<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>25(1)</volume><submitter>Yao Y</submitter><funding>Project of Science and Technology of Hunan Province</funding><pubmed_abstract>This study aims to identify the cancer-associated fibroblasts (CAF)-related genes that can affect immunotherapy and drug sensitivity in hepatocellular carcinoma (HCC). Expression data and survival data associated with HCC were obtained in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted correlation network analysis (WGCNA) analysis was performed to obtain CAF-related genes. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for regression analysis and risk models. Subsequently, Gene Set Enrichment Analysis (GSEA) analysis, Gene Set Enrichment Analysis (ssGSEA) analysis, Tumor Immune Dysfunction and Exclusion (TIDE) analysis and drug sensitivity analysis were performed on the risk models. Survival analysis of CAF scores showed tha</pubmed_abstract><journal>Genes and immunity</journal><pagination>55-65</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10873201</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Prediction of CAF-related genes in immunotherapy and drug sensitivity in hepatocellular carcinoma: a multi-database analysis.</pubmed_title><pmcid>PMC10873201</pmcid><pubmed_authors>Yao Y</pubmed_authors><pubmed_authors>Wang Q</pubmed_authors><pubmed_authors>Zhu Z</pubmed_authors><pubmed_authors>Li S</pubmed_authors><pubmed_authors>Yang K</pubmed_authors><pubmed_authors>Tang C</pubmed_authors><pubmed_authors>Li B</pubmed_authors><pubmed_authors>Feng B</pubmed_authors></additional><is_claimable>false</is_claimable><name>Prediction of CAF-related genes in immunotherapy and drug sensitivity in hepatocellular carcinoma: a multi-database analysis.</name><description>This study aims to identify the cancer-associated fibroblasts (CAF)-related genes that can affect immunotherapy and drug sensitivity in hepatocellular carcinoma (HCC). Expression data and survival data associated with HCC were obtained in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted correlation network analysis (WGCNA) analysis was performed to obtain CAF-related genes. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for regression analysis and risk models. Subsequently, Gene Set Enrichment Analysis (GSEA) analysis, Gene Set Enrichment Analysis (ssGSEA) analysis, Tumor Immune Dysfunction and Exclusion (TIDE) analysis and drug sensitivity analysis were performed on the risk models. Survival analysis of CAF scores showed tha</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Feb</publication><modification>2026-06-03T03:51:34.081Z</modification><creation>2024-11-09T07:42:31.2Z</creation></dates><accession>S-EPMC10873201</accession><cross_references><pubmed>38233508</pubmed><doi>10.1038/s41435-024-00252-z</doi></cross_references></HashMap>