A prognostic nomogram based on competing endogenous RNA network for clear-cell renal cell carcinoma

2020 ◽  
Author(s):  
Yun Peng ◽  
Shangrong Wu ◽  
Zihan Xu ◽  
Dingkun Hou ◽  
Nan Li ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Rna Sequencing ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Signature ◽  
Expression Data ◽  
Competing Endogenous Rna ◽  
Cell Renal Cell Carcinoma

Abstract Backgroud Clear-cell renal cell carcinoma (ccRCC) is stubborn to traditional chemotherapy and radiation treatment, which makes its clinical management a major challenge. Recently, we have made efforts to understand the etiology of ccRCC. Increasing evidence revealed that the competing endogenous RNA (ceRNA) were involved in the development of various tumor. However, it’s scant for studying on ccRCC, and a comprehensive analysis of prognostic model based on lncRNA-miRNA-mRNA ceRNA regulatory network of ccRCC with large-scale sample size and RNA‐sequencing expression data is still limited. Methods RNA‐sequencing expression data were taken out from GTEx database and TCGA database, A total of 354 samples with ccRCC and 157 normal controlled samples were included in our study. The ccRCC-specific genes were obtained from WGCNA and differential expression analysis. Following, the communication between mRNAs and lncRNAs and target miRNAs were predicted by MiRcode, starBase, miRTarBase, and TargetScan. A gene signature of eight genes was constructed by univariate Cox regression, lasso methods and multivariate Cox regression analysis. Results A total of 2191 mRNAs and 1377 lncRNAs was identified, and a dys-regulated ceRNA network for ccRCC was established using 7 mRNAs, 363 lncRNAs, and 3 miRNAs. Further, a gene signature in cluding 8 genes based on this ceRNA was constructed, meanwhile, a nomogram predicting 1-, 3-, 5-year survival probability containing both clinical characteristics and ccRCC-specific gene signatures was developed. Conclusion It could contribute to a better understanding of ccRCC tumorigenesis mechanism and guide clinicians to make a more accurate treatment decision.

A robust ferroptosis-related gene signature predicts overall survival in clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Li Canxuan ◽  
Long Dan
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Risk Groups ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Entire Group ◽  
Cell Renal Cell Carcinoma

Aims: To investigate the prognostic values and potential mechanisms of ferroptosis-related genes in clear cell renal cell carcinoma. Methods: Univariate Cox, least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were employed to identify prognosis-related hub ferroptosis-related genes and establish a prognostic model. Results: The authors established a novel clinical predictive model based on seven hub ferroptosis-related genes in The Cancer Genome Atlas training cohort (n = 374) that was verified in the testing cohort (n = 156) and the entire group (n = 530). Functional analysis indicated that several carcinogenic pathways were enriched. Tumor-infiltrating cells and immunosuppressive molecules were significantly different between the two risk groups. Conclusion: Collectively, the authors successfully constructed a novel ferroptosis-related risk signature that was significantly associated with the prognosis of clear cell renal cell carcinoma.

scholarly journals A novel ferroptosis-related 12-gene signature predicts clinical prognosis and reveals immune relevancy in clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Yingkai Hong ◽  
Mingen Lin ◽  
Dehua Ou ◽  
Zhuangkai Huang ◽  
Peilin Shen
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Risk Group ◽  
Gene Signature ◽  
Cell Renal Cell Carcinoma ◽  
Prognostic Predictor

Abstract Background Clear cell renal cell carcinoma (ccRCC) is still highly aggressive and lethal even with various therapeutic approaches. As kidney is an iron-metabolism-related organ, exploring and assessing the clinical value of ferroptosis, an iron-dependent regulated cell death, is practical and significant. Methods Prognostic ferroptosis-related differentially expressed genes (DEGs) were identified from KIRC cohort in TCGA database, from which a prognostic signature was established using the Lasso-penalized Cox regression analysis. Each patient in the KIRC cohort and the E-MTAB-1980 cohort (from the ArrayExpress database) was assigned with a calculated signature-correlated risk score and categorized to be either in high- or low-risk group divided by the median risk score in the KIRC cohort. Then, the independent prognostic value of the signature was further assessed by Kaplan-Meier (K-M) survival, time-dependent receiver operating characteristic (ROC) and Cox regression analyses base on overall survival (OS) in both cohorts. Lastly, risk-related DEGs were identified in both cohorts and applied with the enrichment analyses for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and immune infiltration. Results Within 60 ferroptosis-related genes, 32 prognostic DEGs were identified, from which we constructed a prognostic 12-gene signature including CARS1, HMGCR, CHAC1, GOT1, CD44, STEAP3, AKR1C1, CBS, DPP4, FANCD2, SLC1A5 and NCOA4. Patients in both cohorts were divided into high- and low-risk group which were visually distributed in two sets and with positive-risk-related mortality. The K-M survival and the ROC curves validated the signature as prognostic valuable with P <0.05 and area under the curve >0.7 in both cohorts, respectively. Multivariate Cox regression further confirmed the risk score as an independent prognostic predictor for OS. Commonly enriched term in GO and KEGG not only shown a highly iron correlation, but also, interesting, an immunity relevancy of 3 immune cells (macrophages, mast cells and regulatory T cell) and 1 immune-related function (antigen processing cell co-stimulation). Conclusion We established a novel 12 ferroptosis-related-gene signature which was proved as an independent prognostic predictor for OS and inferred as relating to tumor immunity in ccRCC, however, the underlying mechanism is still poorly characterized and needed further exploration.

scholarly journals Identification of a Novel Glycolysis-Related Gene Signature Correlates With the Prognosis and Therapeutic Responses in Patients With Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhengtong Lv ◽  
Lin Qi ◽  
Xiheng Hu ◽  
Miao Mo ◽  
Huichuan Jiang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Signature ◽  
Human Protein ◽  
Related Gene ◽  
Cell Renal Cell Carcinoma ◽  
Human Protein Atlas

BackgroundAccumulating evidences indicate significant alterations in the aerobic glycolysis in clear cell renal cell carcinoma (ccRCC). We aim to develop and validate a glycolysis-related genes signature for predicting the clinical outcomes of patients with ccRCC.MethodsmRNA expression profiling of ccRCC was obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis and lasso Cox regression model were performed to identify and construct the prognostic gene signature. The protein expression levels of the core genes were obtained from the Human Protein Atlas database. We used four external independent data sets to verify the predictive power of the model for prognosis, tyrosine kinase inhibitor (TKI) therapy, and immunotherapy responses, respectively. Finally, we explored the potential mechanism of this signature through gene set enrichment analysis (GSEA).ResultsThrough the GSEA, glycolysis-related gene sets were significantly different between ccRCC tissues and normal tissues. Next, we identified and constructed a seven-mRNA signature (GALM, TGFA, RBCK1, CD44, HK3, KIF20A, and IDUA), which was significantly correlated with worse survival outcome and was an independent prognostic indicator for ccRCC patients. Furthermore, the expression levels of hub genes were validated based on the Human Protein Atlas databases. More importantly, the model can predict patients’ response to TKI therapy and immunotherapy. These findings were successfully validated in the external independent ccRCC cohorts. The mechanism exploration showed that the model may influence the prognosis by influencing tumor proliferation, base mismatch repair system and immune status of patients.ConclusionsOur study has built up a robust glycolysis-based molecular signature that predicts the prognosis and TKI therapy and immunotherapy responses of patients with ccRCC with high accuracy, which might provide important guidance for clinical assessment. Also, clinical investigations in large ccRCC cohorts are greatly needed to validate our findings.

scholarly journals A novel ferroptosis-related 12-gene signature predicts clinical prognosis and reveals immune relevancy in clear cell renal cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yingkai Hong ◽  
Mingen Lin ◽  
Dehua Ou ◽  
Zhuangkai Huang ◽  
Peilin Shen
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Renal Cell ◽  
Prognostic Value ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Signature ◽  
Cell Renal Cell Carcinoma ◽  
Prognostic Predictor

Abstract Background Clear cell renal cell carcinoma (ccRCC) is still highly aggressive and lethal even with various therapeutic approaches. As the kidney is an iron metabolism-related organ, exploring and assessing the clinical value of ferroptosis, an iron-dependent regulated cell death, is practical and important. Methods Prognostic ferroptosis-related differentially expressed genes (DEGs) were identified from the KIRC cohort in the cancer genome atlas (TCGA) database, from which a prognostic signature was established using Lasso-penalized Cox regression analysis. Each patient in the KIRC cohort and the E-MTAB-1980 cohort (from the ArrayExpress database) was assigned a calculated signature-correlated risk score and categorized to be either in the high- or low-risk group divided by the median risk score in the KIRC cohort. Then, the independent prognostic value of the signature was further assessed by Kaplan-Meier (K-M) survival, time-dependent receiver operating characteristic (ROC) and Cox regression analyses based on overall survival (OS) in both cohorts. Finally, risk-related DEGs were identified in both cohorts and subjected to enrichment analyses for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and immune infiltration. Results Among 60 ferroptosis-related genes, 32 prognostic DEGs were identified, from which we constructed a prognostic 12-gene signature with CARS1, HMGCR, CHAC1, GOT1, CD44, STEAP3, AKR1C1, CBS, DPP4, FANCD2, SLC1A5 and NCOA4. Patients in both cohorts were divided into high- and low-risk groups, which were visually distributed in two sets and had positive-risk-related mortality. The K-M survival and the ROC curves validated that the signature has prognostic value with P < 0.05 and area under the curve > 0.7 in both cohorts, respectively. Multivariate Cox regression further confirmed the risk score as an independent prognostic predictor for OS. Commonly enriched terms in GO and KEGG not only showed a high iron correlation but also, interestingly, immune relevance of 3 immune cells (macrophages, mast cells and regulatory T cells) and 1 immune-related function (antigen processing cell co-stimulation). Conclusion We established a novel 12 ferroptosis-related-gene signature that was proven to be an independent prognostic predictor for OS and inferred to be related to tumour immunity in ccRCC; however, the underlying mechanism is still poorly characterized and needs further exploration.

scholarly journals Development of a novel gene signature to predict prognosis and response to PD-1 blockade in clear cell renal cell carcinoma

2021 ◽  
Vol 10 (1) ◽  
pp. 1933332
Author(s):  
Xiaomao Yin ◽  
Zaoyu Wang ◽  
Jianfeng Wang ◽  
Yunze Xu ◽  
Wen Kong ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Gene Signature ◽  
Cell Renal Cell Carcinoma ◽  
Novel Gene

scholarly journals Molecular Profiling of Druggable Targets in Clear Cell Renal Cell Carcinoma Through Targeted RNA Sequencing

2019 ◽  
Vol 9 ◽  
Author(s):  
Corina N. A. M. van den Heuvel ◽  
Anne van Ewijk ◽  
Carolien Zeelen ◽  
Tessa de Bitter ◽  
Martijn Huynen ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Rna Sequencing ◽  
Renal Cell ◽  
Clear Cell ◽  
Molecular Profiling ◽  
Cell Renal Cell Carcinoma ◽  
Druggable Targets

scholarly journals A novel 10 glycolysis-related genes signature could predict overall survival for clear cell renal cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qianwei Xing ◽  
Tengyue Zeng ◽  
Shouyong Liu ◽  
Hong Cheng ◽  
Limin Ma ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Regression Analyses ◽  
Cell Renal Cell Carcinoma

Abstract Background The role of glycolysis in tumorigenesis has received increasing attention and multiple glycolysis-related genes (GRGs) have been proven to be associated with tumor metastasis. Hence, we aimed to construct a prognostic signature based on GRGs for clear cell renal cell carcinoma (ccRCC) and to explore its relationships with immune infiltration. Methods Clinical information and RNA-sequencing data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and ArrayExpress datasets. Key GRGs were finally selected through univariate COX, LASSO and multivariate COX regression analyses. External and internal verifications were further carried out to verify our established signature. Results Finally, 10 GRGs including ANKZF1, CD44, CHST6, HS6ST2, IDUA, KIF20A, NDST3, PLOD2, VCAN, FBP1 were selected out and utilized to establish a novel signature. Compared with the low-risk group, ccRCC patients in high-risk groups showed a lower overall survival (OS) rate (P = 5.548Ee-13) and its AUCs based on our established signature were all above 0.70. Univariate/multivariate Cox regression analyses further proved that this signature could serve as an independent prognostic factor (all P < 0.05). Moreover, prognostic nomograms were also created to find out the associations between the established signature, clinical factors and OS for ccRCC in both the TCGA and ArrayExpress cohorts. All results remained consistent after external and internal verification. Besides, nine out of 21 tumor-infiltrating immune cells (TIICs) were highly related to high- and low- risk ccRCC patients stratified by our established signature. Conclusions A novel signature based on 10 prognostic GRGs was successfully established and verified externally and internally for predicting OS of ccRCC, helping clinicians better and more intuitively predict patients’ survival.

scholarly journals A four-gene signature predicts survival in clear-cell renal-cell carcinoma

Oncotarget ◽  
2016 ◽  
Vol 7 (50) ◽  
pp. 82712-82726 ◽  
Author(s):  
Jun Dai ◽  
Yuchao Lu ◽  
Jinyu Wang ◽  
Lili Yang ◽  
Yingyan Han ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Gene Signature ◽  
Cell Renal Cell Carcinoma
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