What question did this study set out to answer?

This study aims to identify molecular features that indicate the risk of progression in oral cavity squamous cell carcinoma.

Multiomic Signatures in Oral Cancer Progression

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Analysis uncovers biomarkers for early identification of higher-risk lesions in oral cancer progression.

This study aims to identify molecular features that indicate the risk of progression in oral cavity squamous cell carcinoma.
Applied integrated multiomics approach to analyze oral tissues and blood samples.
Performed whole-genome and RNA sequencing to identify mutations and expression differences.
Used machine learning for feature evaluation and classifier training on gene expression data.
Conducted differential methylation analysis to assess epigenomic changes in OED and OSCC samples.
Identified shared mutational alterations in key genes between premalignant and malignant groups.
Achieved a classifier model with 92% confidence and 96% AUC for risk assessment.
Detected increased CpG island methylation and differential expression in OSCC samples.
Found specific informative features linked to cancer progression, aiding early identification strategies.

Lei et al. (2026) studied this question.

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