scholarly journals ACE2 Correlated With Immune Infiltration Serves As A Novel Prognostic Biomarker In Clear Cell Renal Cell Carcinoma: Implication For COVID-19

2021 ◽  
Vol 17 (1) ◽  
pp. 20-31
Author(s):  
Wuping Yang ◽  
Lei Li ◽  
Kenan Zhang ◽  
Kaifang Ma ◽  
Haibiao Xie ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Prognostic Biomarker ◽  
Cell Renal Cell Carcinoma ◽  
Immune Infiltration

scholarly journals MP92-02 EVALUATION OF TUMOR PD-1 EXPRESSION AS A PROGNOSTIC BIOMARKER IN PATIENTS WITH LOCALIZED CLEAR CELL RENAL CELL CARCINOMA

2016 ◽  
Vol 195 (4S) ◽  
Author(s):  
Kyu Kim ◽  
Rishi Sekar ◽  
Michelle DiMarco ◽  
Dattatraya Patil ◽  
Adeboye Osunkoya ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Prognostic Biomarker ◽  
Cell Renal Cell Carcinoma

scholarly journals PPARα gene is a diagnostic and prognostic biomarker in clear cell renal cell carcinoma by integrated bioinformatics analysis

2019 ◽  
Vol 10 (10) ◽  
pp. 2319-2331
Author(s):  
Yongwen Luo ◽  
Liang Chen ◽  
Gang Wang ◽  
Guofeng Qian ◽  
Xuefeng Liu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Bioinformatics Analysis ◽  
Clear Cell ◽  
Prognostic Biomarker ◽  
Cell Renal Cell Carcinoma

scholarly journals Identification of Prognostic Metabolism-Related Genes in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yusa Chen ◽  
Yumei Liang ◽  
Ying Chen ◽  
Shaxi Ouyang ◽  
Kanghan Liu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Random Forest ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Multivariate Regression ◽  
Clinical Characteristics ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Immune Infiltration

Background. Clear cell renal cell carcinoma (ccRCC) is a cancer with abnormal metabolism. The purpose of this study was to investigate the effect of metabolism-related genes on the prognosis of ccRCC patients. Methods. The data of ccRCC patients were downloaded from the TCGA and the GEO databases and clustered using the nonnegative matrix factorization method. The limma software package was used to analyze differences in gene expression. A random forest model was used to screen for important genes. A novel Riskscore model was established using multivariate regression. The model was evaluated based on the metabolic pathway, immune infiltration, immune checkpoint, and clinical characteristics. Results. According to metabolism-related genes, kidney clear cell carcinoma (KIRC) datasets downloaded from TCGA were clustered into two groups and showed significant differences in prognosis and immune infiltration. There were 667 differentially expressed genes between the two clusters, of which 408 were screened by univariate analysis. Finally, 12 differentially expressed genes (MDK, SLC1A1, SGCB, C4orf3, MALAT1, PILRB, IGHG1, FZD1, IFITM1, MUC20, KRT80, and SALL1) were filtered out using the random forest model. The model of Riskscore was obtained by multiplying the expression levels of these 12 genes with the corresponding coefficients of the multivariate regression. We found that the Riskscore correlated with the expression of these 12 genes; the high Riskscore matched the low survival rate verified in the verification set. The analysis found that the Riskscore model was associated with most of the metabolic processes, immune infiltration of cells such as plasma cells, immune checkpoints such as PD-1, and clinical characteristics such as M stage. Conclusion. We established a new Riskscore model for the prognosis of ccRCC based on metabolism. The genes in the model provided several novel targets for the study of ccRCC.

Upregulated immune checkpoint HHLA2 in clear cell renal cell carcinoma: a novel prognostic biomarker and potential therapeutic target

2018 ◽  
Vol 56 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Dongming Chen ◽  
Wei Chen ◽  
Yong Xu ◽  
Meng Zhu ◽  
Yi Xiao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Prognostic Biomarker ◽  
Transcriptional Regulatory Network ◽  
Human Endogenous Retrovirus ◽  
Molecular Evidence ◽  
Cell Renal Cell Carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is a malignant urogenital cancer with high mortality; however, current progress in understanding its molecular mechanism and predicting clinical treatment outcome is limited. Therefore, this study is to evaluate the clinical significance of immune inhibitory molecular human endogenous retrovirus-H long terminal repeat-associating protein 2 (HHLA2) in ccRCC prognosis and transcriptional regulatory network.MethodsExpression ofHHLA2in ccRCC was examined by an online database platform ONCOMINE. The ONCOMINE result was independently validated by qRT-PCR and immunohistochemistry. Kaplan-Meier survival was generated using IBM SPSS Statistics V.22. ccRCC tissues cells with high HHLA2 were sorted and subjected to microarray transcriptional profiling and analysis.ResultsIt was shown that expression of HHLA2 was statistically significantly increased in ccRCC tissues compared with normal renal tissues at both transcriptional and protein level. Moreover, the expression of HHLA2 was closely correlated with multiple clinicopathological features including tumour size, clinical stage and histological grade. High HHLA2 expression was associated with poor overall survival and clinical outcome. Comprehensive microarray analysis further identified thousands of HHLA2 targets including mRNA, long non-coding RNA and circular RNA that might function in various biological processes, especially, immune response.ConclusionIncreased HHLA2 expression was observed in ccRCC tumour tissue, which leads to a remarkable shorter overall survival and poorer prognosis. Together with other molecular evidence, we have demonstrated that HHLA2 could be a potential prognostic biomarker for ccRCC.

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