scholarly journals Analyzing and validating the prognostic value and immune microenvironment of clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Jingwei Ke ◽  
Jie Chen ◽  
Xin Liu
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clinical Characteristics ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Cell Renal Cell Carcinoma ◽  
Significant Difference

Abstract Background: There is still controversy regarding immunotherapy biomarkers. Therefore, we aimed to identify prognostic biomarkers related to immunotherapy for clear cell renal cell carcinoma (ccRCC).Methods: Fragments Per Kilobase Million (FPKM) data and clinical characteristics for ccRCC patients from The Cancer Genome Atlas (TCGA) database were downloaded. Unsupervised consensus clustering analysis was performed to divide patients into different immune subgroups according to their single-sample gene set enrichment analysis (ssGSEA) scores. Then, we validated the differences in immune cell infiltration, prognosis, clinical characteristics and expression levels of HLA and immune checkpoint genes between different immune subgroups. Weighted gene coexpression network analysis (WGCNA) was used to identify the significant modules and hub genes that were related to the immune subgroups. A nomogram was established to predict the overall survival (OS) outcomes after independent prognostic factors were identified by least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses.Results: Five clusters (immune subgroups) were identified. There was no significant difference in age, sex or N stage. And there were significant differences in race, T stage, M stage, grade, prognosis and tumor microenvironment. HLA gene families and CTLA4 showed significant differences between the five clusters, while PD1 and PDL1 did not. The red module was significant, and 14 hub genes were obtained. In addition, the nomogram containing LAG3 and GZMK accurately predicted OS outcomes of ccRCC patients.Conclusion: LAG3 and GZMK are strongly related to immunity and may provide suggestions for ccRCC immunotherapy.

scholarly journals N6-Methyladenosine-Related Long Non-coding RNA Signature Associated With Prognosis and Immunotherapeutic Efficacy of Clear-Cell Renal Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Tianming Ma ◽  
Xiaonan Wang ◽  
Jiawen Wang ◽  
Xiaodong Liu ◽  
Shicong Lai ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differential Expression ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis

Increasing evidence suggests that N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) play important roles in cancer progression and immunotherapeutic efficacy in clear-cell renal cell carcinoma (ccRCC). In this study, we conducted a comprehensive ccRCC RNA-seq analysis using The Cancer Genome Atlas data to establish an m6A-related lncRNA prognostic signature (m6A-RLPS) for ccRCC. Forty-four prognostic m6A-related lncRNAs (m6A-RLs) were screened using Pearson correlation analysis (|R| > 0.7, p < 0.001) and univariable Cox regression analysis (p < 0.01). Using consensus clustering, the patients were divided into two clusters with different overall survival (OS) rates and immune status according to the differential expression of the lncRNAs. Gene set enrichment analysis corroborated that the clusters were enriched in immune-related activities. Twelve prognostic m6A-RLs were selected and used to construct the m6A-RLPS through least absolute shrinkage and selection operator Cox regression. We validated the differential expression of the 12 lncRNAs between tumor and non-cancerous samples, and the expression levels of four m6A-RLs were further validated using Gene Expression Omnibus data and Lnc2Cancer 3.0 database. The m6A-RLPS was verified to be an independent and robust predictor of ccRCC prognosis using univariable and multivariable Cox regression analyses. A nomogram based on age, tumor grade, clinical stage, and m6A-RLPS was generated and showed high accuracy and reliability at predicting the OS of patients with ccRCC. The prognostic signature was found to be strongly correlated to tumor-infiltrating immune cells and immune checkpoint expression. In conclusion, we established a novel m6A-RLPS with a favorable prognostic value for patients with ccRCC. The 12 m6A-RLs included in the signature may provide new insights into the tumorigenesis and allow the prediction of the treatment response of ccRCC.

scholarly journals Functional Assessment of Four Novel Immune-Related Biomarkers in the Pathogenesis of Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Daojun Lv ◽  
Xiangkun Wu ◽  
Ming Wang ◽  
Wenzhe Chen ◽  
Shuxin Yang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Rank Aggregation ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Cell Renal Cell Carcinoma ◽  
Network Analyses

BackgroundClear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma whose pathogenesis is not well understood. We aimed at identifying novel immune-related biomarkers that could be valuable in the diagnosis and prognosis of ccRCC.MethodsThe Robust Rank Aggregation (RRA) method was used to integrate differently expressed genes (DEGs) of 7 Gene Expression Omnibus (GEO) datasets and obtain robust DEGs. Weighted gene co-expression network analyses (WGCNA) were performed to identify hub genes associated with clinical traits in The Cancer Genome Atlas (TCGA) database. Comprehensive bioinformatic analyses were used to explore the role of hub genes in ccRCC.ResultsFour hub genes IFI16, LMNB1, RHBDF2 and TACC3 were screened by the RRA method and WGCNA. These genes were found to be up-regulated in ccRCC, an upregulation that could be due to their associations with late TNM stages and tumor grades. The Receiver Operating Characteristic (ROC) curve and Kaplan-Meier survival analysis showed that the four hub genes had great diagnostic and prognostic values for ccRCC, while Gene Set Enrichment Analysis (GSEA) showed that they were involved in immune signaling pathways. They were also found to be closely associated with multiple tumor-infiltrating lymphocytes and critical immune checkpoint expressions. The results of Quantitative Real-time PCR (qRT-PCR) and immunohistochemical staining (IHC) analysis were consistent with bioinformatics analysis results.ConclusionThe four hub genes were shown to have great diagnostic and prognostic values and played key roles in the tumor microenvironment of ccRCC.

scholarly journals High Expression of CDCA7 Predicts Poor Prognosis in Clear Cell Renal Cell Carcinoma and Its Associations With Immunity

2021 ◽  
Author(s):  
Shouyong Liu ◽  
Yi Wang ◽  
Chenkui Miao ◽  
Qianwei Xing ◽  
Zengjun Wang
Keyword(s):  
Renal Cell Carcinoma ◽  
Prognostic Factor ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Independent Prognostic Factor ◽  
Gene Set Enrichment Analysis ◽  
Regression Analyses ◽  
Cell Renal Cell Carcinoma

Abstract BackgroundCell division cycle-associated 7 (CDCA7), as a member of the cell division cycle associated family, was reported to be aberrantly expressed in both solid tumors and hematological tumors, suggesting its essential role in promoting tumorigenesis. Hence, we aimed to explore its comprehensive role of overall survival (OS) in clear cell renal cell carcinoma (ccRCC) and emphasis on immunity.MethodsThe RNA sequencing data and corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) was adopted to explore CDCA7 associated signaling pathways. Univariate and multivariate Cox regression analyses were carried out to assess independent prognostic factors. Furthermore, roles of CDCA7 in human immunity were also investigated.ResultsOur results suggested that CDCA7 was overexpressed in ccRCC and its elevated expression was related to shorter OS (P<0.01). Univariate and multivariate Cox regression analyses identified CDCA7 as an independent prognostic factor (both P<0.05). The prognostic nomogram integrating CDCA7 expression level and clinicopathologic variables was constructed to predict 1-, 3- and 5-year OS. GSEA indicated that high CDCA7 expression was related to the apoptosis pathway, cell cycle pathway, JAK-STAT pathway, NOD like receptor pathway, P53 pathway, T cell receptor pathway and toll like receptor pathway, etc. As for immunity, CDCA7 was significantly associated with tumor mutational burden (TMB), immune checkpoint molecules, tumor microenvironment and immune infiltration.ConclusionsCDCA7 could serve as an independent prognostic factor for ccRCC and it was closely related to immunity

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.

Screening and identification of novel promoter signatures in clear cell renal cell carcinoma metastasis.

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 737-737
Author(s):  
Yuan-Yuan Qu ◽  
Xi Tian ◽  
Wenhao Xu ◽  
Aihemutaijiang Anwaier ◽  
Dingwei Ye ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Cell Renal Cell Carcinoma

737 Background: Clear cell renal cell carcinoma (ccRCC) patient usually face aggressive progression when metastasis occurs. Therefore, in-depth investigation is needed to elucidate underlying mechanisms behind the metastasis of ccRCC to promote therapeutic benefits.This study aims to explore and investigate prognostic gene expression profiles based on multi-cohorts. Methods: Three microarray datasets were obtained from the Gene Expression Omnibus (GEO) database to screen and identify differentially expressed genes (DEGs) according to normalization annotation information. A total of 112 DEGs with functional enrichment were identified as candidate prognostic biomarkers. A protein–protein interaction network (PPI) of DEGs was developed, and the modules were analyzed using STRING and Cytoscape. Results: LASSO Cox regression suggested 31 significant involved genes, and 10 hub genes were identified as independent oncogenes in ccRCC patients. Distinct integrated scores of the hub genes mRNA expression showed statistical significance in predicting disease-free survival (DFS; p<0.001) and overall survival (OS; p<0.001) in TCGA and real-world cohorts. Meanwhile, ROC curves were constructed to validate specificity and sensitivity of the Cox regression penal to predict prognosis. The AUC index for the integrated genes scores was 0.758 for OS and 0.772 for DFS. Conclusions: In conclusion,the present study identifies DEGs and hub genes that may be involved in earlier recurrence and poor prognosis of ccRCC. The expression levels of ADAMTS9, C1S, DPYSL3, H2AFX, MINA, PLOD2, RUNX1, SLC19A1, TPX2 and TRIB3 are of high prognostic value, and may help us understand better the underlying carcinogenesis or progression of ccRCC.

scholarly journals Identification of Hub Genes Associated With Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Hao Huang ◽  
Ling Zhu ◽  
Chao Huang ◽  
Yi Dong ◽  
Liangliang Fan ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Rna Sequencing ◽  
Renal Cell ◽  
Clear Cell ◽  
Single Gene ◽  
Gene Set Enrichment Analysis ◽  
Cancer Type ◽  
Hub Genes ◽  
Cell Renal Cell Carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is a common genitourinary cancer type with a high mortality rate. Due to a diverse range of biochemical alterations and a high level of tumor heterogeneity, it is crucial to select highly validated prognostic biomarkers to be able to identify subtypes of ccRCC early and apply precision medicine approaches.MethodsTranscriptome data of ccRCC and clinical traits of patients were obtained from the GSE126964 dataset of Gene Expression Omnibus and The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) database. Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) screening were applied to detect common differentially co-expressed genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, survival analysis, prognostic model establishment, and gene set enrichment analysis were also performed. Immunohistochemical analysis results of the expression levels of prognostic genes were obtained from The Human Protein Atlas. Single-gene RNA sequencing data were obtained from the GSE131685 and GSE171306 datasets.ResultsIn the present study, a total of 2,492 DEGs identified between ccRCC and healthy controls were filtered, revealing 1,300 upregulated genes and 1,192 downregulated genes. Using WGCNA, the turquoise module was identified to be closely associated with ccRCC. Hub genes were identified using the maximal clique centrality algorithm. After having intersected the hub genes and the DEGs in GSE126964 and TCGA-KIRC dataset, and after performing univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, ALDOB, EFHD1, and ESRRG were identified as significant prognostic factors in patients diagnosed with ccRCC. Single-gene RNA sequencing analysis revealed the expression profile of ALDOB, EFHD1, and ESRRG in different cell types of ccRCC.ConclusionsThe present results demonstrated that ALDOB, EFHD1, and ESRRG may act as potential targets for medical therapy and could serve as diagnostic biomarkers for ccRCC.

scholarly journals Prognostic value and immunological role of AXL gene in clear cell renal cell carcinoma associated with identifying LncRNA/RBP/AXL mRNA networks

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yi Wang ◽  
Ye Tian ◽  
Shouyong Liu ◽  
Zengjun Wang ◽  
Qianwei Xing
Keyword(s):  
Renal Cell Carcinoma ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Tcga Dataset

Abstract Backgrounds This article aimed to explore the prognostic and immunological roles of AXL gene in clear cell renal cell carcinoma (ccRCC) for overall survival (OS) and to identify the LncRNA/RBP/AXL mRNA networks. Methods AXL-related gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA) dataset and AXL-related pathways were identified by gene set enrichment analysis (GSEA). We performed univariate/multivariate Cox regression analysis to evaluate independent prognostic factors and the relationships between AXL and immunity were also investigated. Results The outcomes of us indicated that the AXL mRNA expression was up-regulated in ccRCC samples and high expression of AXL was associated with worse OS in TCGA dataset (P < 0.01). Further external verification results from HPA, UALCAN, ICGC dataset, GSE6344, GSE14994, and qRT-PCR remained consistent (all P < 0.05). AXL was also identified as an independent prognostic factor for ccRCC by univariate/multivariate Cox regression analysis (both P < 0.05). A nomogram including AXL expression and clinicopathological factors was established by us and GSEA results found that elevated AXL expression was associated with the JAK-STAT, P53, WNT, VEGF and MAPK signaling pathways. In terms of immunity, AXL was dramatically linked to tumor microenvironment, immune cells, immune infiltration, immune checkpoint molecules and tumor mutational burden (TMB). As for its potential mechanisms, we also identified several LncRNA/RBP/AXL mRNA axes. Conclusions AXL was revealed to play prognostic and immunological roles in ccRCC and LncRNA/RBP/AXL mRNA axes were also identified by us for its potential mechanisms.

scholarly journals Bioinformatics analysis of C3 and CXCR4 demonstrates their potential as prognostic biomarkers in clear cell renal cell carcinoma (ccRCC)

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jing Quan ◽  
Yuchen Bai ◽  
Yunbei Yang ◽  
Er Lei Han ◽  
Hong Bai ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Therapeutic Targets ◽  
Disease Free Survival ◽  
Prognostic Biomarkers ◽  
Hub Genes ◽  
Cell Renal Cell Carcinoma ◽  
Upregulated Genes

Abstract Background The molecular prognostic biomarkers of clear cell renal cell carcinoma (ccRCC) are still unknown. We aimed at researching the candidate biomarkers and potential therapeutic targets of ccRCC. Methods Three ccRCC expression microarray datasets (include GSE14762, GSE66270 and GSE53757) were downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) between ccRCC and normal tissues were explored. The potential functions of identified DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). And then the protein - protein interaction network (PPI) was established to screen the hub genes. After that, the expressions of hub genes were identified by the oncomine database. The hub genes’ prognostic values of patients with ccRCC were analyzed by GEPIA database. Results A total of 137 DEGs were identified by utilizing the limma package and RRA method, including 63 upregulated genes and 74 downregulated genes. It is found that 137 DEGs were mainly enriched in 82 functional terms and 24 pathways in accordance with the research results. Thirteen highest-scoring genes were screened as hub genes (include 10 upregulated genes and 3 downregulated candidate genes) by utilizing the PPI network and module analysis. Through integrating the oncoming database and GEPIA database, the author found that C3 and CXCR4 are not only overexpressed in ccRCC, but also associated with the prognosis of ccRCC. Further results could reveal that patients with high C3 expression had a poor overall survival (OS), while patients with high CTSS and TLR3 expressions had a good OS; patients with high C3 and CXCR4 expressions had a poor disease-free survival (DFS), while ccRCC patients with high TLR3 expression had a good DFS. Conclusion These findings suggested that C3 and CXCR4 were the candidate biomarkers and potential therapeutic targets of ccRCC patients.

scholarly journals COL6A2/3 can serve as potential therapeutic targets and prognostic biomarkers for clear cell renal cell carcinoma

2020 ◽  
Author(s):  
Wingkeung Yiu ◽  
Can-Xuan Li ◽  
Jie Chen
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Mrna Expression ◽  
Renal Cell ◽  
Clear Cell ◽  
Therapeutic Targets ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Biomarkers ◽  
Cell Renal Cell Carcinoma ◽  
Tumorigenesis And Progression

Abstract Background: Growing evidence has shown that the type VI collagen alpha chain (COL6A) family involved in the tumorigenesis and progression of diverse malignancies; however, its biological roles and potential mechanisms in clear cell renal cell carcinoma (ccRCC) remain unknown. The study was designed to explore the potential mechanisms and functions of COL6As in ccRCC.Methods: ONCOMINE and GEPIA databases were used to compare the transcriptional expression data of COL6As in ccRCC samples and normal renal samples. UALCAN database was utilized to determine the association between clinicopathological features and COL6As expression. Kaplan–Meier method was employed to determine the prognostic value of COL6As mRNA expression in ccRCC. CBioPortal database was used to investigate the genetic alterations of COL6As in ccRCC. Co-expression analyses, functional enrichment analyses, and gene set enrichment analysis (GSEA) were utilized to explore the potential action mechanisms of COL6As in ccRCC. Finally, we estimated the relationship between COL6As expression with immune cell infiltrates.Results: Upregulated transcriptional COL6A2/COL6A3 expression was observed in ccRCC specimens by comparison with noncancerous renal specimens. Patients with increased COL6A2/COL6A3 mRNA expression have a poor clinical outcome and unfavorable prognosis. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and GSEA analyses showed that COL6A2/COL6A3 might promote the tumorigenesis and progression of ccRCC by involving in several cancer-related pathways, such as axon guidance, focal adhesion, ECM receptor interaction. Besides, we found that COL6A2/COL6A3 expression was significantly associated with immune infiltration levels in ccRCC.Conclusions: COL6A2 and COL6A3 could act as candidate prognostic biomarkers and therapeutic targets in ccRCC. However, further experimental work was required to validate the conclusions.

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