{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Chen B"],"funding":["the Social Development Foundation of Zhenjiang","National Natural Science Foundation of China","Natural Science Foundation of Hunan Province","Natural Science Foundation of Jiangsu Province"],"pagination":["545"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8525017"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["21(1)"],"pubmed_abstract":["<h4>Background</h4>Papillary renal cell carcinoma (pRCC) ranks second in renal cell carcinoma and the prognosis of pRCC remains poor. Here, we aimed to screen and identify a novel prognostic cancer-related lncRNA signature in pRCC.<h4>Methods</h4>The RNA-seq profile and clinical feature of pRCC cases were downloaded from TCGA database. Significant cancer-related lncRNAs were obtained from the Immlnc database. Differentially expressed cancer-related lncRNAs (DECRLs) in pRCC were screened for further analysis. Cox regression report was implemented to identify prognostic cancer-related lncRNAs and establish a prognostic risk model, and ROC curve analysis was used to evaluate its precision. The correlation between RP11-63A11.1 and clinical characteristics was further analyzed. Finally, the exp"],"journal":["Cancer cell international"],"pubmed_title":["A novel prognostic cancer-related lncRNA signature in papillary renal cell carcinoma."],"pmcid":["PMC8525017"],"funding_grant_id":["2019JJ40269","SH2021033","BK20211123","81402100"],"pubmed_authors":["Dong D","Zou Y","Hu W","Yao Q","Chen B"],"additional_accession":[]},"is_claimable":false,"name":"A novel prognostic cancer-related lncRNA signature in papillary renal cell carcinoma.","description":"<h4>Background</h4>Papillary renal cell carcinoma (pRCC) ranks second in renal cell carcinoma and the prognosis of pRCC remains poor. Here, we aimed to screen and identify a novel prognostic cancer-related lncRNA signature in pRCC.<h4>Methods</h4>The RNA-seq profile and clinical feature of pRCC cases were downloaded from TCGA database. Significant cancer-related lncRNAs were obtained from the Immlnc database. Differentially expressed cancer-related lncRNAs (DECRLs) in pRCC were screened for further analysis. Cox regression report was implemented to identify prognostic cancer-related lncRNAs and establish a prognostic risk model, and ROC curve analysis was used to evaluate its precision. The correlation between RP11-63A11.1 and clinical characteristics was further analyzed. Finally, the exp","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Oct","modification":"2025-04-22T11:27:39.79Z","creation":"2025-04-05T23:56:02.581Z"},"accession":"S-EPMC8525017","cross_references":{"pubmed":["34663322"],"doi":["10.1186/s12935-021-02247-6"]}}