A novel prognostic model based on immunogenomics for clear cell renal cell carcinoma.

Immune cell infiltration into tumor tissue is closely related to the clinical outcomes of patients with clear cell renal cell carcinoma (ccRCC). This study aimed to screen out potential immune genes associated with ccRCC, analyze their relationships with clinical outcomes, and construct a signature to predict ccRCC. The transcriptome RNA-sequencing data in 539 ccRCC and 72 adjacent normal tissues were obtained from TCGA database. Biomedical computational algorithms were conducted to identify immune-related differential expressed genes (IRDGs) and enriched pathways. Then, LASSO Cox and multivariate Cox analyses were performed to screen out genes that were then used to construct the prognostic model. A total of 116 down-regulated and 565 up-regulated IRDGs were identified. Pathway enrichment analysis suggested that IRDGs was mainly enriched in the pathway of "cytokines and cytokine receptors". The entire data of ccRCC were randomly divided into the training set and the test set with a ratio of 1:1. A 4-gene signature was then constructed using LASSO Cox analysis and multivariate Cox analysis in the training set. This prognostic signature could stratify patients into high- and low-risk groups successfully, and serve as an independent predictor when adjusted with clinical factors by univariate and multivariate Cox regression analysis. These results were verified in the test set and the entire set. Besides, the abundance of CD4 + T cells and dendritic cells increased in the high-risk group. Finally, we built a nomogram incorporating risk score and clinical factors to predict the overall survival of ccRCC patients. These findings may contribute to the research of ccRCC in immunization part.

Wu Z ，Shen Y ，Fan D ，Liu J ，Chen D ，Wang K ，Xu X ... -  《-》

Comprehensive Multi-Omics Identification of Interferon-γ Response Characteristics Reveals That RBCK1 Regulates the Immunosuppressive Microenvironment of Renal Cell Carcinoma.

Interferon-gamma (IFN-γ) has a complex role in modulating the tumor microenvironment (TME) during renal cell carcinoma (RCC) development. To define the role of IFN-γ response genes in RCC progression, we characterized the differential gene expression, prognostic implications, and DNA variation profiles of selected IFN-γ response signatures, which exhibited a significant hazard ratio for the overall survival (OS) and progression-free survival (PFS) of papillary, chromophobia, and clear cell RCC (ccRCC) patients (n = 944). Prognostic nomograms were constructed to predict the outcomes for ccRCC patients, highlighting the prognostic implications of RANBP2-type and C3HC4-type zinc finger containing 1 (RBCK1). Interestingly, large-scale pan-cancer samples (n = 12,521) and three single-cell RNA datasets revealed that RBCK1 showed markedly differential expression between cancer and normal tissues and significantly correlated with tumor-infiltrating immune cells, tumor purity, and immune checkpoint molecules, such as PD-L1, CTLA-4, LAG-3, and TIGIT in pan-cancer samples. Notably, the TIDE score was significantly higher in the RBCK1high group compared with the RBCK1low group in both ccRCC and RCC cohorts. Besides, immunohistochemistry staining showed significantly elevated RBCK1 expression in tumors (n = 50) compared with kidney samples (n = 40) from a real-world cohort, Fudan University Shanghai Cancer Center (FUSCC, Shanghai). After RBCK1 expression was confirmed in ccRCC, we found a significantly decreased number of infiltrating CD4+ T cells, CD4+ FOXP3+ Treg cells, M1 macrophages, and CD56bight/dim NK cells in the immune-cold RBCK1high group. In addition to the distinct heterogeneous immune microenvironment, the increased expression of RBCK1 predicted a prominently worse prognosis than the RBCK1low group for 232 ccRCC patients in the FUSCC proteomic cohort. Furthermore, after transfected with siRNA in human ccRCC cells, extraordinarily decreased cell proliferation, migration capacities, and prominently elevated apoptosis tumor cell proportion were found in the siRNA groups compared with the negative control group. In conclusion, this study identified IFN-γ response clusters, which might be used to improve the prognostic accuracy of immune contexture in the ccRCC microenvironment. Immune-cold RBCK1high patients have pro-tumorigenic immune infiltration and significantly worse outcomes than RBCK1low patients based on results from multi-omics to real-world data. Our discovery of novel independent prognostic indicators for RCC highlights the association between tumor alterations and immune phenotype.

Xu W ，Tao J ，Zhu W ，Liu W ，Anwaier A ，Tian X ，Su J ，Shi G ，Huang H ，Wei G ，Li C ，Qu Y ，Zhang H ，Ye D ... -  《Frontiers in Immunology》

A novel 10 glycolysis-related genes signature could predict overall survival for clear cell renal cell carcinoma.

Xing Q ，Zeng T ，Liu S ，Cheng H ，Ma L ，Wang Y ... -  《BMC CANCER》

Construction of a Novel Immune-Related lncRNA Pair Signature with Prognostic Significance for Kidney Clear Cell Renal Cell Carcinoma.

Renal cell carcinoma (RCC) is one of the most common aggressive malignant tumors in the urinary system, among which the clear cell renal cell carcinoma (ccRCC) is the most common subtype. The immune-related long noncoding ribonucleic acids (irlncRNAs) which are abundant in immune cells and immune microenvironment (IME) have potential significance in evaluating the prognosis and effects of immunotherapy. The signature based on irlncRNA pairs and independent of the exact expression level seems to have a latent predictive significance for the prognosis of patients with malignant tumors but has not been applied in ccRCC yet. In this article, we retrieved The Cancer Genome Atlas (TCGA) database for the transcriptome profiling data of the ccRCC and performed coexpression analysis between known immune-related genes (ir-genes) and lncRNAs to find differently expressed irlncRNA (DEirlncRNA). Then, we adopted a single-factor test and a modified LASSO regression analysis to screen out ideal DEirlncRNAs and constructed a Cox proportional hazard model. We have sifted 28 DEirlncRNA pairs, 12 of which were included in this model. Next, we compared the area under the curve (AUC), found the cutoff point by using the Akaike information criterion (AIC) value, and distinguished the patients with ccRCC into a high-risk group and a low-risk group using this value. Finally, we tested this model by investigating the relationship between risk score and survival, clinical pathological characteristics, cells in tumor immune microenvironment, chemotherapy, and targeted checkpoint biomarkers. A novel immune-related lncRNA pair signature consisting of 12 DEirlncRNA pairs was successfully constructed and tightly associated with overall survival, clinical pathological characteristics, cells in tumor immune microenvironment, and reactiveness to immunotherapy and chemotherapy in patients with ccRCC. Besides, the efficacy of this signature was verified in some commonly used clinicopathological subgroups and could serve as an independent prognostic factor in patients with ccRCC. This signature was proven to have a potential predictive significance for the prognosis of patients with ccRCC and the efficacy of immunotherapy.

Sun JX ，Xia QD ，Liu CQ ，Xu JZ ，Xun Y ，Lu JL ，Hu J ，Wang SG ... -  《-》

Exosome-related lncRNA score: A value-based individual treatment strategy for predicting the response to immunotherapy in clear cell renal cell carcinoma.

Exosomes play a crucial role in intercellular communication in clear cell renal cell carcinoma (ccRCC), while the long non-coding RNAs (lncRNAs) are implicated in tumorigenesis and progression. The purpose of this study is to construction a exosomes-related lncRNA score and a ceRNA network to predict the response to immunotherapy and potential targeted drug in ccRCC. Data of ccRCC patients were obtained from the TCGA database. Pearson correlation analysis was used to identify eExosomes-related lncRNAs (ERLRs) from Top10 exosomes-related genes that have been screened. The entire cohort was randomly divided into a training cohort and a validation cohort in equal scale. LASSO regression and multivariate cox regression was used to construct the ERLRs-based score. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and drug susceptibility between the high- and low-risk groups were also investigated. Finally, the relevant ceRNA network was constructed by machine learning to analyze their potential targets in immunotherapy and drug use of ccRCC patients. A score consisting of 4ERLRs was identified, and patients with higher ERLRs-based score tended to have a worse prognosis than those with lower ERLRs-based score. ROC curves and multivariate Cox regression analysis demonstrated that the score could be considered as a risk factor for prognosis in both training and validation cohorts. Moreover, patients with high scores are predisposed to experience poor overall survival, a larger prevalence of advanced stage (III-IV), a greater tumor mutational burden, a higher infiltration of immunosuppressive cells, and a greater likelihood of responding favorably to immunotherapy. The importance of EMX2OS was determined by mechanical learning, and the ceRNA network was constructed, and EMX2OS may be a potential therapeutic target, possibly exerting its function through the EMX2OS/hsa-miR-31-5p/TLN2 axis. Based on machine learning, a novel ERLRs-based score was constructed for predicting the survival of ccRCC patients. The ERLRs-based score is a promising potential independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics. Meanwhile, we screened out key lncRNAEMX2OS and identified the EMX2OS/hsa-miR-31-5p/TLN2 axis, which may provide new clues for the targeted therapy of ccRCC.

Yang Z ，Zhang X ，Zhan N ，Lin L ，Zhang J ，Peng L ，Qiu T ，Luo Y ，Liu C ，Pan C ，Hu J ，Ye Y ，Jiang Z ，Liu X ，Sun M ，Zhang Y ... -  《Cancer Medicine》