Identification of small molecule drugs and development of a novel autophagy‐related prognostic signature for kidney renal clear cell carcinoma

Xing, Qianwei; Ji, Chengjian; Zhu, Bingye; Cong, Rong

doi:10.1002/cam4.3367

Cited by 9 publications

(7 citation statements)

References 40 publications

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“…( 23 ) AUC = 0.729; Xing et al. ( 24 ) AUC = 0.724] and found that our signature had higher prediction reliability and sensitivity than other published biomarkers ( Figure 4D ). Subsequently, the univariate ( Figure 4E ) and multivariate Cox regression analysis ( Figure 4F ) were performed and confirmed that risk score, age, grade were independent prognostic factors (p < 0.01).…”

Section: Resultsmentioning

confidence: 64%

Identification of an m6A-Related lncRNA Signature for Predicting the Prognosis in Patients With Kidney Renal Clear Cell Carcinoma

Mao

Sun

et al. 2021

Front. Oncol.

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PurposeThis study aimed to construct an m6A-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using data obtained from The Cancer Genome Atlas (TCGA) database.MethodsThe KIRC patient data were downloaded from TCGA database and m6A-related genes were obtained from published articles. Pearson correlation analysis was implemented to identify m6A-related lncRNAs. Univariate, Lasso, and multivariate Cox regression analyses were used to identifying prognostic risk-associated lncRNAs. Five lncRNAs were identified and used to construct a prognostic signature in training set. Kaplan–Meier curves and receiver operating characteristic (ROC) curves were applied to evaluate reliability and sensitivity of the signature in testing set and overall set, respectively. A prognostic nomogram was established to predict the probable 1-, 3-, and 5-year overall survival of KIRC patients quantitatively. GSEA was performed to explore the potential biological processes and cellular pathways. Besides, the lncRNA/miRNA/mRNA ceRNA network and PPI network were constructed based on weighted gene co-expression network analysis (WGCNA). Functional Enrichment Analysis was used to identify the biological functions of m6A-related lncRNAs.ResultsWe constructed and verified an m6A-related lncRNAs prognostic signature of KIRC patients in TCGA database. We confirmed that the survival rates of KIRC patients with high-risk subgroup were significantly poorer than those with low-risk subgroup in the training set and testing set. ROC curves indicated that the prognostic signature had a reliable predictive capability in the training set (AUC = 0.802) and testing set (AUC = 0.725), respectively. Also, we established a prognostic nomogram with a high C-index and accomplished good prediction accuracy. The lncRNA/miRNA/mRNA ceRNA network and PPI network, as well as functional enrichment analysis provided us with new ways to search for potential biological functions.ConclusionsWe constructed an m6A-related lncRNAs prognostic signature which could accurately predict the prognosis of KIRC patients.

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Section: Resultsmentioning

confidence: 64%

Identification of an m6A-Related lncRNA Signature for Predicting the Prognosis in Patients With Kidney Renal Clear Cell Carcinoma

Mao

Sun

et al. 2021

Front. Oncol.

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“…We compared the prognostic‐related ARlncRNAs signature with published predictive models in KIRC patients. The ROC curves showed that the present signature (AUC = 0.809) had higher predictive reliability and sensitivity than other published biomarkers (Chen et al 16 autophagy‐related (AR) mRNA signature, AUC = 0.723; Liu, et al 17 lncRNA signature, AUC = 0.723; Sun, et al 18 immune‐related lncRNA, AUC = 0.709; Yin, et al 19 lncRNA signature, AUC = 0.684; Sun, et al 20 m6A‐related signature, AUC = 0.698; Wan, et al 21 AR‐mRNA signature, AUC = 0.743;Xing, et al 22 AR‐mRNA signature, AUC = 0.723; Yang, et al 23 AR‐mRNA signature, AUC = 0.741; Zhang, et al 24 lncRNA signature, AUC = 0.781; Figure 8).…”

Section: Resultsmentioning

confidence: 99%

Construction and validation of an autophagy‐related long noncoding RNA signature for prognosis prediction in kidney renal clear cell carcinoma patients

Mao

et al. 2021

Cancer Medicine

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“…Nomogram, as a predictive tool, has been widely applied to help clinical decision-making [46][47][48]. In our article, we created a nomogram to intuitively predict OS probabilities in ccRCC, by means of NOP2 and eight clinical parameters (gender, age, grade, stage, T stage, race, N stage, M stage).…”

Section: Discussionmentioning

confidence: 99%

Nucleolar protein NOP2 could serve as a potential prognostic predictor for clear cell renal cell carcinoma

Wang

Liu

et al. 2021

Bioengineered

Self Cite

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As an indispensable part for cancer precision medicine, biomarkers and signatures for predicting cancer prognosis and therapeutic benefits were urgently required. The purpose of this study was to investigate the prognostic roles of NOP2 in renal clear cell carcinoma (ccRCC) for overall survival (OS) and its relationships with immunity. NOP2-related gene expression matrix associated with clinical information was obtained from the Cancer Genome Atlas (TCGA) ccRCC dataset and NOP2-related pathways were identified by gene set enrichment analysis (GSEA). Associations among the NOP2 expression and MSI, TMB, TNB, and immunity were also explored. Both the NOP2 mRNA and protein/phosphoprotein had a higher expression in ccRCC tumor tissues than in normal kidney tissues (both P < 0.001) and elevated NOP2 expression was associated with poor OS (P < 0.001). Logistic regression analysis revealed the NOP2 expression was significantly linked to stage, age, grade, N stage, T stage, and M stage (all P < 0.05). Univariate/multivariate Cox hazard regression analysis results indicated that NOP2 was an independent prognostic factor for OS in ccRCC and GSEA revealed five NOP2-related signaling pathways. Nomogram based on NOP2 and eight clinical characteristic parameters (grade, age, stage, gender, T stage, race, M stage, N stage) was constructed and carefully evaluated. Furthermore, NOP2 gene expression was also found to be significantly related to MSI, TMB, and immunity. Our findings revealed that NOP2 might be a potential prognostic factor for OS in ccRCC and it was significantly associated with immunity, MSI, and TMB.

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Identification of small molecule drugs and development of a novel autophagy‐related prognostic signature for kidney renal clear cell carcinoma

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 9 publications

References 40 publications

Identification of an m6A-Related lncRNA Signature for Predicting the Prognosis in Patients With Kidney Renal Clear Cell Carcinoma

Identification of an m6A-Related lncRNA Signature for Predicting the Prognosis in Patients With Kidney Renal Clear Cell Carcinoma

Construction and validation of an autophagy‐related long noncoding RNA signature for prognosis prediction in kidney renal clear cell carcinoma patients

Nucleolar protein NOP2 could serve as a potential prognostic predictor for clear cell renal cell carcinoma

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