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Artificial intelligence-based epigenomic, transcriptomic and histologic signatures of tobacco use in oral squamous cell carcinoma - npj Precision Oncology

Artificial intelligence-based epigenomic, transcriptomic and histologic signatures of tobacco use in oral squamous cell ca...
Oral squamous cell carcinoma (OSCC) biomarker studies rarely employ multi-omic biomarker strategies and pertinent clinicopathologic characteristics to predict mortality. In this study we determine for the first time a combined epigenetic, gene expression, and histology signature that differentiates between patients with different tobacco use history (heavy tobacco use with ≥10 pack years vs. no tobacco use). Using The Cancer Genome Atlas (TCGA) cohort (n = 257) and an internal cohort (n = 40), we identify 3 epigenetic markers (GPR15, GNG12, GDNF) and 13 expression markers (IGHA2, SCG5, RPL3L, NTRK1, CD96, BMP6, TFPI2, EFEMP2, RYR3, DMTN, GPD2, BAALC, and FMO3), which are dysregulated in OSCC patients who were never smokers vs. those who have a ≥ 10 pack year history. While mortality risk prediction based on smoking status and clinicopathologic covariates alone is inaccurate (c-statistic = 0.57), the combined epigenetic/expression and histologic signature has a c-statistic = 0.9409 in predicting 5-year mortality in OSCC patients.

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A new study has identified a multi-omic biomarker for oral squamous cell carcinoma (OSCC) that can predict mortality in patients. The study, which used data from The Cancer Genome Atlas (TCGA) cohort and an internal cohort, found that a combination of epigenetic, gene expression, and histologic markers can differentiate between OSCC patients with different tobacco use histories. The researchers identified 3 epigenetic markers and 13 expression markers that are dysregulated in OSCC patients who were heavy smokers compared to those who never smoked. The study also found that the multi-omic biomarker, when combined with clinicopathologic factors, was highly predictive of mortality in OSCC patients. This new biomarker panel is the most accurate in predicting 5-year mortality in OSCC patients to date. The study's findings could have significant implications for the prognosis and treatment of OSCC patients.

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