scholarly journals Prognostic significance and immune correlates of CD73 expression in renal cell carcinoma

2020 ◽  
Vol 8 (2) ◽  
pp. e001467
Author(s):  
Abhishek Tripathi ◽  
Edwin Lin ◽  
Wanling Xie ◽  
Abdallah Flaifel ◽  
John A Steinharter ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
T Cell ◽  
Protein Expression ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Significance ◽  
Cox Regression Analysis ◽  
Tcga Dataset ◽  
Cd73 Expression

BackgroundCD73–adenosine signaling in the tumor microenvironment is immunosuppressive and may be associated with aggressive renal cell carcinoma (RCC). We investigated the prognostic significance of CD73 protein expression in RCC leveraging nephrectomy samples. We also performed a complementary analysis using The Cancer Genome Atlas (TCGA) dataset to evaluate the correlation of CD73 (ecto-5′-nucleotidase (NT5E), CD39 (ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1)) and A2 adenosine receptor (A2AR; ADORA2A) transcript levels with markers of angiogenesis and antitumor immune response.MethodsPatients with RCC with available archived nephrectomy samples were eligible for inclusion. Tumor CD73 protein expression was assessed by immunohistochemistry and quantified using a combined score (CS: % positive cells×intensity). Samples were categorized as CD73negative (CS=0), CD73low or CD73high (< and ≥median CS, respectively). Multivariable Cox regression analysis compared disease-free survival (DFS) and overall survival (OS) between CD73 expression groups. In the TCGA dataset, samples were categorized as low, intermediate and high NT5E, ENTPD1 and ADORA2A gene expression groups. Gene expression signatures for infiltrating immune cells, angiogenesis, myeloid inflammation, and effector T-cell response were compared between NT5E, ENTPD1 and ADORA2A expression groups.ResultsAmong the 138 patients eligible for inclusion, ‘any’ CD73 expression was observed in 30% of primary tumor samples. High CD73 expression was more frequent in patients with M1 RCC (29% vs 12% M0), grade 4 tumors (27% vs 13% grade 3 vs 15% grades 1 and 2), advanced T-stage (≥T3: 22% vs T2: 19% vs T1: 12%) and tumors with sarcomatoid histology (50% vs 12%). In the M0 cohort (n=107), patients with CD73high tumor expression had significantly worse 5-year DFS (42%) and 10-year OS (22%) compared with those in the CD73negative group (DFS: 75%, adjusted HR: 2.7, 95% CI 1.3 to 5.9, p=0.01; OS: 64%, adjusted HR: 2.6, 95% CI 1.2 to 5.8, p=0.02) independent of tumor stage and grade. In the TCGA analysis, high NT5E expression was associated with significantly worse 5-year OS (p=0.008). NT5E and ENTPD1 expression correlated with higher regulatory T cell (Treg) signature, while ADORA2A expression was associated with increased Treg and angiogenesis signatures.ConclusionsHigh CD73 expression portends significantly worse survival outcomes independent of stage and grade. Our findings provide compelling support for targeting the immunosuppressive and proangiogenic CD73–adenosine pathway in RCC.

Interleukin-4 Promoter Polymorphisms: A Genetic Prognostic Factor for Survival in Metastatic Renal Cell Carcinoma

2007 ◽  
Vol 25 (7) ◽  
pp. 845-851 ◽  
Author(s):  
Thomas Kleinrath ◽  
Christoph Gassner ◽  
Peter Lackner ◽  
Martin Thurnher ◽  
Reinhold Ramoner
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clinical Course ◽  
Prognostic Significance ◽  
Interleukin 4 ◽  
Promoter Polymorphisms ◽  
Cox Regression Analysis ◽  
Metastatic Rcc

Purpose Renal cell carcinoma (RCC) is considered a cytokine-responsive tumor. The clinical course of a patient may thus be influenced by the patient's capacity to produce distinct cytokines. Therefore, cytokine gene polymorphisms in RCC patients were analyzed to determine haplotype combinations with prognostic significance. Patients and Methods A selection of 21 single nucleotide polymorphisms within the promoter regions of 13 cytokine genes were analyzed in a cross-sectional single-center study of 80 metastatic RCC patients. Univariate and multivariate analyses and the Cox forward-stepwise regression model were chosen to assess genetic risk factors. Results Multivariate Cox regression analysis confirmed by a bootstrap technique identified the heterozygous IL4 genotype −589T−33T/−589C−33C as an independent prognostic risk factor (risk ratio, 3.1; P < .01; 95% CI, 1.4 to 6.9; adjusted for age, sex, and nuclear grading) in metastatic RCC patients. IL4 haplotype −589T−33T and −589C−33C were found with a frequency of 0.069 and 0.925, respectively, which represents a two-fold decrease of IL4 haplotype −589T−33T (P < .01) and an increase of IL4 haplotype −589C−33C frequency (P < .05) in metastatic RCC compared with other white reference study populations. The median overall survival was decreased 3.5-fold (P < .05) in heterozygote patients carrying IL4 haplotype −589T−33T and −589C−33C (3.78 months) compared with patients homozygote for IL4 haplotype −589C−33C (13.44 months). In addition, a linkage disequilibrium between the IL4 gene and the KIF3A gene was detected. Conclusion Our findings indicate that IL4 promoter variants influence prognosis in patients with metastatic RCC and suggest that genetically determined interleukin-4 (IL-4) production affects the clinical course of the disease possibly through regulation of immune surveillance.

scholarly journals Protein Expression of ZEB2 in Renal Cell Carcinoma and Its Prognostic Significance in Patient Survival

PLoS ONE ◽  
2013 ◽  
Vol 8 (5) ◽  
pp. e62558 ◽  
Author(s):  
Yong Fang ◽  
Jinhuan Wei ◽  
Jiazheng Cao ◽  
Hongwei Zhao ◽  
Bing Liao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Protein Expression ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Patient Survival ◽  
Prognostic Significance

scholarly journals A 17-Gene Signature Predicted Prognosis in Renal Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Fan Li ◽  
Weifeng Hu ◽  
Wei Zhang ◽  
Guohao Li ◽  
Yonglian Guo
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Malignant Tumors ◽  
Prognostic Significance ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Incidence And Mortality ◽  
Tcga Dataset

Renal cell carcinoma (RCC), which was one of the most common malignant tumors in urinary system, had gradually increased incidence and mortality in recent years. Although significant advances had been made in molecular and biology research on the pathogenesis of RCC, effective treatments and prognostic indicators were still lacking. In order to predict the prognosis of RCC better, we identified 17 genes that were associated with the overall survival (OS) of RCC patients from The Cancer Genome Atlas (TCGA) dataset and a 17-gene signature was developed. Through SurvExpress, we analyzed the expression differences of the 17 genes and their correlation with the survival of RCC patients in five datasets (ZHAO, TCGA, KIPAN, KIRC, and KIRP), and then evaluated the survival prognostic significance of the 17-gene signature for RCC. Our results showed that the 17-gene signature had a predictive prognostic value not only in single pathologic RCC, but also in multiple pathologic types of RCC. In conclusion, the 17-gene signature model was related to the survival of RCC patients and could help predict the prognosis with significant clinical implications.

Association of gene expression with clinical outcomes in patients with renal cell carcinoma treated with pembrolizumab in KEYNOTE-427.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 5024-5024 ◽  
Author(s):  
David F. McDermott ◽  
Jae-Lyun Lee ◽  
Frede Donskov ◽  
Scott S. Tykodi ◽  
Georg A. Bjarnason ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Rna Sequencing ◽  
Clinical Data ◽  
Renal Cell ◽  
Clear Cell ◽  
Specific Gene ◽  
Gene Expression Signatures

5024 Background: We assessed the association of baseline RNA-sequencing–based gene expression signatures and DNA alterations with response or resistance to pembrolizumab in patients with advanced renal cell carcinoma in cohorts A (clear cell; n = 110) and B (non-clear cell; n = 165) of the phase 2 KEYNOTE-427 study (NCT02853344). Methods: Using RNA-sequencing, we analyzed the association of gene expression signatures (18-gene T-cell–inflamed gene expression profile [GEP]; 10 non–T-cell–inflamed GEP canonical signatures [angiogenesis, gMDSC, glycolysis, hypoxia, mMDSC, MYC, proliferation, RAS, stromal/EMT/TGFβ, WNT]) quantifying tumor microenvironment elements (TME) with objective response rate (ORR) and progression-free survival (PFS). Canonical signatures were derived from 2 databases (TCGA, Moffit) using an algorithm that included genes based on their correlation to reference signatures in the literature. Signature definitions were finalized before linking to the clinical data, and significance was prespecified at 0.10 given the potential for limited power. Canonical signatures were analyzed through regression testing of response for association with consensus signatures after adjusting for T-cell–inflamed GEP and International Metastatic RCC Database Consortium scores in the model. P values were adjusted for multiplicity. Using whole exome sequencing, we also summarized the association of renal cell carcinoma driver gene mutations with ORR. Clinical data cutoff: Jan 30, 2019. Results: Patient characteristics for this analysis were comparable to the overall population. In cohort A, T-cell–inflamed GEP (n = 78) was statistically significantly associated with a better ORR ( P = 0.021; AUROC = 0.65) but not PFS ( P = 0.116). No other TME canonical signatures showed a correlation with ORR or PFS. ORR was estimated for mutations (Table). Conclusions: RNA-sequencing–based, T-cell–inflamed GEP was associated with ORR in patients with clear cell renal cell carcinoma receiving first-line pembrolizumab. Precision was limited by sample size for estimating ORR by specific gene mutation status. Evaluation of tissue-based biomarkers in larger studies are planned. Biomarker analyses from patients in cohort B will also be presented. Clinical trial information: NCT02853344 . [Table: see text]

scholarly journals Metabolic genes show excellent prognostic ability for clear cell renal cell carcinoma

2020 ◽  
Author(s):  
Chengjian Ji ◽  
Yichun Wang ◽  
Liangyu Yao ◽  
Jiaochen Luan ◽  
Rong Cong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Expression Profiles ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Metabolic Genes

Abstract Background Renal cell carcinoma (RCC) is one of the major malignant tumors of the urinary system, with a high mortality rate and a poor prognosis. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC. Although the diagnosis and treatment methods have been significantly improved, the incidence and mortality of ccRCC are high and still increasing. The occurrence and development of ccRCC are closely related to the changes of classic metabolic pathways. This article aims to explore the relationship between metabolic genes and the prognosis of patients with ccRCC. Patients and methods: Gene expression profiles of 63 normal kidney tissues and 446 ccRCC tissues from TCGA database and gene expression profiles of 39 ccRCC tissues from GEO database were used to obtain differentially expressed genes (DEGs) in ccRCC. Through the the KEGG gene sets of GSEA database, we obtained metabolic genes (MGs). Univariate Cox regression analysis was used to identify prognostic MGs. Lasso regression analysis was used to eliminate false positives because of over-fitting. Multivariate Cox regression analysis was used to established a prognostic model. Gene expression data and related survival data of 101 ccRCC patients from ArrayExpress database were used for external validation. Survival analysis, ROC curve analysis, independent prognostic analysis and clinical correlation analysis were performed to evaluate this model. Results We found that there were 479 abnormally expressed MGs in ccRCC tissues. Through univariate Cox regression analysis, Lasso regression analysis and multivariate Cox regression analysis, we identified 4 prognostic MGs (P4HA3, ETNK2, PAFAH2 and ALAD) and established a prognostic model (riskScore). Whether in the training cohort, the testing cohort or the entire cohort, this model could accurately stratify patients with different survival outcomes. The prognostic value of riskScore and 4 MGs was also confirmed in the ArrayExpress database. Results of GSEA analysis show that DEGs in patients with better prognosis were enriched in metabolic pathways. Then, a new Nomogram with higher prognostic value was constructed to better predict the 1-year OS, 3-year OS and 5-year OS of ccRCC patients. In addition, we successfully established a ceRNA network to further explain the differences in the expression of these MGs between high-risk patients and low-risk patients Conclusion We have successfully established a risk model (riskScore) based on 4 MGs, which could accurately predict the prognosis of patients with ccRCC. Our research may shed new light on ccRCC patients' prognosis and treatment management.

scholarly journals Prognostic significance of pathologic nodal positivity in non-metastatic patients with renal cell carcinoma who underwent radical or partial nephrectomy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sung Han Kim ◽  
Boram Park ◽  
Eu Chang Hwang ◽  
Sung-Hoo Hong ◽  
Chang Wook Jeong ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Partial Nephrectomy ◽  
Renal Cell ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Multivariable Analysis ◽  
Survival Outcomes ◽  
Prognostic Impact ◽  
Cox Regression Analysis

AbstractThis retrospective, five-multicenter study was aimed to evaluate the prognostic impact of pathologic nodal positivity on recurrence-free (RFS), metastasis-free (MFS), overall (OS), and cancer-specific (CSS) survivals in patients with non-metastatic renal cell carcinoma (nmRCC) who underwent either radical or partial nephrectomy with/without LN dissection. A total of 4236 nmRCC patients was enrolled between 2000 and 2012, and followed up through the end of 2017. Survival measures were compared between 52 (1.2%) stage pT1-4N1 (LN+) patients and 4184 (98.8%) stage pT1-4N0 (LN−) patients using Kaplan–Meier analysis with the log-rank test and Cox regression analysis to determine the prognostic risk factors for each survival measure. During the median 43.8-month follow-up, 410 (9.7%) recurrences, 141 (3.3%) metastases, and 351 (8.3%) deaths, including 212 (5.0%) cancer-specific deaths, were reported. The risk factor analyses showed that predictive factors for RFS, CSS, and OS were similar, whereas those of MFS were not. After adjusting for significant clinical factors affecting survival outcomes considering the hazard ratios (HR) of each group, the LN+ group, even those with low pT stage, had similar to or worse survival outcomes than the pT3N0 (LN−) group in multivariable analysis and had significantly more relationship with RFS than MFS. All survival measures were significantly worse in pT1-2N1 patients (MFS/RFS/OS/CSS; HR 4.12/HR 3.19/HR 4.41/HR 7.22) than in pT3-4N0 patients (HR 3.08/HR 2.92/HR 2.09/HR 3.73). Therefore, LN+ had an impact on survival outcomes worse than pT3-4N0 and significantly affected local recurrence rather than distant metastasis compared to LN− in nmRCC after radical or partial nephrectomy.

scholarly journals Decreased CDKL2 Expression in Clear Cell Renal Cell Carcinoma Predicts Worse Overall Survival

2022 ◽  
Vol 8 ◽  
Author(s):  
Zhan Chen ◽  
Yan Lv ◽  
Lu He ◽  
Shunli Wu ◽  
Zhuang Wu
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Poor Prognosis ◽  
Clear Cell ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
Cell Renal Cell Carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is the most frequent and lethal type of kidney cancer. Although differential expression of cyclin-dependent kinase-like 2 (CDKL2) has been reported to be associated with tumor progression in other cancers, its prognostic value, and potential mechanism in patients with ccRCC still remain unknown.Methods: Gene expression analysis was conducted using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus, and International Cancer Genome Consortium databases. Further, clinicopathologic analysis; Kaplan–Meier survival analysis; weighted gene co-expression network analysis; gene set enrichment analysis; gene ontology enrichment; methylation; and immune infiltration analyses were performed using TCGA-kidney renal clear cell carcinoma profiles. CDKL2 translational levels were analyzed using The Human Protein Atlas database.Results:CDKL2 expression was decreased in ccRCC samples retrieved from the four databases. Gender, survival status, histologic grade, clinical stage, TNM classification, and tumor status were closely related to CDKL2 expression. In addition, CDKL2 downregulation was an independent prognostic factor for poor prognosis in multivariate analysis. Enrichment analyses using multiple tests revealed that CDKL2 is not just closely related to immune response but this association is highly correlated as well. Further, we found that CDKL2 expression was significantly correlated with the infiltration levels of T cell CD4 memory resting; monocytes; macrophages M0, M1, and M2; dendritic cells resting; mast cells resting; plasma cells; T cell CD8; and T cell regulatory.Conclusion: This is the first report to study the expression of CDKL2 in ccRCC, wherein we suggest that decreased CDKL2 expression is closely correlated with poor prognosis in ccRCC. We consider that CDKL2 is a novel and potential prognostic biomarker associated with immune infiltrates in ccRCC.

scholarly journals METTL14 Acts as a Potential Regulator of Tumor Immune and Progression in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Tianbo Xu ◽  
Su Gao ◽  
Hailong Ruan ◽  
Jingchong Liu ◽  
Yuenan Liu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Tumor Immunity ◽  
Renal Cell ◽  
Clear Cell ◽  
Risk Group ◽  
Critical Role ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis

Clear cell renal cell carcinoma (ccRCC) is characterized by its insensitivity to chemoradiotherapy and lacks effective diagnostic and prognostic biomarkers. In this study, we focused on the role of m6A RNA methylation regulators for tumor immunity. Based on the expression of 20 m6A regulators, consensus clustering was performed to divide patients into cluster1/cluster2 and showed that there was a survival difference between the two clusters. Through cox regression analysis, five hub m6A regulators were screened to construct a risk model. Further analysis showed that the risk score was an independent prognostic factor. GSEA, GSVA, and KEGG analysis revealed that immune cell pathways played a critical role between the high risk group and low risk group. Combined with CIBERSORT and survival analysis, five hub tumor-infiltrating immune cells (TIICs) were identified for further study. Meanwhile, correlation analysis indicated that IGF2BP2 was positively associated with activated memory CD4 T cell and METTL14 was negatively correlated to the regulatory T cell. Therefore, IGF2BP2 and METTL14 were regarded as key genes. Further study verified that only METTL14 possessed good diagnostic and prognostic value. Then, GSEA exhibited that METTL14 was mainly enriched in chemokine related pathways. We also found that CCL5 was negatively correlated to METTL14 and might serve as a potential target of METTL14. In conclusion, these findings suggest that the METTL14/CCL5/Tregs axis is a potential signaling pathway for regulating tumor immunity, and might become novel therapeutic targets for ccRCC.

scholarly journals Preoperative systemic immune-inflammation index predicts prognosis of patients with non-metastatic renal cell carcinoma: a propensity score-matched analysis

2020 ◽  
Author(s):  
Xu Hu ◽  
Yan-Xiang Shao ◽  
Zhi-Qiang Yang ◽  
Wei-Chao Dou ◽  
San-Chao Xiong ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Propensity Score ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Independent Predictor ◽  
Prognostic Significance ◽  
Cox Regression Analysis ◽  
Immune Inflammation ◽  
Metastatic Rcc

Abstract Background: A novel systemic immune-inflammation index (SII), based on the neutrophils, lymphocytes and platelet counts, is associated with the prognosis of several cancers. The present study evaluates the prognostic significance of SII in non-metastatic renal cell carcinoma (RCC).Method: The present study retrospectively reviewed the medical record of patients with non-metastatic RCC who underwent nephrectomy between 2010 and 2013. Receiver operating characteristic (ROC) curve analysis was performed to identify the optimal cut-off value. In addition, the propensity score matching (PSM) was performed with a matching ratio of 1:1. Univariate and multivariate Cox proportional hazards models were used to identify the prognostic factors. The results were reported by hazard ratio (HR) with 95% confidence interval (95% CI). Results: A total of 646 patients were included in the final analysis. High SII group (>529) was significantly associated with older age (P=0.014), larger tumor (P<0.001), higher pathological T stage (P<0.001), higher tumor grade (P<0.001) and more tumor necrosis (P<0.001). Multivariate Cox regression analysis demonstrated that the higher preoperative SII was significantly associated with worse overall survival (OS) (HR=2.26; 95%CI 1.44-3.54; P<0.001) and cancer-specific survival (CSS) (HR=2.17; 95%CI 1.33-3.55; P=0.002). After PSM, elevated preoperative SII was an independent predictor of poor OS (HR=1.78; 95%CI 1.1-2.87; P=0.018) and CSS (HR=1.8; 95%CI 1.07-3.03; P=0.027).Conclusion: In conclusion, preoperative SII is associated with adverse factors for RCC. Furthermore, higher preoperative SII is an independent predictor of poor OS and CSS in surgically treated patients with non-metastatic RCC. More prospective and large scale studies are warranted to validate our findings.

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