Research Paper Volume 16, Issue 16 pp 11955—11969
Comprehensive multi-omics analysis reveals a combination of lncRNAs that synergistically regulate glycolysis and immunotherapeutic effects in renal clear cell carcinoma
- 1 Department of Urology, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China
Received: February 21, 2024 Accepted: July 17, 2024 Published: August 19, 2024
https://doi.org/10.18632/aging.206069How to Cite
Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background: Clear cell renal carcinoma is a common urological malignancy with poor prognosis and treatment outcomes. lncRNAs are important in metabolic reprogramming and the tumor immune microenvironment, but their role in clear cell renal carcinoma is unclear.
Methods: Renal clear cell carcinoma sample data from The Cancer Genome Atlas was used to establish a new risk profile by glycolysis-associated lncRNAs via machine learning. Risk profile-associated column-line plots were constructed to provide a quantitative tool for clinical practice. Patients with renal clear cell carcinoma were divided into high- and low-risk groups. Clinical features, tumor immune microenvironments, and immunotherapy responses were systematically analyzed. We experimentally confirmed the role of LINC01138 and LINC01605 in renal clear cell carcinoma.
Results: The risk profile, consisting of LUCAT1, LINC01138, LINC01605, and HOTAIR, reliably predicted survival in patients with renal clear cell carcinoma and was validated in multiple external datasets. The high-risk group presented higher levels of immune cell infiltration and better immunotherapy responses than the low-risk group. LINC01138 and LINC01605 knockdown inhibited the proliferation of renal clear cell carcinoma.
Conclusions: The identified risk profiles can accurately assess the prognosis of patients with clear cell renal carcinoma and identify patient populations that would benefit from immunotherapy, providing valuable insights and therapeutic targets for the clinical management of clear cell renal carcinoma.
Abbreviations
TCGA: The Cancer Genome Atlas; GEO: Gene Expression Omnibus; GTEx: Genotype-Tissue Expression Program; HR: Hazard Ratio; ROC: Receiver Operating Characteristic; PD-1: Programmed cell death 1; PD-L1: Programmed cell death 1 ligand 1; CTLA4: Cytotoxic T-lymphocyte-associated protein 4; ICB: Immune checkpoint blockade; OS: Overall survival; ROC: Receiver Operation Characteristic; NES: Normalized enrichment score; TMB: Tumor mutation burden; IC50: half maximal inhibitory concentration; GDSC: Genomics of Drug Sensitivity in Cancer; PPI: protein–protein interaction; KM: Kaplan–Meier; ssGSEA: single-sample gene set enrichment analysis; TIDE: tumor immune dysfunction and exclusion; GSEA: gene set enrichment analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; PFS: Progression-free survival; DSS: Disease-free survival.