scholarly journals Identification of Potential Biomarkers Associated With Immune Infiltration in Papillary Renal Cell Carcinoma

2021 ◽  
Author(s):  
Ran Deng ◽  
Jianpeng Li ◽  
Hong Zhao ◽  
Zhirui Zou ◽  
Jiangwei Man ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Immune Cells ◽  
Renal Cell ◽  
Cox Regression ◽  
Papillary Renal Cell Carcinoma ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Cox Regression Analysis

Abstract Background: Immunotherapeutic approaches have recently emerged as effective treatment regimens against various types of cancer. However, the immune-mediated mechanisms surrounding papillary renal cell carcinoma (pRCC) remain unclear. This study aimed to investigate the tumor microenvironment (TME) and identify the potential immune-related biomarkers for pRCC.Methods: The CIBERSORT algorithm was used to calculate the abundance ratio of immune cells in each pRCC sample downloaded from the database UCSC Xena. Univariate Cox analysis was used to select the prognostic-related tumor-infiltrating immune cells (TIICs). Multivariate Cox regression analysis was performed to develop a signature based on the selected prognostic-related TIICs. Then, these pRCC samples were divided into low- and high-risk groups according to the obtained signature. Analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to investigate the biological function of the DEGs (differentially expressed genes) between the high- and low-risk groups. The hub genes were identified using a Weighted Gene Co-Expression Network Analysis (WGCNA) and a Protein-Protein Interaction (PPI) analysis. The hub genes were subsequently validated using Kaplan-Meier survival analysis, Receiver Operating Characteristic (ROC) analysis, a nomogram prediction model, and via the Gene Expression Omnibus (GEO) database, and the Human Protein Atlas (HPA) database. Finally, we validated the correlation between the nine hub genes and immune cells using the XCELL algorithm.Results: According to our analyses, nine immune cells play a vital role in the TME of pRCC. Our analyses also obtained nine potential immune-related biomarkers for pRCC, including TOP2A, BUB1B, BUB1, TPX2, PBK, CEP55, ASPM, RRM2, and CENPF.Conclusion: In this study, our data revealed the crucial TIICs and potential immune-related biomarkers for pRCC and provided compelling insights into the pathogenesis and potential therapeutic targets for pRCC.

scholarly journals N6-Methyladenosine-Related Long Non-coding RNA Signature Associated With Prognosis and Immunotherapeutic Efficacy of Clear-Cell Renal Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Tianming Ma ◽  
Xiaonan Wang ◽  
Jiawen Wang ◽  
Xiaodong Liu ◽  
Shicong Lai ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differential Expression ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis

Increasing evidence suggests that N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) play important roles in cancer progression and immunotherapeutic efficacy in clear-cell renal cell carcinoma (ccRCC). In this study, we conducted a comprehensive ccRCC RNA-seq analysis using The Cancer Genome Atlas data to establish an m6A-related lncRNA prognostic signature (m6A-RLPS) for ccRCC. Forty-four prognostic m6A-related lncRNAs (m6A-RLs) were screened using Pearson correlation analysis (|R| > 0.7, p < 0.001) and univariable Cox regression analysis (p < 0.01). Using consensus clustering, the patients were divided into two clusters with different overall survival (OS) rates and immune status according to the differential expression of the lncRNAs. Gene set enrichment analysis corroborated that the clusters were enriched in immune-related activities. Twelve prognostic m6A-RLs were selected and used to construct the m6A-RLPS through least absolute shrinkage and selection operator Cox regression. We validated the differential expression of the 12 lncRNAs between tumor and non-cancerous samples, and the expression levels of four m6A-RLs were further validated using Gene Expression Omnibus data and Lnc2Cancer 3.0 database. The m6A-RLPS was verified to be an independent and robust predictor of ccRCC prognosis using univariable and multivariable Cox regression analyses. A nomogram based on age, tumor grade, clinical stage, and m6A-RLPS was generated and showed high accuracy and reliability at predicting the OS of patients with ccRCC. The prognostic signature was found to be strongly correlated to tumor-infiltrating immune cells and immune checkpoint expression. In conclusion, we established a novel m6A-RLPS with a favorable prognostic value for patients with ccRCC. The 12 m6A-RLs included in the signature may provide new insights into the tumorigenesis and allow the prediction of the treatment response of ccRCC.

scholarly journals Low REST Expression Indicates a Biomarker of Poor Prognosis in Patients with Renal Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chaoxiang Lv ◽  
Yuanguo Li ◽  
Qiqi Zhang ◽  
Yanyan Chen ◽  
Dandan Wei ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Cholesterol Homeostasis ◽  
Gene Set Enrichment Analysis ◽  
Cox Regression Analysis

It was initially found that neural-restrictive silencer factor/repressor 1-silencing transcription factor (REST) is a transcriptional repressor of neuronal genes in nonneuronal cells. However, it is reported to be abundantly expressed in various types of aggressive cancer cells. In this study, we evaluated the expression patterns of REST in renal cell carcinoma and found that its expression is lower in tumor tissues compared to normal tissues. The chi-square test showed that the low REST expression was closely related to patients’ clinicopathologic parameters, including the pathologic stage and survival status. ROC curve showed that REST had excellent clinical diagnostic prospect. In addition, patients with low REST expression had poor over survival (OS) and relapse-free survival (RFS). Univariate and multivariate Cox regression analysis confirmed that the low REST expression was an independent predictor of poor prognosis in renal cell carcinoma. Gene set enrichment analysis identified P53 pathway, reactive oxygen species pathway, glycolysis, DNA repair, cholesterol homeostasis, and MYC targets V2 enriched with low REST expression phenotype. These results suggested that REST may be a novel biomarker for the diagnosis and prognosis of renal cell carcinoma in clinical applications.

scholarly journals Increased Expression of TICRR Predicts Poor Clinical Outcomes: A Potential Therapeutic Target for Papillary Renal Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Shuang Xia ◽  
Yan Lin ◽  
Jiaqiong Lin ◽  
Xiaoyong Li ◽  
Xuexian Tan ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Renal Cell Carcinoma ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Clinical Outcomes ◽  
Renal Cell ◽  
Cox Regression ◽  
Papillary Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Clinical Stages

Background: Papillary renal cell carcinoma (PRCC), although the second-most common type of renal cell carcinoma, still lacks specific biomarkers for diagnosis, treatment, and prognosis. TopBP1-interacting checkpoint and replication regulator (TICRR) is a DNA replication initiation regulator upregulated in various cancers. We aimed to evaluate the role of TICRR in PRCC tumorigenesis and prognosis.Methods: Based on the Kidney Renal Papillary cell carcinoma Project (KIRP) on The Cancer Genome Atlas (TCGA) database, we determined the expression of TICRR using the Wilcoxon rank sum test. The biological functions of TICRR were evaluated using the Metascape database and Gene Set Enrichment Analysis (GSEA). The association between TICRR and immune cell infiltration was investigated by single sample GSEA. Logistic analysis was applied to study the correlation between TICRR expression and clinicopathological characteristics. Finally, Cox regression analysis, Kaplan–Meier analysis, and nomograms were used to determine the predictive value of TICRR on clinical outcomes in PRCC patients.Results:TICRR expression was significantly elevated in PRCC tumors (P < 0.001). Functional annotation indicated enrichment with negative regulation of cell division, cell cycle, and corresponding pathways in the high TICRR expression phenotype. High TICRR expression in PRCC was associated with female sex, younger age, and worse clinical stages. Cox regression analysis revealed that TICRR was a risk factor for overall survival [hazard ratio (HR): 2.80, P = 0.002], progression-free interval (HR: 2.86, P < 0.001), and disease-specific survival (HR: 7.03, P < 0.001), especially in patients with male sex, age below 60 years, clinical stages II–IV and clinical T stage T1–T2.Conclusion: Increased TICRR expression in PRCC might play a role in tumorigenesis by regulating the cell cycle and has prognostic value for clinical outcomes.

scholarly journals Construction of a Prognostic Value Model in Papillary Renal Cell Carcinoma by Immune-Related Genes

2020 ◽  
Author(s):  
Leilei Wang ◽  
Weile Gu ◽  
Huijun Ni
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Value ◽  
Cox Regression ◽  
Expression Profiles ◽  
Papillary Renal Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Immune Related Genes

Abstract Papillary renal cell carcinoma (PRCC) is the second most common type of renal carcinoma following clear cell renal cell carcinoma, and the role of immune-related genes (IRGs) in tumorigenesis and metastasis is evident; its prognostic value in PRCC remains unclear. In this study, we downloaded the gene expression profiles and clinical data of patients with PRCC from The Cancer Genome Atlas (TCGA) database and obtained IRGs from the ImmPort database. A total of 371 differentially expressed IRGs (DEIRGs) were discovered between PRCC and normal kidney tissues. Prognostic DEIRGs (PDEIRGs) were identified by univariate Cox regression analysis. Then, we screened the four most representative PDEIRGs (IL13RA2, CCL19, BIRC5, and INHBE) and used them to construct a risk model to predict the prognosis of patients with PRCC. This model precisely stratified survival outcome and accurately identified mutation burden in PRCC. Thus, our results suggest that these four PDEIRGs are available prognostic predictors for PRCC. They could be used to assess the prognosis and to guide individualized treatments for patients with PRCC.

scholarly journals Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Jingwei Ke ◽  
Jie Chen ◽  
Xin Liu
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clinical Characteristics ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Cell Renal Cell Carcinoma ◽  
Significant Difference

Abstract Background: There is still controversy regarding immunotherapy biomarkers. Therefore, we aimed to identify prognostic biomarkers related to immunotherapy for clear cell renal cell carcinoma (ccRCC).Methods: Fragments Per Kilobase Million (FPKM) data and clinical characteristics for ccRCC patients from The Cancer Genome Atlas (TCGA) database were downloaded. Unsupervised consensus clustering analysis was performed to divide patients into different immune subgroups according to their single-sample gene set enrichment analysis (ssGSEA) scores. Then, we validated the differences in immune cell infiltration, prognosis, clinical characteristics and expression levels of HLA and immune checkpoint genes between different immune subgroups. Weighted gene coexpression network analysis (WGCNA) was used to identify the significant modules and hub genes that were related to the immune subgroups. A nomogram was established to predict the overall survival (OS) outcomes after independent prognostic factors were identified by least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses.Results: Five clusters (immune subgroups) were identified. There was no significant difference in age, sex or N stage. And there were significant differences in race, T stage, M stage, grade, prognosis and tumor microenvironment. HLA gene families and CTLA4 showed significant differences between the five clusters, while PD1 and PDL1 did not. The red module was significant, and 14 hub genes were obtained. In addition, the nomogram containing LAG3 and GZMK accurately predicted OS outcomes of ccRCC patients.Conclusion: LAG3 and GZMK are strongly related to immunity and may provide suggestions for ccRCC immunotherapy.

scholarly journals Prognostic value and immunological role of AXL gene in clear cell renal cell carcinoma associated with identifying LncRNA/RBP/AXL mRNA networks

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yi Wang ◽  
Ye Tian ◽  
Shouyong Liu ◽  
Zengjun Wang ◽  
Qianwei Xing
Keyword(s):  
Renal Cell Carcinoma ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Tcga Dataset

Abstract Backgrounds This article aimed to explore the prognostic and immunological roles of AXL gene in clear cell renal cell carcinoma (ccRCC) for overall survival (OS) and to identify the LncRNA/RBP/AXL mRNA networks. Methods AXL-related gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA) dataset and AXL-related pathways were identified by gene set enrichment analysis (GSEA). We performed univariate/multivariate Cox regression analysis to evaluate independent prognostic factors and the relationships between AXL and immunity were also investigated. Results The outcomes of us indicated that the AXL mRNA expression was up-regulated in ccRCC samples and high expression of AXL was associated with worse OS in TCGA dataset (P < 0.01). Further external verification results from HPA, UALCAN, ICGC dataset, GSE6344, GSE14994, and qRT-PCR remained consistent (all P < 0.05). AXL was also identified as an independent prognostic factor for ccRCC by univariate/multivariate Cox regression analysis (both P < 0.05). A nomogram including AXL expression and clinicopathological factors was established by us and GSEA results found that elevated AXL expression was associated with the JAK-STAT, P53, WNT, VEGF and MAPK signaling pathways. In terms of immunity, AXL was dramatically linked to tumor microenvironment, immune cells, immune infiltration, immune checkpoint molecules and tumor mutational burden (TMB). As for its potential mechanisms, we also identified several LncRNA/RBP/AXL mRNA axes. Conclusions AXL was revealed to play prognostic and immunological roles in ccRCC and LncRNA/RBP/AXL mRNA axes were also identified by us for its potential mechanisms.

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.

Second-line VEGF TKI after IO combination therapy: Results from the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC).

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 684-684
Author(s):  
Igor Stukalin ◽  
Shaan Dudani ◽  
Connor Wells ◽  
Chun Loo Gan ◽  
Sumanta K. Pal ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Combination Therapy ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Response Rates ◽  
Second Line ◽  
First Line ◽  
Cox Regression Analysis

684 Background: Immuno-Oncology (IO) combinations are standard of care first-line treatment for metastatic renal cell carcinoma (mRCC). Data on therapy with vascular endothelial growth factor (VEGF) tyrosine kinase inhibitors (TKI) post-progression on IO-combination therapy are limited. Methods: Using the IMDC, a retrospective analysis was done on mRCC patients treated with second-line VEGF TKIs after receiving IO combination therapy. Patients received first-line ipilimumab+nivolumab (IOIO) or anti-PD(L)1+anti-VEGF (IOVE). Baseline variables and second-line IMDC risk factors were collected. Overall response rates (ORR), time to treatment failure (TTF) and overall survival (OS) were determined. Multivariable Cox regression analysis was performed. Results: 142 patients were included. 75 patients received IOIO and 67 received IOVE pretreatment. The ORR of 2nd line therapy was 17/46 (37%) and 7/57 (12%) in the IOIO and IOVE pretreated groups, respectively (p<0.01). 2nd-line TTF was 5.4 months (95% CI 4.1-8.3) for the IOIO- and 4.6 months (95% CI 3.7-5.8) for the IOVE-pretreated group (p=0.37). 2nd-line median OS was 17.2 months (95% CI 10.8-35.1) and 11.8 months (95% CI 9.9-21.3) for the prior IOIO and IOVE groups, respectively (p=0.13). The hazard ratio adjusted by IMDC for IOVE vs IOIO pretreatment was 1.22 (95% CI 0.73-2.07, p=0.45) for 2nd line TTF and 1.43 (95% CI 0.74-2.8, p=0.29) for 2nd line OS. Conclusions: VEGF TKIs show activity after combination IO therapy. Response rates are higher in patients treated with VEGF TKIs after first-line IOIO compared to after IOVE. In patients with VEGF TKI after IOIO or IOVE, no difference in OS and TTF was observed.[Table: see text]

scholarly journals rs3200401 MALAT1 GENE POLYMORPHISM IS NOT RELATED TO AGE OF KIDNEY CANCER ONSET

2020 ◽  
Vol 20 (2) ◽  
pp. 119-123
Author(s):  
A.D. Volkohon ◽  
V. Yu. Harbuzova ◽  
O.V. Ataman
Keyword(s):  
Renal Cell Carcinoma ◽  
Gene Polymorphism ◽  
Cell Carcinoma ◽  
Kidney Cancer ◽  
Renal Cell ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Today, the long non-coding RNA MALAT1 is considered to be one of the major RNAs involved in the emergence and metastasizing of various malignant tumours. Recent experiments have shown that MALAT1 plays an important role in the onset and progression of kidney cancer as well. It was found that cancer patient survival depends on the level of MALAT1 gene expression. The aim of the study was to investigate the possible association between rs3200401 MALAT1 gene polymorphism and age of kidney cancer onset among Ukrainian patients. Materials and methods. The venous blood of 101 patients with clear cell renal cell carcinoma (42 women and 59 men) was used for study. Determination of MALAT1 gene rs320040 polymorphism was performed by the Real-Time polymerase chain reaction method using TaqManSNP Assay C_3246069_10 components. Statistical analysis of the data obtained was performed using SPSS (version 17.0). To test the possible association between rs3200401 genotypes and the age of kidney cancer onset Kaplan-Meier and Cox regression techniques were used. P value < 0.05 was considered as statistically significant. Results. The obtained results of MALAT1 gene rs3200401 polymorphic site genotyping revealed that 71 (70.3%) patients with renal cell carcinoma had CC genotype, 29 (28.7%) – CT, 1 (1%) – TT genotype. Survival analysis by Kaplan-Meier method showed that life expectancy until the tumour occurrence was not related to rs3200401 locus (log rank P = 0.449 – for codominant model; log rank P = 0.847 – for dominant model). The results of Cox regression analysis also showed no link between MALAT gene rs3200401-site and risk of renal cell carcinoma development (P > 0.05). No statistically significant results were found after adjustment for sex, body mass index, metastasis, smoking and drinking habits (P > 0.05). Conclusions. The rs3200401 gene polymorphism of long non-coding RNA MALAT1 is not associated with the age of kidney cancer onset in Ukrainian population.

scholarly journals Combination of Albumin-Globulin Score and Sarcopenia to Predict Prognosis in Patients With Renal Cell Carcinoma Undergoing Laparoscopic Nephrectomy

2021 ◽  
Vol 8 ◽  
Author(s):  
Weipu Mao ◽  
Nieke Zhang ◽  
Keyi Wang ◽  
Qiang Hu ◽  
Si Sun ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Training Set ◽  
Test Set ◽  
Cox Regression Analysis ◽  
Inflammatory Status ◽  
Grade 3 ◽  
The Impact

We conducted a multicenter clinical study to construct a novel index based on a combination of albumin-globulin score and sarcopenia (CAS) that can comprehensively reflect patients' nutritional and inflammatory status and assess the prognostic value of CAS in renal cell carcinoma (RCC) patients. Between 2014 and 2019, 443 patients from 3 centers who underwent nephrectomy were collected (343 in the training set and 100 in the test set). Kaplan-Meier curves were employed to analyze the impact of albumin-globulin ratio (AGR), albumin-globulin score (AGS), sarcopenia, and CAS on overall survival (OS) and cancer-specific survival (CSS) in RCC patients. Receiver operating characteristic (ROC) curves were used to assess the predictive ability of AGR, AGS, sarcopenia, and CAS on prognosis. High AGR, low AGS, and nonsarcopenia were associated with higher OS and CSS. According to CAS, the training set included 60 (17.5%) patients in grade 1, 176 (51.3%) patients in grade 2, and 107 (31.2%) patients in grade 3. Lower CAS was linked to longer OS and CSS. Multivariate Cox regression analysis revealed that CAS was an independent risk factor for OS (grade 1 vs. grade 3: aHR = 0.08; 95% CI: 0.01–0.58, p = 0.012; grade 2 vs. grade 3: aHR = 0.47; 95% CI: 0.25–0.88, p = 0.018) and CSS (grade 1 vs. grade 3: aHR = 0.12; 95% CI: 0.02–0.94, p = 0.043; grade 2 vs. grade 3: aHR = 0.31; 95% CI: 0.13–0.71, p = 0.006) in RCC patients undergoing nephrectomy. Additionally, CAS had higher accuracy in predicting OS (AUC = 0.687) and CSS (AUC = 0.710) than AGR, AGS, and sarcopenia. In addition, similar results were obtained in the test set. The novel index CAS developed in this study, which reflects patients' nutritional and inflammatory status, can better predict the prognosis of RCC patients.

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