Deciphering oral cancer subtypes: Integrating differential gene expression and pathway analysis followed by non-negative matrix factorization transcription analysis

Abstract

Oral cancer is a major public health concern around the globe, and its classification relies on factors such as habitual status and tumor stages. However, a significant gap exists in understanding oral cancer patients' molecular and genomic characteristics. This study aims to bridge this gap by analyzing International Cancer Genome Consortium (ICGC's) oral cancer data, which identified 2270 differentially expressed genes related to oral cancer. We employed pathway enrichment analysis, highlighting key pathways including hypoxia, VEGF, PI3K, and TGF-β, and STAT2, E2F4, and SP1 transcription factors enriched in tumor samples compared to normal samples. Moreover, we utilized a non-negative matrix factorization (NMF) technique for unsupervised subtype discovery and identified three distinct tumor subgroups. Each subgroup exhibited unique molecular profiles, with pathways related to TNF-α, NF-κB, and hypoxia enriched across all groups. Notably, transcription factor analysis revealed crucial differences: subgroup A was enriched in EGR1, TP53, and HIF1A; subgroup B showed high levels of CDX2 and HNF4A; while subgroup C was characterized by enrichment in ATF4 and E2F4. These findings suggest the feasibility of classifying oral squamous cell carcinoma (OSCC) patients based on gene expression profiles, laying a foundational framework for future research aimed at personalized treatment strategies.