scholarly journals A New Prognostic Risk Model Based on PPAR Pathway-Related Genes in Kidney Renal Clear Cell Carcinoma

PPAR Research ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yingkun Xu ◽  
Xiunan Li ◽  
Yuqing Han ◽  
Zilong Wang ◽  
Chenglin Han ◽  
...  
Keyword(s):  
Survival Rate ◽  
Cell Carcinoma ◽  
Risk Model ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
R Language ◽  
Ppar Pathway

Objective. This study is aimed at using genes related to the peroxisome proliferator-activated receptor (PPAR) pathway to establish a prognostic risk model in kidney renal clear cell carcinoma (KIRC). Methods. For this study, we first found the PPAR pathway-related genes on the gene set enrichment analysis (GSEA) website and found the KIRC mRNA expression data and clinical data through TCGA database. Subsequently, we used R language and multiple R language expansion packages to analyze the expression, hazard ratio analysis, and coexpression analysis of PPAR pathway-related genes in KIRC. Afterward, using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website, we established the protein-protein interaction (PPI) network of genes related to the PPAR pathway. After that, we used LASSO regression curve analysis to establish a prognostic survival model in KIRC. Finally, based on the model, we conducted correlation analysis of the clinicopathological characteristics, univariate analysis, and multivariate analysis. Results. We found that most of the genes related to the PPAR pathway had different degrees of expression differences in KIRC. Among them, the high expression of 27 genes is related to low survival rate of KIRC patients, and the high expression of 13 other genes is related to their high survival rate. Most importantly, we used 13 of these genes successfully to establish a risk model that could accurately predict patients’ prognosis. There is a clear correlation between this model and metastasis, tumor, stage, grade, and fustat. Conclusions. To the best of our knowledge, this is the first study to analyze the entire PPAR pathway in KIRC in detail and successfully establish a risk model for patient prognosis. We believe that our research can provide valuable data for future researchers and clinicians.

GALNT14 expression in renal clear cell carcinoma and its effect on prognosis

2021 ◽  
Author(s):  
Yuqin Wei ◽  
Fan Wu ◽  
Shengfeng Zhang ◽  
Yanlin Tan ◽  
Qunying Wu ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Cox Regression ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Regulatory Pathways ◽  
Cox Analysis ◽  
The Relationship

Abstract Background The expression of GALNT14 in kidney renal clear cell carcinoma (KIRC) and its clinical significance remains unknown. Methods The KIRC data expressed by GALNT14 was downloaded from The Cancer Genome Atlas (TCGA) database. The expression of GALNT14 was analyzed by R software, Perl software and online analysis database. The relationship between GALNT14 expression and clinicopathological features in KIRC was analyzed by univariate, multivariate Cox regression and some databases. Gene Expression Profling Interactive Analysis (GEPIA), Starbase v3.0, UALCAN, and Kaplan-Meier were used to analyze the relationship between GALNT14 expression and overall survival (OS) in KIRC. UALCAN detects the expression of GALNT14 methylation in KIRC. Linkedomics and Genemania were used to analyze the gene co-expression of GALNT14. Gene Set Enrichment Analysis (GSEA) was performed to search for potential regulatory pathways. Results We found that GALNT14 was overexpressed in KIRC (p=1.433e-25). Patients with high GALNT14 expression in KIRC had a better prognosis than patients with low GALNT14 expression (p=0.008). In addition, high GALNT14 expression in KIRC was significantly associated with low T stage and positive OS (p<0.05). Univariate Cox analysis showed that GALNT14 was positively correlated with OS (p<0.001). Multivariate Cox analysis showed that GALNT14 was associated with OS (p<0.001), age (p=0.01) and histological grade (p=0.02). GALNT14 methylation is low expressed in KIRC (p<0.001). GSEA analysis showed that GALNT14 was enriched in histidine metabolism, peroxisome, and renin-angiotensin system pathways. Conclusion GALNT14 can be used as an independent prognostic factor for renal clear cell carcinoma and a potential target for clinical diagnosis and treatment of KIRC.

scholarly journals Comprehensive Analysis of the Immune Infiltrates of Pyroptosis in Kidney Renal Clear Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhuolun Sun ◽  
Changying Jing ◽  
Xudong Guo ◽  
Mingxiao Zhang ◽  
Feng Kong ◽  
...  
Keyword(s):  
High Risk ◽  
Cell Carcinoma ◽  
Poor Prognosis ◽  
Immune Cell ◽  
Risk Model ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Risk Scores

Kidney renal clear cell carcinoma (KIRC) has long been identified as a highly immune-infiltrated tumor. However, the underlying role of pyroptosis in the tumor microenvironment (TME) of KIRC remains poorly described. Herein, we systematically analyzed the prognostic value, role in the TME, response to ICIs, and drug sensitivity of pyroptosis-related genes (PRGs) in KIRC patients based on The Cancer Genome Atlas (TCGA) database. Cluster 2, by consensus clustering for 24 PRGs, presented a poor prognosis, likely because malignancy-related hallmarks were remarkably enriched. Additionally, we constructed a prognostic prediction model that discriminated well between high- and low-risk patients and was further confirmed in external E-MTAB-1980 cohort and HSP cohort. By further analyzing the TME based on the risk model, higher immune cell infiltration and lower tumor purity were found in the high-risk group, which presented a poor prognosis. Patients with high risk scores also exhibited higher ICI expression, indicating that these patients may be more prone to profit from ICIs. The sensitivity to anticancer drugs that correlated with model-related genes was also identified. Collectively, the pyroptosis-related prognosis risk model may improve prognostic information and provide directions for current research investigations on immunotherapeutic strategies for KIRC patients.

scholarly journals Gene Signature Associated With Bromodomain Genes Predicts the Prognosis of Kidney Renal Clear Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Junwan Lu ◽  
Changrui Qian ◽  
Yongan Ji ◽  
Qiyu Bao ◽  
Bin Lu
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Cell Carcinoma ◽  
Epigenetic Regulation ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Survival Prediction

Bromodomain (BRD) proteins exhibit a variety of activities, such as histone modification, transcription factor recruitment, chromatin remodeling, and mediator or enhancer complex assembly, that affect transcription initiation and elongation. These proteins also participate in epigenetic regulation. Although specific epigenetic regulation plays an important role in the occurrence and development of cancer, the characteristics of the BRD family in renal clear cell carcinoma (KIRC) have not been determined. In this study, we investigated the expression of BRD family genes in KIRC at the transcriptome level and examined the relationship of the expression of these genes with patient overall survival. mRNA levels of tumor tissues and adjacent tissues were extracted from The Cancer Genome Atlas (TCGA) database. Seven BRD genes (KAT2A, KAT2B, SP140, BRD9, BRPF3, SMARCA2, and EP300) were searched by using LASSO Cox regression and the model with prognostic risk integration. The patients were divided into two groups: high risk and low risk. The combined analysis of these seven BRD genes showed a significant association with the high-risk groups and lower overall survival (OS). This analysis demonstrated that total survival could be predicted well in the low-risk group according to the time-dependent receiver operating characteristic (ROC) curve. The prognosis was determined to be consistent with that obtained using an independent dataset from TCGA. The relevant biological functions were identified using Gene Set Enrichment Analysis (GSEA). In summary, this study provides an optimized survival prediction model and promising data resources for further research investigating the role of the expression of BRD genes in KIRC.

scholarly journals Establishment and Validation of a Prognostic Risk Model for Autophagy-Related Genes in Clear Cell Renal Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Wenkai Han ◽  
Xiaoyan Xu ◽  
Kai Che ◽  
Guofeng Ma ◽  
Danxia Li ◽  
...  
Keyword(s):  
High Risk ◽  
Prognostic Factor ◽  
Cell Carcinoma ◽  
Risk Model ◽  
Clear Cell ◽  
Risk Group ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
High Risk Group ◽  
Low Risk

Background. Autophagy plays an essential role in tumorigenesis. At present, due to the unclear role of autophagy in renal clear cell carcinoma, we studied the potential value of autophagy-related genes (ARGs) in renal clear cell carcinoma (ccRCC). Methods. We obtained all ccRCC data from The Cancer Genome Atlas (TCGA). We extracted the expression data of ARGs for difference analysis and carried out biological function analysis on the different results. The autophagy risk model was constructed. The 5-year survival rate was assessed using the model, and the predictive power of the model was evaluated from multiple perspectives. Cox regression analysis was use to assess whether the model could be an independent prognostic factor. Finally, the correlation between the model and clinical indicators is analyzed. Results. The patients were divided into the high-risk group and low-risk group according to the median of autophagy risk score, and the results showed that the prognosis of the low-risk group was better than that of a high-risk group. The validation results of external data sets show that our model has good predictive value for ccRCC patients. The model can be an independent prognostic factor. Finally, the results show that our model has a stable predictive ability. Conclusion. The autophagy gene model we constructed can be used as an excellent prognostic indicator for ccRCC. Our study provides the possibility of individualized and precise treatment for ccRCC patients.

scholarly journals Downregulation of PPA2 expression correlates with poor prognosis of kidney renal clear cell carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12086
Author(s):  
Wenbiao Zhu ◽  
Huiming Jiang ◽  
Shoucheng Xie ◽  
Huanqin Xiao ◽  
Qinghua Liu ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Survival Data ◽  
Poor Prognosis ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
External Validation ◽  
Renal Clear Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
Mesenchymal Transition ◽  
Cox Regression Analysis

Background Kidney renal clear cell carcinoma (KIRC) is the most common subtype of kidney cancer. Inorganic pyrophosphatase (PPA2) is an enzyme that catalyzes the hydrolysis of pyrophosphate to inorganic phosphate; few studies have reported its significance in cancers. Therefore, we aimed to explore the prognostic value of PPA2 in KIRC. Methods PPA2 expression was detected via immunohistochemistry in a tissue chip containing specimens from 150 patients with KIRC. We evaluated the correlation between PPA2 expression, clinicopathological characteristics, and survival. Data from online databases and another cohort (paraffin-embedded specimens from 10 patients with KIRC) were used for external validation. Results PPA2 expression was significantly lower in KIRC tissues than in normal renal tissues (p < 0.0001). Low expression of PPA2 was significantly associated with a high histologic grade and poor prognosis. The differential expression of PPA2 was validated at the gene and protein levels. Multivariate Cox regression analysis showed that PPA2 expression was an independent prognostic factor in patients with KIRC. Gene set enrichment analysis suggested that decreased expression of PPA2 might be related to the epithelial-mesenchymal transition in KIRC. Conclusions Our study demonstrated that PPA2 is an important energy metabolism-associated biomarker correlated with a favorable prognosis in KIRC.

scholarly journals A 14 immune-related gene signature predicts clinical outcomes of kidney renal clear cell carcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10183
Author(s):  
Yong Zou ◽  
Chuan Hu
Keyword(s):  
Cell Carcinoma ◽  
Clinical Outcomes ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Clinical Prognosis ◽  
Immune Related Gene ◽  
Immune Related Genes

Kidney renal clear cell carcinoma (KIRC) is the leading cause of kidney cancer-related deaths. Currently, there are no studies in tumor immunology investigating the use of signatures as a predictor of overall survival in KIRC patients. Our study attempts to establish an immune-related gene risk signature to predict clinical outcomes in KIRC. A total of 528 patients from The Cancer Genome Atlas (TCGA) database were included in our analysis and randomly divided into training (n = 315) and testing sets (n = 213). We collected 1,534 immune-related genes from the Immunology Database and Analysis Portal as candidates to construct our signature. LASSO-COX was used to find gene models with the highest predictive ability. We used survival and Cox analysis to test the model’s independent prognostic ability. Univariate analysis identified 650 immune-related genes with prognostic abilities. After 1,000 iterations, we choose 14 of the most frequent and stable immune-related genes as our signature. We found that the signature was associated with M stage, T stage, and pathological staging. More importantly, the signature can independently predict clinical prognosis in KIRC patients. Gene Set Enrichment Analysis (GSEA) showed an association between our signature and critical metabolism pathways. Our research established a model based upon 14 immune-related genes that predicted the prognosis of KIRC patients based on tumor immune microenvironments.

scholarly journals Microenvironment-related gene TNFSF13B predicts poor prognosis in kidney renal clear cell carcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9453
Author(s):  
Mingzhe Jiang ◽  
Jiaxing Lin ◽  
Haotian Xing ◽  
Jun An ◽  
Jieping Yang ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Poor Prognosis ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Interaction Network ◽  
Renal Clear Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Potential Biomarker

Background Kidney renal clear cell carcinoma (KIRC) affects the genitourinary system. Although treatment of KIRC in early stages can be highly successful, this type of cancer is difficult to detect until later stages of disease that are less easily treatable. Previous studies have focused on tumor cells, but have ignored the contributions of the tumor microenvironment. Methods We analyzed KIRC gene expression data from The Cancer Genome Atlas with the ESTIMATE algorithm to identify differentially expressed genes. Through protein–protein interaction network analysis, we identified clusters and picked genes from the clusters for further analysis. Differential expression, Kaplan–Meier, and univariate Cox analyses were used to select prognostic biomarkers. Gene Set Enrichment Analysis (GSEA) and Tumor Immune Estimation Resource (TIMER) analysis were used to explore the immune characteristics of these genes as biomarkers. Results Through the ESTIMATE algorithm and other system biology tools, TNFSF13B was identified as a prognostic biomarker. TNFSF13B is highly expressed in tumors, and high expression of TNFSF13B leads to poor prognosis. Further GSEA and TIMER analysis revealed that the expression of TNFSF13B was related to the immune signaling pathway and lymphocyte infiltration. Our findings strongly suggest that TNFSF13B may be a potential biomarker or target related to the tumor microenvironment for KIRC.

scholarly journals A new prognostic risk model based on autophagy-related genes in kidney renal clear cell carcinoma

Bioengineered ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 7805-7819
Author(s):  
Guangzhen Wu ◽  
Yingkun Xu ◽  
Huayu Zhang ◽  
Zihao Ruan ◽  
Peizhi Zhang ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Risk Model ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Model Based

Delayed Pancreatic Metastasis of Renal Clear Cell Carcinoma

2013 ◽  
Vol 13 (2) ◽  
pp. 79-80
Author(s):  
Zane Simtniece ◽  
Gatis Kirsakmens ◽  
Ilze Strumfa ◽  
Andrejs Vanags ◽  
Maris Pavars ◽  
...  
Keyword(s):  
Abdominal Pain ◽  
Surgical Treatment ◽  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Primary Tumour ◽  
Renal Clear Cell Carcinoma ◽  
Pancreatic Metastasis ◽  
Distal Pancreatic Resection

Abstract Here, we report surgical treatment of a patient presenting with pancreatic metastasis (MTS) of renal clear cell carcinoma (RCC) 11 years after nephrectomy. RCC is one of few cancers that metastasise in pancreas. Jaundice, abdominal pain or gastrointestinal bleeding can develop; however, asymptomatic MTS can be discovered by follow-up after removal of the primary tumour. The patient, 67-year-old female was radiologically diagnosed with a clinically silent mass in the pancreatic body and underwent distal pancreatic resection. The postoperative period was smooth. Four months after the surgery, there were no signs of disease progression.

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