Gene expression analysis in clear cell renal cell carcinoma using gene set enrichment analysis for biostatistical management

2011 ◽  
Vol 108 (2b) ◽  
pp. E29-E35 ◽  
Author(s):  
Matthias Maruschke ◽  
D. Reuter ◽  
D. Koczan ◽  
O. W. Hakenberg ◽  
H.-J. Thiesen
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Gene Expression Analysis ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Cell Renal Cell Carcinoma

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 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 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 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 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.

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