIT implementation could significantly reduce late-stage diagnoses and increase 5-year survival rate by 27.02 % through early interception.
conclusionsThis study introduced a novel, dual-model blood architecture (SPOGIT/CSO) that enables highly accurate, early detection of GI cancers and their precursors. By facilitating timely clinical intervention, SPOGIT/CSO represented a paradigm-shifting strategy with the potential to significantly improve patient survival outcomes and transform GI cancer management.
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