<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>10(17)</volume><submitter>Lin P</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>Head and neck squamous cell carcinoma (HNSC) is the 7th most common type of cancer in the world. Through the advantages of The Cancer Genome Atlas (TCGA) large-scale sequencing-based genome analysis technology, we can explore the potential molecular mechanisms that can improve the prognosis of HNSC patients.&lt;h4>Methods&lt;/h4>The HNSC transcriptome and clinical data were downloaded from TCGA database. A univariate survival analysis and differential expression analysis were conducted to obtain the intersection gene set. A protein-protein interaction (PPI) analysis, modular analysis, and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis were then conducted to identify the hub genes. Clinical correlation analysis, univariate and m</pubmed_abstract><journal>Annals of translational medicine</journal><pagination>923</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9511182</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Prognostic value of CD247 in patients with head and neck squamous cell carcinoma: bioinformatic analysis of TCGA database.</pubmed_title><pmcid>PMC9511182</pmcid><pubmed_authors>Lin P</pubmed_authors><pubmed_authors>Ding Y</pubmed_authors><pubmed_authors>Wang QY</pubmed_authors><pubmed_authors>Liu MY</pubmed_authors><pubmed_authors>Ye JC</pubmed_authors><pubmed_authors>Hu XL</pubmed_authors><pubmed_authors>Hu YY</pubmed_authors></additional><is_claimable>false</is_claimable><name>Prognostic value of CD247 in patients with head and neck squamous cell carcinoma: bioinformatic analysis of TCGA database.</name><description>&lt;h4>Background&lt;/h4>Head and neck squamous cell carcinoma (HNSC) is the 7th most common type of cancer in the world. Through the advantages of The Cancer Genome Atlas (TCGA) large-scale sequencing-based genome analysis technology, we can explore the potential molecular mechanisms that can improve the prognosis of HNSC patients.&lt;h4>Methods&lt;/h4>The HNSC transcriptome and clinical data were downloaded from TCGA database. A univariate survival analysis and differential expression analysis were conducted to obtain the intersection gene set. A protein-protein interaction (PPI) analysis, modular analysis, and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis were then conducted to identify the hub genes. Clinical correlation analysis, univariate and m</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Sep</publication><modification>2026-05-28T01:09:25.347Z</modification><creation>2025-04-19T22:48:55.221Z</creation></dates><accession>S-EPMC9511182</accession><cross_references><pubmed>36172089</pubmed><doi>10.21037/atm-22-1143</doi></cross_references></HashMap>