{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["16(14)"],"submitter":["Yang HS"],"pubmed_abstract":["<b>Background</b>: Patients with \"driver gene-negative\" LUAD lack effective targeted therapies. This study aimed to elucidate the role of the glycolysis pathway in driver gene-negative LUAD to identify key genes and potential therapeutic targets. <b>Methods</b>: Bulk RNA sequencing data from 49 patients with driver gene-negative LUAD were analyzed. The driver gene-negative status of patients was confirmed by immunoblotting. Gene set enrichment analysis (GSEA) was conducted on six hallmark pathways related to glycolysis. Additionally, key genes were identified and a risk score model was constructed. Finally, single-cell RNA sequencing data were processed using the Seurat package for data cleaning, dimensionality reduction clustering, and cell type identification. <b>Results</b>: GSEA analys"],"journal":["Journal of Cancer"],"pagination":["4233-4244"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12595263"],"repository":["biostudies-literature"],"pubmed_title":["Exploring the Glycolytic Mechanisms in \"Driver Gene-Negative\" Lung Adenocarcinoma (LUAD): A Single-Cell RNA Sequencing Approach to Identify the MIF-HIF-1α Axis."],"pmcid":["PMC12595263"],"pubmed_authors":["Chen Q","Liang CY","Yang HS","Zhang J","Han Y","Zhu W","Yu QD","Li YH","Luo HH"],"additional_accession":[]},"is_claimable":false,"name":"Exploring the Glycolytic Mechanisms in \"Driver Gene-Negative\" Lung Adenocarcinoma (LUAD): A Single-Cell RNA Sequencing Approach to Identify the MIF-HIF-1α Axis.","description":"<b>Background</b>: Patients with \"driver gene-negative\" LUAD lack effective targeted therapies. This study aimed to elucidate the role of the glycolysis pathway in driver gene-negative LUAD to identify key genes and potential therapeutic targets. <b>Methods</b>: Bulk RNA sequencing data from 49 patients with driver gene-negative LUAD were analyzed. The driver gene-negative status of patients was confirmed by immunoblotting. Gene set enrichment analysis (GSEA) was conducted on six hallmark pathways related to glycolysis. Additionally, key genes were identified and a risk score model was constructed. Finally, single-cell RNA sequencing data were processed using the Seurat package for data cleaning, dimensionality reduction clustering, and cell type identification. <b>Results</b>: GSEA analys","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025","modification":"2026-06-05T12:45:44.384Z","creation":"2026-05-17T03:07:45.066Z"},"accession":"S-EPMC12595263","cross_references":{"pubmed":["41210694"],"doi":["10.7150/jca.119149"]}}