<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>16(1)</volume><submitter>Wang C</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>CD4&lt;sup>+&lt;/sup> T cells, as critical mediators of immune regulation, have not been fully elucidated in their role in hepatocellular carcinoma (HCC) immune evasion.&lt;h4>Methods&lt;/h4>We analyzed single-cell RNA sequencing (scRNA-seq) data from 16 HCC patients (GSE149614). Cell types were annotated based on cluster-specific differentially expressed genes (DEGs), utilizing the SingleR and PISCES for automated cell type assignment, with reference to established markers from previous studies. Metabolic reprogramming, transcriptional networks, and intercellular communication were assessed via GSVA, SCENIC, and CellChat. A prognostic model integrating TCGA-LIHC and validated in GSE109211 was developed using LASSO Cox regression. Molecular docking and dynamics simulations evaluated</pubmed_abstract><journal>Discover oncology</journal><pagination>1704</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12463779</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Identification of immunosuppressive CD4&amp;lt;sup&amp;gt;+&amp;lt;/sup&amp;gt; T-cell subtype and construction of prognostic model for hepatocellular carcinoma.</pubmed_title><pmcid>PMC12463779</pmcid><pubmed_authors>Tian F</pubmed_authors><pubmed_authors>Wang C</pubmed_authors><pubmed_authors>Lou Y</pubmed_authors><pubmed_authors>Zhou T</pubmed_authors><pubmed_authors>Zhang L</pubmed_authors><pubmed_authors>Li L</pubmed_authors></additional><is_claimable>false</is_claimable><name>Identification of immunosuppressive CD4&amp;lt;sup&amp;gt;+&amp;lt;/sup&amp;gt; T-cell subtype and construction of prognostic model for hepatocellular carcinoma.</name><description>&lt;h4>Background&lt;/h4>CD4&lt;sup>+&lt;/sup> T cells, as critical mediators of immune regulation, have not been fully elucidated in their role in hepatocellular carcinoma (HCC) immune evasion.&lt;h4>Methods&lt;/h4>We analyzed single-cell RNA sequencing (scRNA-seq) data from 16 HCC patients (GSE149614). Cell types were annotated based on cluster-specific differentially expressed genes (DEGs), utilizing the SingleR and PISCES for automated cell type assignment, with reference to established markers from previous studies. Metabolic reprogramming, transcriptional networks, and intercellular communication were assessed via GSVA, SCENIC, and CellChat. A prognostic model integrating TCGA-LIHC and validated in GSE109211 was developed using LASSO Cox regression. Molecular docking and dynamics simulations evaluated</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Sep</publication><modification>2026-06-03T20:25:17.02Z</modification><creation>2026-05-01T03:10:28.195Z</creation></dates><accession>S-EPMC12463779</accession><cross_references><pubmed>40996677</pubmed><doi>10.1007/s12672-025-03556-2</doi></cross_references></HashMap>