{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["12(11)"],"submitter":["Lou S"],"funding":["The authors received no specific funding for this work."],"pubmed_abstract":["<h4>Background</h4>Cervical cancer is one of the most common malignancies among women. Vesicle-mediated transport mechanisms significantly influence tumor cell behavior through intercellular material exchange. However, prognostic significance in CC patients remains underexplored.<h4>Research design and methods</h4>We identified differentially expressed vesicle-mediated transport-related genes from TCGA and GeneCards datasets through differential expression analysis. We constructed a prognostic model using Cox regression and LASSO regression, categorized patients into high- and low-risk groups, and validated the model in the GEO data set. A nomogram integrating clinical features and risk scores demonstrated the model's independent prognostic capability. We analyzed tumor immune cell infiltr"],"journal":["Immunity, inflammation and disease"],"pagination":["e70052"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11544644"],"repository":["biostudies-literature"],"pubmed_title":["Identification of Vesicle-Mediated Transport-Related Genes for Predicting Prognosis, Immunotherapy Response, and Drug Screening in Cervical Cancer."],"pmcid":["PMC11544644"],"pubmed_authors":["Lou S","Lv H","Zhang L"],"additional_accession":[]},"is_claimable":false,"name":"Identification of Vesicle-Mediated Transport-Related Genes for Predicting Prognosis, Immunotherapy Response, and Drug Screening in Cervical Cancer.","description":"<h4>Background</h4>Cervical cancer is one of the most common malignancies among women. Vesicle-mediated transport mechanisms significantly influence tumor cell behavior through intercellular material exchange. However, prognostic significance in CC patients remains underexplored.<h4>Research design and methods</h4>We identified differentially expressed vesicle-mediated transport-related genes from TCGA and GeneCards datasets through differential expression analysis. We constructed a prognostic model using Cox regression and LASSO regression, categorized patients into high- and low-risk groups, and validated the model in the GEO data set. A nomogram integrating clinical features and risk scores demonstrated the model's independent prognostic capability. We analyzed tumor immune cell infiltr","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Nov","modification":"2026-07-15T09:38:15.178Z","creation":"2025-04-06T10:13:45.213Z"},"accession":"S-EPMC11544644","cross_references":{"pubmed":["39513664"],"doi":["10.1002/iid3.70052"]}}