ArticleCancer cell international2021
Identification of key genes for HNSCC from public databases using bioinformatics analysis.
Article in Cancer cell international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Integrated bioinformatics approaches and expression assays identified a potential prognostic biomarker in oral squamous cell carcinoma.Scientific reports · 2026Article
- Large scale plasma proteomic profiles improve prediction of idiopathic pulmonary fibrosis in general population.Respiratory research · 2025Article
- Transcriptomic insights into GSDME-driven pyroptosis in head and neck cancer.Scientific reports · 2025Article
- [CEACAM6 inhibits proliferation and migration of nasopharyngeal carcinoma cells by suppressing epithelial-mesenchymal transition].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2025Article
- Unveiling Biomarkers in Head and Neck Squamous Cell Carcinoma through Bioinformatics: The Role ofInternational journal of molecular sciences · 2024Article
- Exploring gene regulatory interaction networks and predicting therapeutic molecules for hypopharyngeal cancer and EGFR-mutated lung adenocarcinoma.FEBS open bio · 2024Article
- The emerging roles of CEACAM6 in human cancer (Review).International journal of oncology · 2024Review
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe cause and underlying molecular mechanisms of head and neck squamous cell carcinoma (HNSCC) are unclear. Our study aims to identify the key genes associated with HNSCC and reveal potential biomarkers.
methodsIn this study, the expression profile dataset GSE83519 of the Gene Expression Omnibus database and the RNA sequencing dataset of HNSCC of The Cancer Genome Atlas were included for analysis. Sixteen differentially expressed genes were screened from these two datasets using R software. Gene Expression Profiling Interactive Analysis 2 (GEPIA2) was then adopted for survival analysis, and finally, three key genes related to the overall survival of HNSCC patients were identified. Furthermore, we verified these three genes using the Oncomine database and from real-time PCR and immunohistochemistry results from HNSCC tissues.
resultsThe expression data of 44 samples from GSE83519 and 545 samples from TCGA-HNSC were collected. Using bioinformatics, the two databases were integrated, and 16 DEGs were screened out. Gene Ontology (GO) enrichment analysis showed that the biological functions of DEGs focused primarily on the apical plasma membrane and regulation of anoikis. Kyoto Encyclopedia of Genes and Genomes (KEGG) signalling pathway analysis showed that these DEGs were mainly involved in drug metabolism-cytochrome P450 and serotonergic synapses. Survival analysis identified three key genes, CEACAM5, CEACAM6 and CLCA4, that were closely related to HNSCC prognosis. The Oncomine database, qRT-PCR and IHC verified that all 3 key genes were downregulated in most HNSCC tissues compared to adjacent normal tissues.
conclusionsThis study indicates that integrated bioinformatics analyses play an important role in screening for differentially expressed genes and pathways in HNSCC, helping us better understand the biomarkers and molecular mechanism of HNSCC.
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