Identifying prognostic biomarkers based on aberrant DNA methylation in kidney renal clear cell carcinoma

Neutrophil cytoplasmic factor 1/2/4 (NCF1/2/4) belongs to the NADPH oxidase complex, which is a cytoplasmic component, and its polymorphism is the main factor related to autoimmune diseases, which is probably caused by the regulation of peroxide. They also play a role in tumor growth and metastasis. This research is aimed at evaluating the biological function and prognostic role of NCF1, NCF2, and NCF4 genes in kidney renal clear cell carcinoma (KIRC) by using multiple online bioinformatics website, including Oncomine, GEPIA, UALCAN, Kaplan–Meier Plotter, TIMER, TISIDB, cBioPortal, LinkedOmics, GeneMANIA, and DAVID databases. The mRNA levels of NCFs were higher in KIRC tissues than in normal tissues. The overexpression of NCFs was significantly correlated with advanced pathological grades and individual cancer stages in KIRC. Meanwhile, the expressions of NCFs played an important role in the tumorigenesis and progression of KIRC. Prognostic value analysis suggested that high transcription levels of NCF1/4 were associated with poor overall survival in KIRC patients. In addition, results from the LinkedOmics database showed that the KEGG pathway related to NCFs mainly focused on immune activation and immune regulation function. NCF genetic alterations, including copy number amplification, missense mutation, and deep deletion, could be found through the cBioPortal database. Further, NCF expression was significantly correlated with infiltration levels of various immune cells as well as immune signatures. Protein-protein interaction network and enrichment analysis of NCF1/2/4 in KIRC showed that NCF coexpressed genes mainly associated with diverse immune marker sets showed significance. Overall, these results indicated that NCFs could be prognostic biomarkers as well as effective targets for diagnosis in KIRC.

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A methylomics-correlated nomogram predicts the recurrence free survival risk of kidney renal clear cell carcinoma

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2021424 ◽

2021 ◽

Vol 18 (6) ◽

pp. 8559-8576

Author(s):

Xiuxian Zhu ◽

◽

Xianxiong Ma ◽

Chuanqing Wu

Keyword(s):

Dna Methylation ◽

Cell Carcinoma ◽

Roc Analysis ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

External Validation ◽

Renal Clear Cell Carcinoma ◽

Recurrence Free Survival ◽

Free Survival ◽

Validation Set

<abstract> <sec><title>Background</title>Various studies have suggested that the DNA methylation signatures were promising to identify novel hallmarks for predicting prognosis of cancer. However, few studies have explored the capacity of DNA methylation for prognostic prediction in patients with kidney renal clear cell carcinoma (KIRC). It's very promising to develop a methylomics-related signature for predicting prognosis of KIRC. </sec> <sec><title>Methods</title>The 282 patients with complete DNA methylation data and corresponding clinical information were selected to construct the prognostic model. The 282 patients were grouped into a training set (70%, n = 198 samples) to determine a prognostic predictor by univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. The internal validation set (30%, n = 84) and an external validation set (E-MTAB-3274) were used to validate the predictive value of the predictor by receiver operating characteristic (ROC) analysis and Kaplan–Meier survival analysis. </sec> <sec><title>Results</title>We successfully identified a 9-DNA methylation signature for recurrence free survival (RFS) of KIRC patients. We proved the strong robustness of the 9-DNA methylation signature for predicting RFS through ROC analysis (AUC at 1, 3, 5 years in internal dataset (0.859, 0.840, 0.817, respectively), external validation dataset (0.674, 0.739, 0.793, respectively), entire TCGA dataset (0.834, 0.862, 0.842, respectively)). In addition, a nomogram combining methylation risk score with the conventional clinic-related covariates was constructed to improve the prognostic predicted ability for KIRC patients. The result implied a good performance of the nomogram. </sec> <sec><title>Conclusions</title>we successfully identified a DNA methylation-associated nomogram, which was helpful in improving the prognostic predictive ability of KIRC patients. </sec> </abstract>

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