LINC00839, LINC01671, AC093673 and AC008760 are Associated with the Prognosis and Immune Infiltration of Clear-cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer, and it is a significant global health problem causing significant morbidity and mortality. Long noncoding RNAs (lncRNAs) have been identified as a class of gene expression regulators that play a critical role in the immune system. However, the function of lncRNAs in the immune microenvironment of ccRCC remains unclear Long noncoding RNAs (lncRNAs) have been identified as a class of gene expression regulators that play a critical role in the immune system. The least absolute shrinkage and selection operator regression techniques, robust likelihoodbased survival modeling, and Cox regression analysis were used to identify potential prognostic lncRNAs. The relationship between the signature and the tumor's immune infiltration was analyzed using gene set enrichment analysis and the subset analysis of immune cells. LINC00839, LINC01671, AC093673, and AC008760 were selected to create a risk signature. For 3-, 5-, and 8-year overall survival rates, the areas under the receiver operating characteristic curves of the risk signature set were 0.689, 0.721, and 0.719 in the training set and 0.683, 0.686, and 0.665 in the validation set, respectively. A model and nomogram were constructed using the risk signature and clinical characteristics. The C-index of the model was 0.78 in the training set and 0.773 in the validation set. he relationship between the signature and the tumor's immune infiltration was analyzed using gene set enrichment analysis and the subset analysis of immune cells. A model and nomogram were constructed using the risk signature and clinical characteristics. The risk signature reflects the tumor's current immune infiltration and is associated with regulatory T cell differentiation, interleukin 17 production regulation, negative regulation of inflammatory response to an antigenic stimulus, and the IL6-JAK-STAT3 signaling pathway. This study provides prognostic information for ccRCC patients and may also serve as a useful clue for future immunotherapies. The study's first major strength was the use of stricter criteria (both sample and lncRNAs) to increase the precision of the findings and the model's efficiency. Simultaneously, a variety of calculation methods are used to ensure the validity of the results, including univariate/multivariate Cox regression, robust likelihood-based survival modeling, and LASSO regression analyses. Second, the immune-cell components of the samples were thoroughly analyzed (not just using immune scoring) in order to establish a more detailed relationship between tumor immune infiltration and risk signature. Thirdly, a visually recognizable nomogram of the model has been created for clinicians' ease of use. no avaiable