<p>Research on prognostic factors for oral squamous cell carcinoma (OSCC) has revealed new therapeutic targets, with angiogenesis playing a key role in tumor development, invasion, and prognosis. However, reports on OSCC prognostic prediction construction based on angiogenesis factors are limited. Through bioinformatics analysis, we aimed to identify angiogenesis factors whose expression changes may be linked to OSCC prognosis. RNA sequencing, clinical data, and angiogenesis factor data were obtained from The Cancer Genome Atlas and Molecular Signatures Database. The characterized gene was selected and analyzed for correlations with clinicopathological features, prognosis, and cancer-associated fibroblasts infiltration using various databases. Further analyses included gene mutation, functional enrichment, and validation using clinical OSCC samples and tumor-bearing nude mice. Gene expression was assessed by western blotting, immunohistochemistry, immunofluorescence, and quantitative reverse transcription polymerase chain reaction. Epidermal growth factor (<i>EGF</i>) emerged as a key gene, showing significant upregulation in OSCC tissues compared to normal oral mucosa. Univariate and multivariate Cox regression analyses confirmed that high EGF expression correlates with poor overall survival and serves as an independent prognostic factor. EGF was also linked to cancer-associated fibroblast infiltration and can influence angiogenesis pathways. Our findings indicate that EGF may serve as a prognostic biomarker and potential therapeutic target for OSCC.</p>

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Integrated bioinformatics approaches and expression assays identified a potential prognostic biomarker in oral squamous cell carcinoma

  • Li He,
  • Lijuan Shi,
  • Jian Wei,
  • Yiwen Xu,
  • Minhai Nie,
  • Chunhui Li,
  • Xuqian Liu

摘要

Research on prognostic factors for oral squamous cell carcinoma (OSCC) has revealed new therapeutic targets, with angiogenesis playing a key role in tumor development, invasion, and prognosis. However, reports on OSCC prognostic prediction construction based on angiogenesis factors are limited. Through bioinformatics analysis, we aimed to identify angiogenesis factors whose expression changes may be linked to OSCC prognosis. RNA sequencing, clinical data, and angiogenesis factor data were obtained from The Cancer Genome Atlas and Molecular Signatures Database. The characterized gene was selected and analyzed for correlations with clinicopathological features, prognosis, and cancer-associated fibroblasts infiltration using various databases. Further analyses included gene mutation, functional enrichment, and validation using clinical OSCC samples and tumor-bearing nude mice. Gene expression was assessed by western blotting, immunohistochemistry, immunofluorescence, and quantitative reverse transcription polymerase chain reaction. Epidermal growth factor (EGF) emerged as a key gene, showing significant upregulation in OSCC tissues compared to normal oral mucosa. Univariate and multivariate Cox regression analyses confirmed that high EGF expression correlates with poor overall survival and serves as an independent prognostic factor. EGF was also linked to cancer-associated fibroblast infiltration and can influence angiogenesis pathways. Our findings indicate that EGF may serve as a prognostic biomarker and potential therapeutic target for OSCC.