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

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.

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

Frontiers in Genetics ◽

10.3389/fgene.2021.726369 ◽

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.

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Metabolic genes show excellent prognostic ability for clear cell renal cell carcinoma

10.21203/rs.3.rs-25880/v1 ◽

2020 ◽

Author(s):

Chengjian Ji ◽

Yichun Wang ◽

Liangyu Yao ◽

Jiaochen Luan ◽

Rong Cong ◽

...

Keyword(s):

Gene Expression ◽

Renal Cell Carcinoma ◽

Regression Analysis ◽

Cell Carcinoma ◽

Renal Cell ◽

Cox Regression ◽

Expression Profiles ◽

Cell Renal Cell Carcinoma ◽

Cox Regression Analysis ◽

Metabolic Genes

Abstract Background Renal cell carcinoma (RCC) is one of the major malignant tumors of the urinary system, with a high mortality rate and a poor prognosis. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC. Although the diagnosis and treatment methods have been significantly improved, the incidence and mortality of ccRCC are high and still increasing. The occurrence and development of ccRCC are closely related to the changes of classic metabolic pathways. This article aims to explore the relationship between metabolic genes and the prognosis of patients with ccRCC. Patients and methods: Gene expression profiles of 63 normal kidney tissues and 446 ccRCC tissues from TCGA database and gene expression profiles of 39 ccRCC tissues from GEO database were used to obtain differentially expressed genes (DEGs) in ccRCC. Through the the KEGG gene sets of GSEA database, we obtained metabolic genes (MGs). Univariate Cox regression analysis was used to identify prognostic MGs. Lasso regression analysis was used to eliminate false positives because of over-fitting. Multivariate Cox regression analysis was used to established a prognostic model. Gene expression data and related survival data of 101 ccRCC patients from ArrayExpress database were used for external validation. Survival analysis, ROC curve analysis, independent prognostic analysis and clinical correlation analysis were performed to evaluate this model. Results We found that there were 479 abnormally expressed MGs in ccRCC tissues. Through univariate Cox regression analysis, Lasso regression analysis and multivariate Cox regression analysis, we identified 4 prognostic MGs (P4HA3, ETNK2, PAFAH2 and ALAD) and established a prognostic model (riskScore). Whether in the training cohort, the testing cohort or the entire cohort, this model could accurately stratify patients with different survival outcomes. The prognostic value of riskScore and 4 MGs was also confirmed in the ArrayExpress database. Results of GSEA analysis show that DEGs in patients with better prognosis were enriched in metabolic pathways. Then, a new Nomogram with higher prognostic value was constructed to better predict the 1-year OS, 3-year OS and 5-year OS of ccRCC patients. In addition, we successfully established a ceRNA network to further explain the differences in the expression of these MGs between high-risk patients and low-risk patients Conclusion We have successfully established a risk model (riskScore) based on 4 MGs, which could accurately predict the prognosis of patients with ccRCC. Our research may shed new light on ccRCC patients' prognosis and treatment management.

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The ceRNA Network Has Potential Prognostic Value in Clear Cell Renal Cell Carcinoma: A Study Based on TCGA Database

BioMed Research International ◽

10.1155/2020/4830847 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Haosheng Liu ◽

Zhaowen Zhu ◽

Jianxiong Fang ◽

Tianqi Liu ◽

Zhenhui Zhang ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Molecular Mechanisms ◽

Kidney Development ◽

Cox Regression ◽

Clear Cell ◽

Cell Renal Cell Carcinoma ◽

Cox Regression Analysis ◽

Cerna Network

Clear cell renal cell carcinoma (ccRCC) is a very common cancer in urology. Many evidences suggest that complex changed pathways take a nonnegligible part in the occurrence and development of ccRCC. Nevertheless, the underlying mechanism is not clear. In this study, the expression data between ccRCC and normal tissue samples in TCGA database were compared to distinguish differentially expressed genes (DEGs: mRNAs, miRNAs, and lncRNAs). Afterwards, we used GO enrichment and KEGG pathway enrichment analyses to explore the functions of these DEGs. We also found the correlation between three RNAs and created a competing endogenous RNA (ceRNA) network. Moreover, we used univariate Cox regression analysis to select DEGs that are connected with overall survival (OS) of ccRCC patients. We found 1652 mRNAs, 1534 lncRNAs, and 173 miRNAs that were distinguished in ccRCC compared with normal tissues. According to GO analysis, the maladjusted mRNAs are mainly concentrated in immune cell activation and kidney development, while according to KEGG, they are mainly concentrated in pathways related to cancer. A total of 5 mRNAs, 1 miRNA, and 4 lncRNAs were connected with patients’ OS. In this article, a network of lncRNA-miRNA-mRNA was established; it is expected to be able to indicate possible molecular mechanisms for initial of ccRCC and provide a new viewpoint for diagnosis of ccRCC.

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

10.21203/rs.3.rs-143767/v1 ◽

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

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A New Prognostic Risk Signature of Eight Ferroptosis-Related Genes in the Clear Cell Renal Cell Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.700084 ◽

2021 ◽

Vol 11 ◽

Author(s):

Ji Chen ◽

Yating Zhan ◽

Rongrong Zhang ◽

Bo Chen ◽

Junting Huang ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Immune Cell ◽

Cox Regression ◽

Clear Cell ◽

Locally Advanced ◽

Lasso Regression ◽

Cell Renal Cell Carcinoma ◽

Cox Regression Analysis

Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma and has poor prognosis in the locally advanced stage. Ferroptosis, a relatively new type of cell death, has gained significant attention in recent years. This study aimed to explore the prognostic value of ferroptosis-related genes (FRGs) in ccRCC. In this study, 50 differentially expressed FRGs between ccRCC and adjacent normal kidney tissues were identified, 26 of them correlated with overall survival (OS) (P <0.05). Eight optimal FRGs were selected by Lasso regression and multivariate Cox regression analysis, and used to construct a new prognostic risk signature to predict the prognosis of ccRCC patients. In addition, the signature passed the validation of prognostic survival analyses by a significant margin, and the risk score was identified as an independent prognostic marker via Cox regression analyses. Further studies indicated that the signature was significantly correlated with immune cell infiltration. Moreover, the levels of eight FRGs were examined in ccRCC. Collectively, the 8-FRG prognostic risk signature helps the clinicians predict the prognosis and OS of the patients, and standardize prognostic assessments.

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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

10.21203/rs.3.rs-207677/v1 ◽

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.

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Epigenetic signature predicts overall survival clear cell renal cell carcinoma

Cancer Cell International ◽

10.1186/s12935-020-01640-x ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Yejinpeng Wang ◽

Liang Chen ◽

Lingao Ju ◽

Kaiyu Qian ◽

Xinghuan Wang ◽

...

Keyword(s):

Dna Methylation ◽

Renal Cell Carcinoma ◽

Overall Survival ◽

Cell Carcinoma ◽

Renal Cell ◽

Cox Regression ◽

Clear Cell ◽

The Cancer Genome Atlas ◽

Cell Renal Cell Carcinoma ◽

Cox Regression Analysis

Abstract Background Recently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC). Methods We used the DNA methylation dataset of The Cancer Genome Atlas (TCGA) database to construct a 31-CpG-based signature which could accurately predict the overall survival of ccRCC. Meanwhile, we constructed a nomogram to predict the prognosis of patients with ccRCC. Result Through LASSO Cox regression analysis, we obtained the 31-CpG-based epigenetic signature which were significantly related to the prognosis of ccRCC. According to the epigenetic signature, patients were divided into two groups with high and low risk, and the predictive value of the epigenetic signature was verified by other two sets. In the training set, hazard ratio (HR) = 13.0, 95% confidence interval (CI) 8.0–21.2, P < 0.0001; testing set: HR = 4.1, CI 2.2–7.7, P < 0.0001; entire set: HR = 7.2, CI 4.9–10.6, P < 0.0001, Moreover, combined with clinical indicators, the prediction of 5-year survival of ccRCC reached an AUC of 0.871. Conclusions Our study constructed a 31-CpG-based epigenetic signature that could accurately predicted overall survival of ccRCC and staging progression of ccRCC. At the same time, we constructed a nomogram, which may facilitate the prediction of prognosis for patients with ccRCC.

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Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma

PeerJ ◽

10.7717/peerj.8827 ◽

2020 ◽

Vol 8 ◽

pp. e8827 ◽

Cited By ~ 5

Author(s):

Yiqiao Zhao ◽

Zijia Tao ◽

Xiaonan Chen

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Risk Score ◽

Renal Cell ◽

Cox Regression ◽

Clear Cell ◽

Experimental Studies ◽

The Cancer Genome Atlas ◽

Cell Renal Cell Carcinoma ◽

Cox Regression Analysis

Background Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent malignancies worldwide, N6-methyladenosine (m6A) has been shown to play important roles in regulating gene expression and phenotypes in both health and disease. Here, our purpose is to construct a m6A-regulrator-based risk score (RS) for prediction of the prognosis of ccRCC. Methods We used clinical and expression data of m6A related genes from The Cancer Genome Atlas (TCGA) dataset and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis to develop an RS to predict survival of patients with ccRCC, and analyzed correlations between RS and other clinical indicators such as age, grade and stage. Validation of this RS was then engaged in another cohort, E-MTAB-1980 from the ArrayExpress dataset. Finally, we used quantitative real-time PCR to analyze the expression profile of genes consists of the RS. Results A three-gene RS including METTL3, METTL14 and HNRNPA2B1 which can predict overall survival (OS) of ccRCC patients from TCGA. After applying this RS into the validation cohort from Arrayexpress, we found that it successfully reproduced the result; furthermore, the results of PCR validation were in line with our analysis. Conclusion To sum up, our study has identified an RS composed of m6A related genes that may predict the prognosis of ccRCC patients, which might be helpful for future therapeutic strategies. Our results call for further experimental studies for validations.

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A Novel Ferroptosis-Related Pathway for Regulating Immune Checkpoints in Clear Cell Renal Cell Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.678694 ◽

2021 ◽

Vol 11 ◽

Author(s):

Su Gao ◽

Hailong Ruan ◽

Jingchong Liu ◽

Yuenan Liu ◽

Di Liu ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Tumor Immunity ◽

Renal Cell ◽

Molecular Mechanisms ◽

Cox Regression ◽

Clear Cell ◽

Cell Renal Cell Carcinoma ◽

Survival Analyses ◽

Cox Regression Analysis

Ferroptosis is a novel form of cell death and plays a role in various diseases, especially tumors. It has been reported that ferroptosis is involved in the growth and progression of clear cell renal cell carcinoma (ccRCC); however, the specific molecular mechanisms are still unclear. In this study, we constructed a four-gene signature (FeSig) of ferroptosis-related genes via Cox regression analysis. ROC and survival analyses indicated that FeSig had good diagnostic and prognostic value. Further analysis revealed that ferroptosis was associated with tumor immunity in ccRCC. Next, weighted gene co-expression network analysis was performed to identify the potential regulatory mechanisms. Combined with correlation and survival analyses, the TAZ/WNT10B axis was identified as a tumor immune-related regulatory pathway. In conclusion, these findings suggest that ferroptosis is correlated with tumor immunity. The TAZ/WNT10B axis may be a novel biomarker and therapeutic target for immunotherapy in ccRCC.

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

10.21203/rs.3.rs-274762/v1 ◽

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.

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