scholarly journals The CSRNP Gene Family Serves as a Prognostic Biomarker in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Huaru Zhang ◽  
Xiaofu Qiu ◽  
Guosheng Yang
Keyword(s):  
Renal Cell Carcinoma ◽  
Gene Family ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Value ◽  
Clear Cell ◽  
Prognostic Biomarker ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Renal Cell Carcinoma

The cysteine-serine-rich nuclear protein (CSRNP) family has prognostic value for various cancers. However, the association between this proteins and prognosis of clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to determine the prognostic value of the CSRNP family for patients with ccRCC. Therefore, the gene expression profiling interactive analysis database was used to analyze the mRNA expression of CSRNP family members (CSRNPs) in relation with survival. Combined and independent prognostic values of CSRNPs were evaluated using SurvExpress and multivariate Cox regression analyses, respectively. Potential signaling pathways impacted by CSRNPs were evaluated using Metascape. Associations between the CSRNP family and immunocyte infiltration were determined from single-sample gene set enrichment analysis. Both cBioPortal and MethSurv were used to explore whether genomic and epidemic alterations might influence prognosis. We found that when both CSRNP1 and CSRNP3 had a low expression, patients with ccRCC had a worse overall survival (OS). Therefore, a prognostic signature was constructed as follows: risk score = −0.224 × expmRNA ofCSRNP1 + 0.820 × expmRNA ofCSRNP2 − 1.428 × expmRNA ofCSRNP3. We found that OS was worse in patients from the high- than from the low-risk groups (AUC = 0.69). Moreover, this signature was an independent predictor after adjusting for clinical features. Functional enrichment analysis positively associated CSRNPs with the acute inflammatory response and humoral immune response pathways. This was validated by correlating each CSRNP with 28 types of immunocytes in tumor and normal tissues. A higher expression of CSRNP1 and CSRNP3 was associated with a better prognosis in both the high- and low-mutant burden groups. Cg19538674, cg07772537, and cg07811002 of CSRNP1, CSRNP2, and CSRNP3, respectively, were the predominant DNA methylation sites affecting OS. The CSRNP gene family signature may serve as a prognostic biomarker for predicting OS in patients with ccRCC. The association between CSRNPs and immune infiltration might offer future clinical treatment options.

scholarly journals A novel five-zinc finger-related-gene signature related to tumor immune microenvironment allows for treatment stratification and predicts prognosis in clear cell renal cell carcinoma patients

2021 ◽  
Author(s):  
Feilong Zhang ◽  
Jiyue Wu ◽  
Jiandong Zhang ◽  
Peng Cao ◽  
Zejia Sun ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Zinc Finger ◽  
Renal Cell ◽  
Drug Sensitivity ◽  
Cox Regression ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Renal Cell Carcinoma

Abstract Background Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent renal malignant tumors, which survival rate and quality of life of ccRCC patients are not satisfactory. Therefore, identification of prognostic biomarkers of ccRCC patients will contribute to early and accurate clinical intervention and treatment, and then improve their prognosis. Methods We downloaded the original expression data of mRNAs from The Cancer Genome Atlas database and the zinc finger(ZNF)-related genes (ZRGs) from UniProt online database. Differentially expressed ZRGs (DE-ZRGs) was screened from tumor and adjacent nontumor tissues and functional enrichment analysis was conducted out. A five-ZRG signature were constructed by univariate Cox regression, least absolute shrinkage and selection operator and multivariate Cox regression. Furthermore, we screened out independent prognosis-related factors to build a nomogram by univariate and multivariate Cox regression. Potential biological pathways of five ZRGs were analyzed by Gene Set Enrichment Analysis (GSEA). Then, we further quantitatively analyze immune infiltration and evaluate tumor microenvironment by single sample GSEA. Finally, drug sensitivity of ccRCC patients was analyzed by the Genomics of Drug Sensitivity in Cancer database. Results TRIM59, VAV3, ZNF189, AGAP9 and PYGO1 were screened to be significantly associated with the prognosis of ccRCC patients. Through incorporated risk score and clinical parameters, we constructed a nomogram, which showed a good prognostic performance for ccRCC patients.

scholarly journals Data Mining of Prognostic Microenvironment-Related Genes in Clear Cell Renal Cell Carcinoma: A Study with TCGA Database

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Bin Chen ◽  
Wei Chen ◽  
Jing Jin ◽  
Xueping Wang ◽  
Yifang Cao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Value ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Cancer Prognosis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent kidney malignancies. The tumor microenvironment (TME) is highly related to the oncogenesis, progress, and prognosis of ccRCC. The aim of this study was to infer the level of infiltrating stromal and immune cells and assess the prognostic value of them. The gene expression profile was obtained from TCGA and used for calculating the stromal and immune scores. Based on a cut-off value, patients were divided into low- and high-stromal/immune score groups. Survival analysis was performed to evaluate the prognostic value of stromal and immune scores. Moreover, differentially expressed genes (DEGs) that are highly related to TME were determined and applied for functional enrichment analysis and protein-protein interaction (PPI) network. The Kaplan-Meier plot demonstrated that patients with high-immune scores and stromal scores had poorer clinical outcome. In addition, a total of 89 DEGs were identified and mainly involved in 5 pathways. The top 5 degree genes were extracted from the PPI network; among them, IL10 and XCR1 were highly associated with prognosis of ccRCC. The results of the present study demonstrated that ESTIMATE algorithm-based stromal and immune scores may be a credible indicator of cancer prognosis and IL10 along with XCR1 may be a potential key regulator for the TME of ccRCC.

Gene set enrichment analysis and ingenuity pathway analysis of metastatic clear cell renal cell carcinoma cell line

2016 ◽  
Vol 311 (2) ◽  
pp. F424-F436 ◽  
Author(s):  
Mohammed I. Khan ◽  
Konrad J. Dębski ◽  
Michał Dabrowski ◽  
Anna M. Czarnecka ◽  
Cezary Szczylik
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cell Line ◽  
Pathway Analysis ◽  
Renal Cell ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Cell Renal Cell Carcinoma

In recent years, genome-wide RNA expression analysis has become a routine tool that offers a great opportunity to study and understand the key role of genes that contribute to carcinogenesis. Various microarray platforms and statistical approaches can be used to identify genes that might serve as prognostic biomarkers and be developed as antitumor therapies in the future. Metastatic renal cell carcinoma (mRCC) is a serious, life-threatening disease, and there are few treatment options for patients. In this study, we performed one-color microarray gene expression (4×44K) analysis of the mRCC cell line Caki-1 and the healthy kidney cell line ASE-5063. A total of 1,921 genes were differentially expressed in the Caki-1 cell line (1,023 upregulated and 898 downregulated). Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA) approaches were used to analyze the differential-expression data. The objective of this research was to identify complex biological changes that occur during metastatic development using Caki-1 as a model mRCC cell line. Our data suggest that there are multiple deregulated pathways associated with metastatic clear cell renal cell carcinoma (mccRCC), including integrin-linked kinase (ILK) signaling, leukocyte extravasation signaling, IGF-I signaling, CXCR4 signaling, and phosphoinositol 3-kinase/AKT/mammalian target of rapamycin signaling. The IPA upstream analysis predicted top transcriptional regulators that are either activated or inhibited, such as estrogen receptors, TP53, KDM5B, SPDEF, and CDKN1A. The GSEA approach was used to further confirm enriched pathway data following IPA.

scholarly journals GNRH1 and LTB4R might be novel immune-related prognostic biomarkers in clear cell renal cell carcinoma (ccRCC)

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hua-Hui Wu ◽  
Xin Yan ◽  
Zhao Chen ◽  
Guo-Wei Du ◽  
Xiao-Jie Bai ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Leukotriene B4 ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Biomarkers ◽  
Cell Renal Cell Carcinoma

Abstract Background Clear cell renal cell carcinoma (ccRCC) occupied most of renal cell carcinoma (RCC), which associated with poor prognosis. The purpose of this study is to screen novel and prognostic biomarkers for patients with ccRCC. Methods and results Firstly, Gene Expression Omnibus database was used to collect microarray data for weighted gene co-expression network construction. Gene modules related to prognosis which interest us most were picked out. 90 hub genes were further chosen in the key modules, two of which including gonadotropin releasing hormone 1 (GNRH1) and leukotriene B4 receptor (LTB4R) were screened and validated as immune-related prognostic biomarkers. Based on several public databases and ccRCC tissues collected by ourselves, we performed survival analysis, spearman correlation analysis, receiver operating characteristic (ROC) analysis, quantitative real-time PCR (qRT-PCR), western blotting, immunofluorescence (IF) and immunohistochemistry (IHC) staining for the validation of immune-related prognostic biomarkers. We further explored the relationship between immune-related prognostic biomarker expressions and immunocytes. Finally, gene set enrichment analysis (GSEA) demonstrated that the two immune-related prognostic biomarkers were significantly correlated with cell cycle. Conclusions Generally speaking, the present study has identified two novel prognostic biomarkers for patients with ccRCC, which showed strong correlation with prognosis of patients with ccRCC, could further be used as potential prognostic biomarkers in ccRCC.

scholarly journals RNA Sequencing Reveals Upregulation of RUNX1-RUNX1T1 Gene Signatures in Clear Cell Renal Cell Carcinoma

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Zuquan Xiong ◽  
Hongjie Yu ◽  
Yan Ding ◽  
Chenchen Feng ◽  
Hanming Wei ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Hypoxia Inducible Factor ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Renal Cell Carcinoma ◽  
Tissue Samples ◽  
Gene Set

In the past few years, therapies targeted at the von Hippel-Lindau (VHL) and hypoxia-inducible factor (HIF) pathways, such as sunitinib and sorafenib, have been developed to treat clear cell renal cell carcinoma (ccRCC). However, the majority of patients will eventually show resistance to antiangiogenesis therapies. The purpose of our study was to identify novel pathways that could be potentially used as targets for new therapies. Whole transcriptome sequencing (RNA-Seq) was conducted on eight matched tumor and adjacent normal tissue samples. A novel RUNX1-RUNX1T1 pathway was identified which was upregulated in ccRCC through gene set enrichment analysis (GSEA). We also confirmed the findings based on previously published gene expression microarray data. Our data shows that upregulated of the RUNX1-RUNX1T1 gene set maybe an important factor contributing to the etiology of ccRCC.

scholarly journals Pyroptosis Regulators and Tumor Microenvironment Infiltration Characterization in Clear Cell Renal Cell Carcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Xi Zhang ◽  
Xiyi Wei ◽  
Yichun Wang ◽  
Shuai Wang ◽  
Chengjian Ji ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Gene Set Enrichment ◽  
Cell Renal Cell Carcinoma ◽  
Gene Set

BackgroundIt is well known that chronic inflammation can promote the occurrence and progression of cancer. As a type of proinflammatory death, pyroptosis can recast a suitable microenvironment to promote tumor growth. However, the potential role of pyroptosis in clear cell renal cell carcinoma (ccRCC) remains unclear.MethodsThe transcriptome expression profile and mutation profile data of ccRCC with clinical characteristics included in this study were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering was used for clustering. Gene set enrichment analysis (GSEA) analysis were applied to evaluate the biological mechanisms. Single sample gene set enrichment analysis (ssGSEA) was applied for evaluating the proportion of various immune infiltrating cells. The ESTIMATE algorithm was involved to compute the immune microenvironment scores.ResultsAmong the 17 pyroptosis regulators, a total of 15 pyroptosis regulators were differential expressed between tumor and normal tissues, in which 12 of them emerged strong correlations with prognoses. According to the pyroptosis components, the ccRCC patients were divided into four pyroptosis subtypes with different clinical, molecular, and pathway characteristics. Compared with other clusters, cluster B showed the pyroptosis heat phenotype, while cluster D represented the pyroptosis cold phenotype with poor overall survival. In addition, we performed principal component analysis (PCA) on the differential genes between clusters to construct the pyroptosis index. Furthermore, the pyroptosis index was significantly correlated with survival in different tumor mutation statuses and different grades and stages. Besides, the expression of pyroptosis-related regulators was related to the infiltration of immune cells and the expression of immune checkpoints, among which AIM2 was considered as the most significant immune-related pyroptosis regulator. Ultimately, we found that AIM2 was related to the immune activation pathway and was significantly overexpressed in tumor tissues.ConclusionThis study revealed that pyroptosis regulators and pyroptosis index played an important role in the development and prognoses of ccRCC. Moreover, AIM2 can be used as a predictor of the response of immunotherapy. Assessing the pyroptosis patterns may help evaluate the tumor status and guide immunotherapy strategies.

scholarly journals GNRH1 and LTB4R Might Be Novel Immune-Related Prognostic Biomarkers in Clear Cell Renal Cell Carcinoma (ccRCC)

2021 ◽  
Author(s):  
Hua-Hui Wu ◽  
Xin Yan ◽  
Zhao Chen ◽  
Guo-Wei Du ◽  
Xiao-Jie Bai ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Biomarkers ◽  
Cell Renal Cell Carcinoma ◽  
Gene Modules

Abstract Background: Clear cell renal cell carcinoma (ccRCC) occupied most of renal cell carcinoma (RCC), which associated with poor prognosis. The purpose of this study is to screen novel and prognostic biomarkers for patients with ccRCC. Methods and Results: Firstly, Gene Expression Omnibus database was used to collect microarray data for weighted gene co-expression network construction. Gene modules related to prognosis which interest us most were picked out. 90 hub genes were further chosen in the key modules, two of which including GNRH1 and LTB4R were screened and validated as immune-related prognostic biomarkers. Several methods including survival analysis, spearman correlation analysis, HPA, One-way ANOVA and ROC analysis were used for the validation of immune-related prognostic biomarkers. We further explored the relationship between immune-related prognostic biomarker expressions and immunocytes. Finally, gene set enrichment analysis (GSEA) demonstrated that the two immune-related prognostic biomarkers were significantly correlated with cell cycle. Conclusions: Generally speaking, the present study has identified two novel prognostic biomarkers for patients with ccRCC, which showed strong correlation with prognosis of patients with ccRCC, could further be used as potential prognostic biomarkers in ccRCC.

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