Integrated network analysis and experimental validation identify CCNA2, CD44, and STAT1 as clinically relevant hub genes in oral squamous cell carcinoma

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Authors: Mingyang Bu, Yue Gu, Yuhan Meng, Yunyi Cui, Qianli Wu, Yali Kong, Haoyang Liu, Yi Chen, Jiajun Zhang, Lizhen Guo, Y Yang, Dongyang Huang
+1 more Zhe Ma
Cited by: 0
References: 35

Abstract

Oral squamous cell carcinoma remains a major clinical challenge, with only marginal gains in long-term survival due to frequent recurrence, lymphatic dissemination and therapeutic resistance. Robust and biologically grounded molecular determinants are needed to improve tumor characterization and facilitate translational advances. Transcriptomic profiles from GSE30784, GSE9844 and TCGA-HNSC were integrated to identify reproducible dysregulated genes, followed by construction of a high-confidence PPI network for hub gene prioritization. Prognostic and diagnostic relevance was assessed using Kaplan-Meier, Cox regression and ROC analyses. Experimental validation was performed by immunohistochemistry in human OSCC tissues and by qPCR in OSCC cell lines. Cross-cohort integration yielded a reproducible set of DEGs, from which CCNA2, CD44 and STAT1 emerged as network-defined hub genes. All three genes were consistently upregulated across independent cohorts and showed significant prognostic and diagnostic associations. Functional enrichment indicated that these genes are embedded in proliferation-, adhesion- and stress-response-related signaling programs. Experimental assays further confirmed their elevated expression at both transcript and protein levels in OSCC tissues and cell models. CCNA2, CD44 and STAT1 constitute reproducible and functionally anchored hub genes in OSCC, carrying both diagnostic and prognostic implications. These findings substantially refine the molecular understanding of OSCC and provide rational entry points for subsequent mechanistic and translational investigations.

Fields of Study & Subjects

Head and Neck Cancer Studies Bioinformatics and Genomic Networks Cancer-related molecular mechanisms research

Publication details

Journal / source
Frontiers in Molecular Biosciences
Volume
13
Pages
1748821–1748821
Publication date
9 February 2026
Language
EN