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

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.

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Integrated analysis of the underlying immunomodulator and survival signature of STON1 gene in kidney renal clear cell carcinoma

10.21203/rs.3.rs-847345/v1 ◽

2021 ◽

Author(s):

Axiu Zheng ◽

Jianrong Bai ◽

Yanping Ha ◽

Bingshu Wang ◽

Yuan Zou ◽

...

Keyword(s):

Cell Carcinoma ◽

Risk Score ◽

Immune Cell ◽

Cox Regression ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

Renal Clear Cell Carcinoma ◽

Clinicopathological Characteristics ◽

Risk Scores ◽

Integrated Analysis

Abstract Background Stonin 1 (STON1) is an endocytic protein but its role in cancer remains unclear. Here, we investigated the role of STON1 in kidney renal clear cell carcinoma (KIRC). Methods We undertook bioinformatics analyses of a series of public databases to determine the expression and clinical significance of STON1 in KIRC and focused on STON1-related immunomodulator and survival signatures. A nomogram model integrating clinicopathological characteristics and risk scores for KIRC was established and validated. Results Through TGCA and GEO databases, STON1 mRNA was found to be significantly downregulated in KIRC compared with normal controls, and decreased STON1 was related to grade, TNM stage, distant metastasis, and vital status of KIRC. Furthermore, OncoLnc, UALCAN, Kaplan–Meier, and GEPIA2 analyses supported that KIRC patients with high STON1 expression had better overall survival. STON1 was positively associated with mismatch proteins including MLH1, PMS2, MSH2, MSH6 and EpCAM, and was negatively correlated with tumor mutational burden. Interestingly, arm-level deletion of STON1 was clearly related to the abundance of immune cells and the infiltration abundance in the majority of 26 immune cell types that were positively related to STON1 mRNA level in the TIMER database. The TISIDB database revealed 21 immunostimulators and 10 immunoinhibitors that were obviously related to STON1 in KIRC. In univariate and multivariate Cox regression analyses, CTLA4 , KDR , LAG3 , PDCD1 , HHLA2 , TNFRSF25 , and TNFSF14 were screened to establish a risk score model, and the low-risk group had a better prognosis for KIRC. Furthermore, a nomogram integrating clinicopathological characteristics and risk score had better accuracy and practicability in predicating the survival of KIRC patients. Conclusions Decreased STON1 expression in KIRC leads to clinical progression and poor survival. Mechanically, loss of STON1 is associated with the aberrant immune microenvironment in KIRC. Integrated clinicopathological characteristics and risk score derived from STON1 -related immunomodulators can aid the prediction of KIRC survival.

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

Disease Markers ◽

10.1155/2020/8841859 ◽

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.

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Development and validation of ferroptosis-related lncRNAs prognosis signatures in kidney renal clear cell carcinoma

Cancer Cell International ◽

10.1186/s12935-021-02284-1 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xiao-Liang Xing ◽

Zhi-Yong Yao ◽

Jialan Ou ◽

Chaoqun Xing ◽

Feng Li

Keyword(s):

Cell Carcinoma ◽

Cox Regression ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

Renal Clear Cell Carcinoma ◽

Assessment Model ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Risk Scores ◽

Non Coding Rnas

Abstract Background Ferroptosis is a recently recognised new type of cell death which may be a potential target for cancer therapy. In the present study, we aimed to screen ferroptosis-related differentially expressed long non-coding RNAs as biomarkers to predict the outcome of kidney renal clear cell carcinoma. Methods RNAseq count data and corresponding clinical information were obtained from the Cancer Genome Atlas database. Lists of ferroptosis-related genes and long non-coding RNAs were obtained from the FerrDb and GENCODE databases, respectively. The candidate prognostic signatures were screened by Cox regression analyses and least absolute shrinkage and selection operator analyses. Results Three ferroptosis-related long non-coding RNAs (DUXAP8, LINC02609, and LUCAT1) were significantly correlated with the overall survival of kidney renal clear cell carcinoma independently. Kidney renal clear cell carcinoma patients with high-risk values displayed worse OS. Meanwhile, the expression of these three ferroptosis-related long non-coding RNAs and their risk scores were significantly correlated with clinicopathological features. Principal component analyses showed that patients with kidney renal clear cell carcinoma have differential risk values were well distinguished by the three ferroptosis-related long non-coding RNAs. Conclusions The present study suggests that the risk assessment model constructed by these three ferroptosis-related long non-coding RNAs could accurately predict the outcome of kidney renal clear cell carcinoma. We also provide a novel perspective for cancer prognosis screening.

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Bioinformatics Analysis of the Prognostic and Biological Significance of ZDHHC-Protein Acyltransferases in Kidney Renal Clear Cell Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2020.565414 ◽

2020 ◽

Vol 10 ◽

Author(s):

Zhuang Liu ◽

Chang Liu ◽

Mingming Xiao ◽

Yamei Han ◽

Siyue Zhang ◽

...

Keyword(s):

Cell Carcinoma ◽

Poor Prognosis ◽

Immune Cell ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

Biological Significance ◽

Renal Clear Cell Carcinoma ◽

Common Type ◽

Covalent Attachment ◽

Abnormal Expression

ZDHHC-protein acyltransferases (ZDHHCs) are a family of 23 signature Asp-His-His-Cys (DHHC) domain-containing enzymes that mediate palmitoylation by covalent attachment of the 16-carbon fatty acid palmitate to thiol groups of specific cysteine residues in substrate proteins. Emerging evidence has shown abnormal expression of ZDHHCs in a variety of disease states, including cancer. Kidney renal clear cell carcinoma (KIRC) is the eighth most common type of cancer, which accounts for the majority of malignant kidney tumors. However, there are currently no effective therapeutic targets or biomarkers for clinical treatment and prognosis in KIRC. In this study, we first analyzed the expression pattern of the 23 ZDHHCs in KIRC using TCGA and GEPIA database, and found that the expression of ZDHHC2, 3, 6, 14, 15, 21, and 23 was significantly down-regulated whereas the expression of ZDHHC9, 17, 18, 19 and 20 was significantly up-regulated in KIRC patient tissues vs. normal tissues. And the expression of ZDHHC2, 3, 6, 9, 14, 15, and 21 in tumors decreased with the increase of the pathological stage of KIRC patients. Notably, KIRC patients with decreased expression of ZDHHC3, 6, 9, 14, 15, 17, 20, 21, 23 and increased expression of ZDHHC19 were significantly associated with poor prognosis. Further, we found that there was a significant correlation between ZDHHC3, 6, 9, 14, 15, 17, 19, 20, 21, 23 expressions and immune cell infiltration. Besides, high mRNA expression was the most common type of gene alteration and there was a high correlation among the expression of ZDHHC6, 17, 20 and 21. Finally, function prediction indicated that the immune or metabolic disorders or the activation of oncogenic signaling pathways caused by abnormal expression of these ZDHHCs may be important mechanisms of tumor progression and poor prognosis in patients with KIRC. Our results may provide novel insight for identifying tumor markers or molecular targets for the treatment of KIRC.

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

PeerJ ◽

10.7717/peerj.9453 ◽

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.

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

PeerJ ◽

10.7717/peerj.8205 ◽

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.

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

10.21203/rs.3.rs-761157/v1 ◽

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.

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LY96 Upregulation Promotes Kidney Renal Clear Cell Carcinoma (KIRC)

10.21203/rs.3.rs-154342/v1 ◽

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.

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

10.21203/rs.3.rs-471905/v1 ◽

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.

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Tumor antigens and immune subtypes guided mRNA vaccine development for kidney renal clear cell carcinoma

Molecular Cancer ◽

10.1186/s12943-021-01465-w ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Hang Xu ◽

Xiaonan Zheng ◽

Shiyu Zhang ◽

Xianyanling Yi ◽

Tianyi Zhang ◽

...

Keyword(s):

Cell Carcinoma ◽

Topoisomerase Ii ◽

Tumor Antigens ◽

Immune Cell ◽

Vaccine Development ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

Renal Clear Cell Carcinoma ◽

Survival Outcomes ◽

Topoisomerase Ii Alpha

AbstractCurrent treatment strategy for kidney renal clear cell carcinoma (KIRC) is limited. Tumor-associated antigens, especially neoantigen-based personalized mRNA vaccines represent new strategies and manifest clinical benefits in solid tumors, but only a small proportion of patients could benefit from them, which prompts us to identify effective antigens and suitable populations to facilitate mRNA vaccines application in cancer therapy. Through performing expression, mutation, survival and correlation analyses in TCGA-KIRC dataset, we identified four genes including DNA topoisomerase II alpha (TOP2A), neutrophil cytosol factor 4 (NCF4), formin-like protein 1 (FMNL1) and docking protein 3 (DOK3) as potential KIRC-specific neoantigen candidates. These four genes were upregulated, mutated and positively associated with survival and antigen-presenting cells in TCGA-KIRC. Furthermore, we identified two immune subtypes, named renal cell carcinoma immune subtype 1 (RIS1) and RIS2, of KIRC. Distinct clinical, molecular and immune-related signatures were observed between RIS1 and RIS2. Patients of RIS2 had better survival outcomes than those of RIS1. Further comprehensive immune-related analyses indicated that RIS1 is immunologically “hot” and represent an immunosuppressive phenotype, whereas RIS2 represents an immunologically “cold” phenotype. RIS1 and RIS2 also showed differential features with regard to tumor infiltrating immune cells and immune checkpoint-related genes. Moreover, the immune landscape construction identified the immune cell components of each KIRC patient, predicted their survival outcomes, and assisted the development of personalized mRNA vaccines. In summary, our study identified TOP2A, NCF4, FMNL1 and DOK3 as potential effective neoantigens for KIRC mRNA vaccine development, and patients with RIS2 tumor might benefit more from mRNA vaccination.

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