ArticleFrontiers in oncology2026
Artificial intelligence driven multi-omics framework identifies COL6A3 as a diagnostic biomarker and a putative gene target modulated by Embelin in Colorectal cancer.
Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Bioinformatics analysis and experimental validation confirm COL6A3 as a promising target for renal cell carcinoma therapy.Translational andrology and urology · 2026Article
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2 authors.
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Abstract
Background: The third leading cause of death worldwide is colorectal cancer due to a lack of early detection biomarkers and therapeutic small molecules. Advances in systems biology offer a combination of multi-omics and Artificial intelligence to discover the potential biomarkers and targets. Methods: We used a combination of Results: Trained model predicted COL6A3 as a prominent hub gene across all three ML algorithms with high cross validation accuracy (AUC values: > ~0.90), showing the accuracy of predictions and feature selections of the trained model. Embelin treatment results in the upregulation of pro-apoptotic markers (BAX, CASPASE3) and the downregulation of anti-apoptotic genes (BCL2, PI3KCA). These findings suggest that COL6A3 is a candidate biomarker and a potential mediator of embelin activity. Conclusion: This study underscores the integration of AI, multi-omics, and
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