scholarly journals Reduced GRAMD1C expression correlates to poor prognosis and immune infiltrates in kidney renal clear cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8205
Author(s):  
Haiyan Hao ◽  
Ziheng Wang ◽  
Shiqi Ren ◽  
Hanyu Shen ◽  
Hua Xian ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Signaling Pathway ◽  
Poor Prognosis ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Wnt Signaling Pathway ◽  
Rna Degradation ◽  
Renal Clear Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Underlying Mechanisms

There has been an increase in the mortality rate and morbidity of kidney cancer (KC) with kidney renal clear cell carcinoma (KIRC) being the most common subtype of KC. GRAMD1C (GRAM Domain Containing 1C) has not been reported to relate to prognosis and immunotherapy in any cancers. Using bioinformatics methods, we judged the prognostic value of GRAMD1C expression in KIRC and investigated the underlying mechanisms of GRAMD1C affecting the overall survival of KIRC based on data downloaded from The Cancer Genome Atlas (TCGA). The outcome revealed that reduced GRAMD1C expression could be a promising predicting factor of poor prognosis in kidney renal clear cell carcinoma. Meanwhile, GRAMDIC expression was significantly correlated to several tumor-infiltrating immune cells (TIICs), particularly the regulatory T cells (Tregs). Furthermore, GRAMD1C was most significantly associated with the mTOR signaling pathway, RNA degradation, WNT signaling pathway, toll pathway and AKT pathway in KIRC. Thus, GRAMD1C has the potential to become a novel predictor to evaluate prognosis and immune infiltration for KIRC patients.

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 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.

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 LY96 Upregulation Promotes Kidney Renal Clear Cell Carcinoma (KIRC)

2021 ◽  
Author(s):  
Ji-li Xu ◽  
Yong Guo
Keyword(s):  
Transcription Factors ◽  
Cell Carcinoma ◽  
Dna Methyltransferase ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Related Factors ◽  
Beneficial Effects ◽  
Highly Correlated

Abstract Background: LY96 has been reported to be relevant with kidney inflammatory injury but the function of this gene in kidney renal clear cell carcinoma (KIRC) remains unknown.Methods: Various online tools were applied to analyze the roles of LY96 in KIRC using data from the Cancer Genome Atlas. Differential LY96 expression and overall survival (OS) based on different expression levels were analyzed through Oncomine and GEPIA tools. The alterations, related genes, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathways of LY96 were explored via cBioPortal and STRING database. LinkedOmics and Cistrome DB Toolkit were utilized to identify targets of kinase, miRNAs, and transcription factors. The relationship between LY96 and some associated genes or regulatory factors was displayed via GeneMANIA and TIMER tool. TISIDB revealed correlations between LY96 expression and immune-associated factors in the tumor microenvironment. Results: High LY96 expression level was observed in KIRC and associated with poor prognosis and diverse clinical characteristics. LY96 often amplified in KIRC and was mostly linked to the inflammatory response. Several highly correlated genes, kinase targets, transcription factors, and DNA methyltransferase that may interact with LY96 were all identified. Our study also demonstrated that various immune-related factors were relevant to LY96 in KIRC. Conclusions: Our study has shown the complex relationships between LY96 and KIRC from diverse angles. High LY96 expression had an adverse effect on the prognosis of KIRC. To find effective demethylation agents and transcription factors inhibitors targeting LY96 may have beneficial effects on the survival of KIRC patients.

scholarly journals Identification of Tumor Microenvironment-Related Genes in Kidney Renal Clear Cell Carcinoma Patients via Bioinformatic Analysis

2021 ◽  
Author(s):  
Rongjiong Zheng ◽  
Yaosen SHao ◽  
Mingming Wang ◽  
Yeli Tang ◽  
Meiling Hu
Keyword(s):  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Renal Clear Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment

Abstract BackgroundTumor microenvironment has been implicated in the development and progression of cancers. However, the prognostic significance of tumor microenvironment-related genes in kidney renal clear cell carcinoma (KIRC) remains unclear. MethodsIn this study, we obtained and analyzed gene expression profiles from The Cancer Genome Atlas database. Stromal and immune scores were calculated based on the ESTIMATE algorithm. ResultsIn the discovery series of 537 patients, we identified a list of differentially expressed genes which was significantly associated with prognosis in KIRC patients. Protein-protein interaction networks and functional enrichment analysis were both performed, indicating that these identified genes were related to the immune response. ConclusionsThe tumor microenvironment-related genes could serve as the potential biomarkers for KIRC.

OSkirc: a web tool for identifying prognostic biomarkers in kidney renal clear cell carcinoma

2019 ◽  
Vol 15 (27) ◽  
pp. 3103-3110 ◽  
Author(s):  
Longxiang Xie ◽  
Qiang Wang ◽  
Yifang Dang ◽  
Linna Ge ◽  
Xiaoxiao Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Carcinoma ◽  
Web Application ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
P Value ◽  
Survival Plot

Aim: To develop a free and quick analysis online tool that allows users to easily investigate the prognostic potencies of interesting genes in kidney renal clear cell carcinoma (KIRC). Patients & methods: A total of 629 KIRC cases with gene expression profiling data and clinical follow-up information are collected from public Gene Expression Omnibus and The Cancer Genome Atlas databases. Results: One web application called Online consensus Survival analysis for KIRC (OSkirc) that can be used for exploring the prognostic implications of interesting genes in KIRC was constructed. By OSkirc, users could simply input the gene symbol to receive the Kaplan–Meier survival plot with hazard ratio and log-rank p-value. Conclusion: OSkirc is extremely valuable for basic and translational researchers to screen and validate the prognostic potencies of genes for KIRC, publicly accessible at http://bioinfo.henu.edu.cn/KIRC/KIRCList.jsp

scholarly journals Abnormal Expression and Prognostic Significance of EPB41L1 in Kidney Renal Clear Cell Carcinoma Based on Data Mining

2020 ◽  
Author(s):  
Taotao Liang ◽  
Siyao Sang ◽  
Qi Shao ◽  
Zhichao Deng ◽  
Ting Wang ◽  
...  
Keyword(s):  
Data Mining ◽  
Cell Adhesion ◽  
Cell Carcinoma ◽  
Cancer Cell ◽  
Poor Prognosis ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Renal Clear Cell Carcinoma

Abstract Background: EPB41L1 gene (erythrocyte membrane protein band 4.1 like 1) encodes the protein 4.1N, a member of 4.1 family, playing a vital role in cell adhesion and migration, which is associated with the malignant progression of various human cancers. However, the expression and prognostic significance of EPB41L1 in kidney renal clear cell carcinoma (KIRC) remains to be investigated.Methods: In this study, we collected the mRNA expression of EPB41L1 in KIRC through the Oncomine platform, and used the HPA database to perform the pathological tissue immunohistochemistry in patients. Then, the sub-groups and prognosis of KIRC were performed by UALCAN and GEPIA web-tool, respectively. Further, the mutation of EPB41L1 in KIRC were analyzed by c-Bioportal. The co-expression genes of EPB41L1 in KIRC were displayed from the LinkedOmics database, and function enrichment analysis was used by LinkFinder module in LinkedOmics. Co-expression gene network was constructed through the STRING database, and the MCODE plug-in of which was used to build the gene modules, both of them were visualized by Cytoscape software. Finally, the top modular genes in the same patient cohort were constructed through data mining in TCGA by using the UCSC Xena browser.Results: The results indicated that EPB41L1 was down-expressed in KIRC, leading to a poor prognosis. Moreover, there is a mutation in the FERM domain of EPB41L1, but it has no significant effect on the prognosis of KIRC. The co-expressed genes of EPB41L1 was associated with cell adhesion. Further analysis suggested that EPB41L1 and amyloid beta precursor protein (APP) were coordinated to regulated cancer cell adhesion, thereby increasing the incidence of cancer cell metastasis and tumor invasion.Conclusions: In summary, EPB41L1 is constantly down-expressed in KIRC tissues, resulting a poor prognosis. Therefore, we suggest that it can be an effective biomarker for the diagnosis of KIRC.

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