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 ... -  《-》

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 cellular senescence-related genes in the prognosis, tumor microenvironment, and immunotherapy/chemotherapy of clear cell renal cell carcinoma.

The transcriptome public database and advances in biological discoveries contributed to significant progresses in identifying the drivers of cancer progression. Cellular senescence (CS) is considered as a leading factor resulting in cancer development. The purpose of this study was to explore the significance of CS-related genes in the molecular classification and survival outcome of clear cell renal cell carcinoma (ccRCC). CS-related genes were obtained from the CellAge database, and patients from TCGA-KIRC dataset and ICGC dataset were clustered by ConsesusClusterPlus. The characteristics of overall survival (OS), genomic variation, and tumor microenvironment (TME) of each cluster were analyzed. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was conducted to develop a CS-related risk model to score ccRCC patients and assess the risk scores in predicting patients' response to immunotherapy and chemotherapy. A nomogram based on the risk model was established to improve the risk stratification of patients. CcRCC was divided into three molecular subtypes based on CS-related genes. The three molecular phenotypes showed different OS and clinical manifestations, mutation patterns, and TME states. Five genes were obtained from nine differentially expressed CS-related genes in the three molecular subtypes to develop a risk model. Patients with ccRCC were divided into high- and low-risk subgroups. The former showed an unfavorable OS, with a significantly higher genomic variation rate, TME score, and numerous immune checkpoint expressions when compared to the low-risk subgroup. Risk score reflected the response of patients to axitinib, bortezomib, sorafenib, sunitinib, and temsirolimus. In general, CS-related genes divided ccRCC into three molecular subtypes with distinct OS, mutation patterns, and TME states. The risk model based on the five CS-related genes can predict the prognosis and therapeutic outcome of ccRCC patients, providing a theoretical basis for further study on the molecular mechanism of CS-related ccRCC.

Lu C ，Wang Y ，Nie L ，Chen L ，Li M ，Qing H ，Li S ，Wu S ，Wang Z ... -  《Frontiers in Immunology》

Cuproptosis-related modification patterns depict the tumor microenvironment, precision immunotherapy, and prognosis of kidney renal clear cell carcinoma.

Due to the different infiltration abundance of immune cells in tumor, the efficacy of immunotherapy varies widely among individuals. Recently, growing evidence suggested that cuproptosis has impact on cancer immunity profoundly. However, the comprehensive roles of cuproptosis-related genes in tumor microenvironment (TME) and in response to immunotherapy are still unclear. Based on 43 cuproptosis-related genes, we employed unsupervised clustering to identify cuproptosis-related patterns and single-sample gene set enrichment analysis algorithm to build a cuproptosis signature for individual patient's immune cell infiltration and efficacy of immune checkpoint blockade (ICB) evaluation. Then, the cuproptosis-related genes were narrowed down using univariate Cox regression model and least absolute shrinkage and selection operator algorithm. Finally, a cuproptosis risk score was built by random survival forest based on these narrowed-down genes. Two distinct cuproptosis-related patterns were developed, with cuproptosis cluster 1 showing better prognosis and higher enrichment of immune-related pathways and infiltration of immune cells. For individual evaluation, the cuproptosis signature that we built could be used not only for predicting immune cell infiltration in TME but also for evaluating an individual's sensitivity to ICBs. Patients with higher cuproptosis signature scores exhibited more activated cancer immune processes, higher immune cell infiltration, and better curative efficacy of ICBs. Furthermore, a robust cuproptosis risk score indicated that patients with higher risk scores showed worse survival outcomes, which could be validated in internal and external validation cohorts. Ultimately, a nomogram which combined the risk score with the prognostic clinical factors was developed, and it showed excellent prediction accuracy for survival outcomes. Distinct cuproptosis-related patterns have significant differences on prognosis and immune cell infiltration in kidney renal clear cell carcinoma (KIRC). Cuproptosis signature and risk score are able to provide guidance for precision therapy and accurate prognosis prediction for patients with KIRC.

Cai Z ，He Y ，Yu Z ，Hu J ，Xiao Z ，Zu X ，Li Z ，Li H ... -  《Frontiers in Immunology》

Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common renal malignancy, although newly developing targeted therapy and immunotherapy have been showing promising effects in clinical treatment, the effective biomarkers for immune response prediction are still lacking. The study is to construct a gene signature according to ccRCC immune cells infiltration landscape, thus aiding clinical prediction of patients response to immunotherapy. Firstly, ccRCC transcriptome expression profiles from Gene Expression Omnibus (GEO) database as well as immune related genes information from IMMPORT database were combine applied to identify the differently expressed meanwhile immune related candidate genes in ccRCC comparing to normal control samples. Then, based on protein-protein interaction network (PPI) and following module analysis of the candidate genes, a hub gene cluster was further identified for survival analysis. Further, LASSO analysis was applied to construct a signature which was in succession assessed with Kaplan-Meier survival, Cox regression and ROC curve analysis. Moreover, ccRCC patients were divided as high and low-risk groups based on the gene signature followed by the difference estimation of immune treatment response and exploration of related immune cells infiltration by TIDE and Cibersort analysis respectively among the two groups of patients. Based on GEO and IMMPORT databases, a total of 269 differently expressed meanwhile immune related genes in ccRCC were identified, further PPI network and module analysis of the 269 genes highlighted a 46 genes cluster. Next step, Kaplan-Meier and Cox regression analysis of the 46 genes identified 4 genes that were supported to be independent prognosis indicators, and a gene signature was constructed based on the 4 genes. Furthermore, after assessing its prognosis indicating ability by both Kaplan-Meier and Cox regression analysis, immune relation of the signature was evaluated including its association with environment immune score, Immune checkpoint inhibitors expression as well as immune cells infiltration. Together, immune predicting ability of the signature was preliminary explored. Based on ccRCC genes expression profiles and multiple bioinformatic analysis, a 4 genes containing signature was constructed and the immune regulation of the signature was preliminary explored. Although more detailed experiments and clinical trials are needed before potential clinical use of the signature, the results shall provide meaningful insight into further ccRCC immune researches.

Gui Z ，Du J ，Wu N ，Shen N ，Yang Z ，Yang H ，Wang X ，Zhao N ，Zeng Z ，Wei R ，Ma W ，Wang C ... -  《BMC CANCER》