Computational construction of TME-related lncRNAs signature for predicting prognosis and immunotherapy response in clear cell renal cell carcinoma.

The tumor microenvironment (TME) is closely related to clear cell renal cell carcinoma (ccRCC) prognosis, and immunotherapy response. In current study, comprehensive bio-informative analysis was adopted to construct a TME-related lncRNA signature for immune checkpoint inhibitors (ICIs) and targeted drug responses in ccRCC patients. The TME mRNAs were screened following the immune and stromal scores with the data from GSE15641, GSE29609, GSE36895, GSE46699, GSE53757, and The Cancer Genome Atlas (TCGA)-kidney renal clear cell carcinoma (KIRC). And the TME-related lncRNAs were recognized using correlation analysis. The TME-related lncRNAs prognostic model was constructed using the training dataset. Kaplan-Meier analysis, principal-component analysis, and time-dependent receiver operating characteristic were used to evaluate the risk model. The immune cell infiltration in TME was evaluated using the single-sample gene set enrichment analysis (ssGSEA), ESTIMATE, and microenvironment cell populations counter algorithm. The immunophenoscore (IPS) was used to assess the response to immunotherapy with the constructed model. In the current study, 364 TME-related lncRNAs were selected based on the integrated bioinformatical analysis. Six TME-related lncRNAs (LINC00460, LINC01094, AC008870.2, AC068792.1, and AC007637.1) were identified as the prognostic signature in the training dataset and subsequently verified in the testing and entire datasets. Patients in the high-risk group exhibited poor overall survival and disease-free survival than those in the low-risk group. The 1-, 3-, and 5-year areas under the curves of the prognostic signature in the entire dataset were 0.704, 0.683, and 0.750, respectively. The risk score independently predicted ccRCC survival based on univariate and multivariate Cox regression. GSEA analysis suggested that the high-risk group was concentrated on immune-related pathways. The high-risk group were characterized by high immune cell infiltration, high TMB and somatic mutation counters, high IPS-PD-1 + CTLA4 scores, and immune checkpoints expression upregulation, reflecting the higher ICIs response. The half inhibitory concentrations of sunitinib, temsirolimus, and rapamycin were low in the high-risk group. The TME-related lncRNAs signature constructed could reliably predict the prognosis and immunotherapy response and targeted ccRCC patients' therapy.

Zhou L ，Fang H ，Guo F ，Yin M ，Long H ，Weng G ... -  《-》

Comprehensive analysis of LD-related genes signature for predicting prognosis and immunotherapy response in clear cell renal cell carcinoma.

Jia Y ，Dong X ，Yang F ，Zhou L ，Long H ... -  《BMC Nephrology》

A novel necroptosis-related long noncoding RNA model for predicting clinical features, immune characteristics, and therapeutic response in clear cell renal cell carcinoma.

Necroptosis is an immune-related cell death pathway involved in the regulation of the tumor microenvironment (TME). Here, we aimed to explore the role of necroptosis in clear cell renal cell carcinoma (ccRCC) and construct a necroptosis-related lncRNA (NRL) model to assess its potential association with clinical characteristics and immune status. Gene expression profiles and clinical data for ccRCC patients were obtained from the Cancer Genome Atlas (TCGA). Pearson's correlation, univariate Cox, and least absolute shrinkage and selection operator analyses were used to develop an NRL model. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to determine the prognostic value of the NRL model. The clinical information was used to assess the diagnostic value of the NRL model. The TME, immune function, immune cell infiltration, and immune checkpoints associated with the NRL model risk score were studied using the ESTIMATE, GSEA, ssGSEA, and CIBERSORT algorithms. The immunophenoscore (IPS) and half-maximal inhibitory concentration (IC50) were used to compare the efficacies of immunotherapy and chemotherapy based on the NRL model. Finally, in vitro assays were performed to confirm the biological roles of NRLs. A total of 18 necroptosis-related genes and 285 NRLs in ccRCC were identified. A four-NRL model was constructed and showed good performance in the diagnosis and prognosis of ccRCC patients. The ESTIMATE scores, tumor mutation burden, and tumor stemness indices were significantly correlated with NRL model risk score. Immune functions such as chemokine receptors and immune receptor activity showed differences between different risk groups. The infiltration of immunosuppressive cells such as Tregs was higher in high-risk patients than in low-risk patients. High-risk patients were more sensitive to immunotherapy and some chemotherapy drugs, such as sunitinib and temsirolimus. Finally, the expression of NRLs included in the model was verified, and knocking down these NRLs in tumor cells affected cell proliferation, migration, and invasion. Necroptosis plays an important role in the progression of ccRCC. The NRL model we constructed can be used to predict the clinical characteristics and immune features of ccRCC patients.

Zhang L ，Chen Y ，Hu W ，Wu B ，Ye L ，Wang D ，Bai T ... -  《Frontiers in Immunology》

Novel immune-related signature based on immune cells for predicting prognosis and immunotherapy response in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common malignant tumor of the kidney and is characterized by poor prognosis. We sought to build an immune-related prognostic signature and investigate its relationship with immunotherapy response in ccRCC. Immune-related genes were identified by ssGSEA and WGCNA. The prognostic signature was conducted via univariate, least absolute shrinkage and selection operator, and multivariable Cox regression analyses. Kaplan-Meier analysis, PCA, t-SNE, and ROC were used to evaluate the risk model. A total of 119 immune-related genes associated with prognosis were screened out. Six immune-related genes (CSF1, CD5L, AIM2, TIMP3, IRF6, and HHLA2) were applied to construct a prognostic signature for KIRC. Kaplan-Meier analysis showed that patients in high-risk group had a poorer survival outcome than in low-risk group. The 1-, 3- and 5-year AUC of the prognostic signature was 0.754, 0.715, and 0.739, respectively. Univariate and multivariate Cox regression models demonstrated that the risk signature was an independent prognostic factor for KIRC survival. GSEA analysis suggested that the high-risk group was concentrated on immune-related pathways. The high-risk group with more regulatory T-cell infiltration showed a higher expression of immune negative regulation genes. The risk score had positively relationship with TIDE score and negatively with the response of immunotherapy. The IC50 values of axitinib, sunitinib, sorafenib, and temsirolimus were lower in the high-risk group. Our study defined a robust signature that may be promising for predicting clinical outcomes and immunotherapy and targeted therapy response in ccRCC patients.

Zhou L ，Fang H ，Yin M ，Long H ，Weng G ... -  《-》

Development of a novel disulfidptosis-related lncRNA signature for prognostic and immune response prediction in clear cell renal cell carcinoma.

Wang N ，Hu Y ，Wang S ，Xu Q ，Jiao X ，Wang Y ，Yan L ，Cao H ，Shao F ... -  《Scientific Reports》