Identification of key genes for HNSCC from public databases using bioinformatics analysis

Area of Science:

• Oncology
• Genomics
• Bioinformatics

Background:

• Head and neck squamous cell carcinoma (HNSCC) etiology and molecular mechanisms remain largely unknown.
• Identifying key genes and potential biomarkers is crucial for understanding HNSCC development.

Purpose of the Study:

• To identify key genes associated with HNSCC.
• To reveal potential diagnostic and prognostic biomarkers for HNSCC.
• To elucidate the molecular mechanisms underlying HNSCC.

Main Methods:

• Integrated analysis of two large-scale datasets: GSE83519 and The Cancer Genome Atlas (TCGA) for HNSCC.
• Screening of differentially expressed genes (DEGs) using R software.
• Survival analysis using Gene Expression Profiling Interactive Analysis 2 (GEPIA2) to identify prognostic genes.
• Validation of key genes using Oncomine, qRT-PCR, and immunohistochemistry (IHC).

Main Results:

• 16 differentially expressed genes (DEGs) were identified by integrating HNSCC datasets.
• Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated DEGs involvement in apical plasma membrane, anoikis regulation, drug metabolism, and serotonergic pathways.
• Three key genes (CEACAM5, CEACAM6, CLCA4) were significantly associated with HNSCC patient prognosis.
• Validation confirmed downregulation of CEACAM5, CEACAM6, and CLCA4 in HNSCC tissues compared to normal tissues.

Conclusions:

• Integrated bioinformatics analysis is effective for identifying DEGs and pathways in HNSCC.
• CEACAM5, CEACAM6, and CLCA4 are potential biomarkers for HNSCC.
• These findings contribute to a better understanding of HNSCC molecular mechanisms and offer potential therapeutic targets.