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Identification of Prognostic and Predictive Biomarkers and Druggable Targets among 205 Antioxidant Genes in 21 Different Tumor Types via Data-Mining

(1) Background: Oxidative stress is crucial in carcinogenesis and the response of tumors to treatment. Antioxidant genes are important determinants of resistance to chemotherapy and radiotherapy. We hypothesized that genes involved in the oxidative stress response may be valuable as prognostic bioma...

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Autores principales: Özenver, Nadire, Efferth, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9959161/
https://www.ncbi.nlm.nih.gov/pubmed/36839749
http://dx.doi.org/10.3390/pharmaceutics15020427
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author Özenver, Nadire
Efferth, Thomas
author_facet Özenver, Nadire
Efferth, Thomas
author_sort Özenver, Nadire
collection PubMed
description (1) Background: Oxidative stress is crucial in carcinogenesis and the response of tumors to treatment. Antioxidant genes are important determinants of resistance to chemotherapy and radiotherapy. We hypothesized that genes involved in the oxidative stress response may be valuable as prognostic biomarkers for the survival of cancer patients and as druggable targets. (2) Methods: We mined the KM Plotter and TCGA Timer2.0 Cistrome databases and investigated 205 antioxidant genes in 21 different tumor types within the context of this investigation. (3) Results: Of 4347 calculations with Kaplan–Meier statistics, 84 revealed statistically significant correlations between high gene expression and worse overall survival (p < 0.05; false discovery rate ≤ 5%). The tumor types for which antioxidant gene expression was most frequently correlated with worse overall survival were renal clear cell carcinoma, renal papillary cell carcinoma, and hepatocellular carcinoma. Seventeen genes were clearly overexpressed in tumors compared to their corresponding normal tissues (p < 0.001), possibly qualifying them as druggable targets (i.e., ALOX5, ALOX5AP, EPHX4, G6PD, GLRX3, GSS, PDIA4, PDIA6, PRDX1, SELENOH, SELENON, STIP1, TXNDC9, TXNDC12, TXNL1, TXNL4A, and TXNRD1). (4) Conclusions: We concluded that a sub-set of antioxidant genes might serve as prognostic biomarkers for overall survival and as druggable targets. Renal and liver tumors may be the most suitable entities for this approach.
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spelling pubmed-99591612023-02-26 Identification of Prognostic and Predictive Biomarkers and Druggable Targets among 205 Antioxidant Genes in 21 Different Tumor Types via Data-Mining Özenver, Nadire Efferth, Thomas Pharmaceutics Article (1) Background: Oxidative stress is crucial in carcinogenesis and the response of tumors to treatment. Antioxidant genes are important determinants of resistance to chemotherapy and radiotherapy. We hypothesized that genes involved in the oxidative stress response may be valuable as prognostic biomarkers for the survival of cancer patients and as druggable targets. (2) Methods: We mined the KM Plotter and TCGA Timer2.0 Cistrome databases and investigated 205 antioxidant genes in 21 different tumor types within the context of this investigation. (3) Results: Of 4347 calculations with Kaplan–Meier statistics, 84 revealed statistically significant correlations between high gene expression and worse overall survival (p < 0.05; false discovery rate ≤ 5%). The tumor types for which antioxidant gene expression was most frequently correlated with worse overall survival were renal clear cell carcinoma, renal papillary cell carcinoma, and hepatocellular carcinoma. Seventeen genes were clearly overexpressed in tumors compared to their corresponding normal tissues (p < 0.001), possibly qualifying them as druggable targets (i.e., ALOX5, ALOX5AP, EPHX4, G6PD, GLRX3, GSS, PDIA4, PDIA6, PRDX1, SELENOH, SELENON, STIP1, TXNDC9, TXNDC12, TXNL1, TXNL4A, and TXNRD1). (4) Conclusions: We concluded that a sub-set of antioxidant genes might serve as prognostic biomarkers for overall survival and as druggable targets. Renal and liver tumors may be the most suitable entities for this approach. MDPI 2023-01-28 /pmc/articles/PMC9959161/ /pubmed/36839749 http://dx.doi.org/10.3390/pharmaceutics15020427 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Özenver, Nadire
Efferth, Thomas
Identification of Prognostic and Predictive Biomarkers and Druggable Targets among 205 Antioxidant Genes in 21 Different Tumor Types via Data-Mining
title Identification of Prognostic and Predictive Biomarkers and Druggable Targets among 205 Antioxidant Genes in 21 Different Tumor Types via Data-Mining
title_full Identification of Prognostic and Predictive Biomarkers and Druggable Targets among 205 Antioxidant Genes in 21 Different Tumor Types via Data-Mining
title_fullStr Identification of Prognostic and Predictive Biomarkers and Druggable Targets among 205 Antioxidant Genes in 21 Different Tumor Types via Data-Mining
title_full_unstemmed Identification of Prognostic and Predictive Biomarkers and Druggable Targets among 205 Antioxidant Genes in 21 Different Tumor Types via Data-Mining
title_short Identification of Prognostic and Predictive Biomarkers and Druggable Targets among 205 Antioxidant Genes in 21 Different Tumor Types via Data-Mining
title_sort identification of prognostic and predictive biomarkers and druggable targets among 205 antioxidant genes in 21 different tumor types via data-mining
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9959161/
https://www.ncbi.nlm.nih.gov/pubmed/36839749
http://dx.doi.org/10.3390/pharmaceutics15020427
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