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https://dspace.iiti.ac.in/handle/123456789/18898
| Title: | Non-invasive biomarkers for early oral cancer detection through multiomics approach |
| Authors: | Verma, Tarun Prakash Singh, Siddharth Jha, Hem Chandra |
| Issue Date: | 2026 |
| Publisher: | Springer Nature |
| Citation: | Verma, T. P., Singh, S., Meloth, S., Chaudhary, N., Nad, P., Chaudhary, A., Chandramohanadas, R., Agrawal, D., & Jha, H. C. (2026). Non-invasive biomarkers for early oral cancer detection through multiomics approach. British Journal of Cancer. https://doi.org/10.1038/s41416-026-03540-9 |
| Abstract: | Background: Non-invasive biomarker-based approaches are urgently needed to support early identification and monitoring of Oral squamous cell carcinoma (OSCC) and its precursor, oral submucous fibrosis (OSMF). Methods: We employed combined metabolomic and proteomic analyses to profile saliva and lesion surface swabs from clinically diagnosed OSCC (n = 15), OSMF (n = 20), and healthy controls (n = 27). Polar and nonpolar metabolites were extracted separately from saliva, while proteins were isolated from exfoliated mucosal epithelial cells. Differential expression, pathway enrichment, and biomarker classification were performed across four comparisons: OSCC vs non-OSCC (controls + OSMF), OSCC vs OSMF, OSMF vs control, and OSCC vs control. Results: Distinct molecular changes were observed across the health-to-cancer spectrum. Top discriminatory salivary metabolites included linoelaidic acid, gamma-glutamylcysteine, and 3-hydroxybutyryl-CoA, implicating dysregulated linoleic acid metabolism, redox imbalance, and fatty acid β-oxidation in pathogenesis. Proteomic data revealed significant upregulation of histone variants, cytoskeletal keratins, and BPI-fold-containing proteins in OSCC, reflecting chromatin remodelling and epithelial-mesenchymal transition. Multivariate biomarker panels achieved high accuracy (AUC ≥ 0.96) for classifying OSMF from OSCC. Conclusion: Our combined metabolomic and proteomic profiling revealed non-invasive molecular signatures for early detection and monitoring of OSCC and OSMF. © The Author(s), under exclusive licence to Springer Nature Limited 2026. |
| URI: | https://dx.doi.org/10.1038/s41416-026-03540-9 https://dspace.iiti.ac.in:8080/jspui/handle/123456789/18898 |
| ISSN: | 0007-0920 |
| Type of Material: | Journal Article |
| Appears in Collections: | Department of Physics Mehta Family School of Biosciences and Biomedical Engineering |
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