biostudies-literatureUnknown13Qu GNatural Science Foundation of Hunan Province<b>Objective:</b> In order to predict the prognosis in patients with clear cell renal cell carcinoma (ccRCC) so as to understand cancer lipid metabolism and sensitivity to immune-targeting drugs, model algorithms were used to establish a risk coefficient model of long non-coding RNAs (lncRNAs) associated with lipid metabolism. <b>Methods:</b> The transcriptome data were retrieved from TCGA, and lncRNAs associated with lipid metabolism were obtained through Pearson correlation and differential expression analyses. Differentially expressed lipid metabolism-related lncRNAs and lipid metabolism-related lncRNA pairs were obtained using the R language software. The minimum absolute shrinkage method and the selector operation regression method were used to construct the model and draw the receiveFrontiers in genetics1040421https://www.ebi.ac.uk/biostudies/studies/S-EPMC9845405biostudies-literaturePrognostic prediction of clear cell renal cell carcinoma based on lipid metabolism-related lncRNA risk coefficient model.PMC9845405Yang GLiu LYi LTang CQu GChen DXu YfalsePrognostic prediction of clear cell renal cell carcinoma based on lipid metabolism-related lncRNA risk coefficient model.<b>Objective:</b> In order to predict the prognosis in patients with clear cell renal cell carcinoma (ccRCC) so as to understand cancer lipid metabolism and sensitivity to immune-targeting drugs, model algorithms were used to establish a risk coefficient model of long non-coding RNAs (lncRNAs) associated with lipid metabolism. <b>Methods:</b> The transcriptome data were retrieved from TCGA, and lncRNAs associated with lipid metabolism were obtained through Pearson correlation and differential expression analyses. Differentially expressed lipid metabolism-related lncRNAs and lipid metabolism-related lncRNA pairs were obtained using the R language software. The minimum absolute shrinkage method and the selector operation regression method were used to construct the model and draw the receive2022-01-01T00:00:00Z20222025-04-04T13:52:57.788Z2025-04-04T13:52:57.788ZS-EPMC98454053668588210.3389/fgene.2022.1040421