Identification of EGFR as a Novel Key Gene in Clear Cell Renal Cell Carcinoma (ccRCC) through Bioinformatics Analysis and Meta-Analysis

Wang, Sheng; Yu, Zhihong; Chai, Kequn

doi:10.1155/2019/6480865

Cited by 20 publications

(17 citation statements)

References 31 publications

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“…In addition to our results, downregulation of PLG in ccRCC was confirmed by Schrödter et al who screened the DEGs using a microarray and qPCR [32]. PLG was also screened as a hub gene in some research, which suggested it might play a major role in ccRCC [33,34]. Worse OS of ccRCC patients associated with low expression of PLG was verified by Wang et al using UALCAN [34].…”

Section: Discussionsupporting

confidence: 83%

“…PLG was also screened as a hub gene in some research, which suggested it might play a major role in ccRCC [33,34]. Worse OS of ccRCC patients associated with low expression of PLG was verified by Wang et al using UALCAN [34]. Our GSEA analysis showed that low expression of PLG also probably negatively mediates p53 signaling pathway to promote ccRCC progression.…”

Section: Discussionmentioning

confidence: 54%

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Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma

et al. 2020

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Background: Clear cell renal cell carcinoma (ccRCC) comprises the majority of kidney cancer death worldwide, whose incidence and mortality are not promising. Identifying ideal biomarkers to construct a more accurate prognostic model than conventional clinical parameters is crucial.Methods: Raw count of RNA-sequencing data and clinicopathological data were acquired from The Cancer Genome Atlas (TCGA). Tumor samples were divided into two sets. Differentially expressed genes (DEGs) were screened in the whole set and prognosis-related genes were identified from the training set. Their common genes were used in LASSO and best subset regression which were performed to identify the best prognostic 5 genes. The gene-based risk score was developed based on the Cox coefficient of the individual gene. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier (KM) survival analysis were used to assess its prognostic power. GSE29609 dataset from GEO (Gene Expression Omnibus) database was used to validate the signature. Univariate and multivariate Cox regression were performed to screen independent prognostic parameters to construct a nomogram. The predictive power of the nomogram was revealed by time-dependent ROC curves and the calibration plot and verified in the validation set. Finally, Functional enrichment analysis of DEGs and 5 novel genes were performed to suggest the potential biological pathways.Results: PADI1, ATP6V0D2, DPP6, C9orf135 and PLG were screened to be significantly related to the prognosis of ccRCC patients. The risk score effectively stratified the patients into high-risk group with poor overall survival (OS) based on survival analysis. AJCC-stage, age, recurrence and risk score were regarded as independent prognostic parameters by Cox regression analysis and were used to construct a nomogram. Time-dependent ROC curves showed the nomogram performed best in 1-, 3-and 5-year survival predictions compared with AJCC-stage and risk score in validation sets. The calibration plot showed good agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis suggested several enriched biological pathways related to cancer. Conclusions:In our study, we constructed a gene-based model integrating clinical prognostic parameters to predict prognosis of ccRCC well, which might provide a reliable prognosis assessment tool for clinician and aid treatment decision-making in the clinic. © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article' s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article'

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Section: Discussionsupporting

confidence: 83%

Section: Discussionmentioning

confidence: 54%

Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma

et al. 2020

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“…The Cochrane collaboration risk of bias assessment tool assessed the risk of bias in RCTs in terms of random sequence generation, blindness, incomplete outcome data, allocation concealment and selective reporting. Based on the description of a previous study by Wang, [ 27 ] the Newcastle-Ottawa Scale (NOS) was used to assess the quality of OBS. In the meta-analysis, funnel plots were not used to assess the likelihood of publication bias because of the insufficient number of trials.…”

Section: Methodsmentioning

confidence: 99%

The efficacy and safety of gemcitabine-based induction chemotherapy for locally advanced nasopharyngeal carcinoma treated with concurrent chemoradiation

et al. 2021

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Objectives: To assess the efficacy and toxicity of gemcitabine-based induction chemotherapy followed by concurrent chemoradiotherapy (CCRT) in locally advanced nasopharyngeal carcinoma (LA-NPC). Methods: Both observational studies (OBS) and randomized controlled trials (RCT) were included in the meta-analysis. Systematic online searches were conducted in Web of Sciences, PubMed, Embase, meeting proceedings and ClinicalTrials.gov from the inception to May 25, 2020. The primary endpoint of interest was overall survival. Results: five OBSs and 2 RCTs including 1680 patients were incorporated in the analysis. The evidence from the RCTs showed that adding gemcitabine-based induction chemotherapy to CCRT significantly improved progression free survival (hazard ratio (HR): 0.60, 95% confidence interval (CI): 0.40–0.88; P = .010; chi square P = .25; I 2 = 24%) and overall survival (HR: 0.47; 95% CI: 0.28–0.80; P = 0.005; chi square P = .49, I 2 = 0%) and was related to a higher risk of hematological toxicities. Furthermore, based on the data of OBSs, overall survival (HR: 0.52; 95% CI: 0.31–0.88; P = .02; chi square P = .37, I 2 = 6%) was significantly improved in patients treated with gemcitabine-based induction chemotherapy compared to those treated with taxane-based induction chemotherapy. However, the progression free survival (HR: 0.67; 95% CI: 0.45–1.01; P = .06; chi square P = .74; I 2 = 0%) showed no significant difference. Conclusions: For LA-NPC patients, adding gemcitabine-based induction chemotherapy to CCRT significantly improved overall survival and progression free survival with a higher risk of hematological toxicities when compared to CCRT alone. Also, gemcitabine-based regimen could be used as an alternative induction chemotherapy regimen to taxane-based regimen in the treatment of LA-NPC.

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“…Renal cell carcinoma (RCC) is one of the most prevalent cancers 1 and was ranked the sixth deadliest malignant tumor worldwide in 2018 2 . According to The American Cancer Society, in the USA alone, it was estimated that more than 73,000 new cases of RCC would be diagnosed by the end of 2019 and over 14,000 people would die from it in 2019 3 .…”

Section: Introductionmentioning

confidence: 99%

Identification of a Glucose Metabolism-related Signature for prediction of Clinical Prognosis in Clear Cell Renal Cell Carcinoma

Wang¹,

Zhang²,

Yu³

et al. 2020

J. Cancer

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Background: Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent and invasive histological subtypes among all renal cell carcinomas (RCC). Cancer cell metabolism, particularly glucose metabolism, has been reported as a hallmark of cancer. However, the characteristics of glucose metabolism-related gene sets in ccRCC have not been systematically profiled. Methods: In this study, we downloaded a gene expression profile and glucose metabolism-related gene set from TCGA (The Cancer Genome Altas) and MSigDB, respectively, to analyze the characteristics of glucose metabolism-related gene sets in ccRCC. We used a multivariable Cox regression analysis to develop a risk signature, which divided patients into low- and high- risk groups. In addition, a nomogram that combined the risk signature and clinical characteristics was created for predicting the 3- and 5-year overall survival (OS) of ccRCC. The accuracy of the nomogram prediction was evaluated using the area under the receiver operating characteristic curve (AUC) and a calibration plot. Results: A total of 231 glucose metabolism-related genes were found, and 68 differentially expressed genes (DEGs) were identified. After screening by univariate regression analysis, LASSO regression analysis and multivariable Cox regression analysis, six glucose metabolism-related DEGs ( FBP1, GYG2, KAT2A, LGALS1, PFKP, and RGN ) were selected to develop a risk signature. There were significant differences in the clinical features (Fuhrman nuclear grade and TNM stage) between the high- and low-risk groups. The multivariable Cox regression indicated that the risk score was independent of the prognostic factors (training set: HR=3.393, 95% CI [2.025, 5.685], p<0.001; validation set: HR=1.933, 95% CI [1.130, 3.308], p=0.016). The AUCs of the nomograms for the 3-year OS in the training and validation sets were 0.808 and 0.819, respectively, and 0.777 and 0.796, respectively, for the 5- year OS. Conclusion: We demonstrated a novel glucose metabolism-related risk signature for predicting the prognosis of ccRCC. However, additional in vitro and in vivo research is required to validate our findings.

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Identification of EGFR as a Novel Key Gene in Clear Cell Renal Cell Carcinoma (ccRCC) through Bioinformatics Analysis and Meta-Analysis

Cited by 20 publications

References 31 publications

Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma

Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma

The efficacy and safety of gemcitabine-based induction chemotherapy for locally advanced nasopharyngeal carcinoma treated with concurrent chemoradiation

Identification of a Glucose Metabolism-related Signature for prediction of Clinical Prognosis in Clear Cell Renal Cell Carcinoma

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