NRF2-regulated metabolic gene signature as a prognostic biomarker in non-small cell lung cancer

Namani, Akhileshwar; Cui, Qin; Wu, Yihe; Wang, Hongyan; Wang, Xiu Jun; Tang, Xiuwen

doi:10.18632/oncotarget.19349

Cited by 41 publications

(33 citation statements)

References 81 publications

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“…Additionally, AKR1C2 may be considered as one of the biomarkers that indicates cisplatin resistance and may be act as one of the effective molecular targets for rescuing cisplatin sensitivity [42]. In agreement with our finding, Namani et al, have identified a gene expression signature that includes TXNRD1, AKR1C1, AKR1C2, and SRXN1 along with other genes in head and neck squamous cell cancer and non small cell lung cancer [43,44]. Interestingly, they found that higher expression of this gene signature is associated with poor survival and drug resistance.…”

Section: Agingsupporting

confidence: 90%

Integrated data analysis reveals significant associations of KEAP1 mutations with DNA methylation alterations in lung adenocarcinomas

Elshaer

El-Manawy

Hammad

et al. 2020

Aging

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INTRODUCTION Lung cancer is the leading cause of cancer deaths worldwide. Human lung cancers are classified into two major histologic types, small-cell lung cancer and nonsmall-cell lung cancer (NSCLC), the latter comprising several subtypes. Previously, lung squamous cell carcinoma was the predominant form of NSCLC, but in the last few decades it has been replaced by lung adenocarcinoma (LUAD). Moreover, LUAD is the most common type of lung cancer in women, non-smokers, and young people [1]. Epigenetic changes in tumor tissue are involved in the pathogenesis of cancer. DNA methylation is a wellstudied epigenetic alteration in cancer, owing in part to www.aging-us.com

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Section: Agingsupporting

confidence: 90%

Integrated data analysis reveals significant associations of KEAP1 mutations with DNA methylation alterations in lung adenocarcinomas

Elshaer

El-Manawy

Hammad

et al. 2020

Aging

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“…In the background of TME, the disorder of tumor metabolism could deeply influence the multiple functions of malignant cancer cells [ 9 ]. Previous reports have identified metabolic signatures for prognostic prediction based on multiomics analyses in lung cancer [ 10 – 12 ]. However, the TME is a complex interaction network, and the integrated research on the roles of metabolic signatures in TME is still lacking.…”

Section: Introductionmentioning

confidence: 99%

Identification of a 5-Gene Metabolic Signature for Predicting Prognosis Based on an Integrated Analysis of Tumor Microenvironment in Lung Adenocarcinoma

Zhang

2020

Journal of Oncology

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Lung adenocarcinoma (LUAD) is a common subtype of lung cancer with a depressing survival rate. The reprogramming of tumor metabolism was identified as a new hallmark of cancer in tumor microenvironment (TME), and we made a comprehensive exploration to reveal the prognostic role of the metabolic-related genes. Transcriptome profiling data of LUAD were, respectively, downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Based on the extracted metabolic-related genes, a novel 5-gene metabolic prognostic signature (including GNPNAT1, LPGAT1, TYMS, LDHA, and PTGES) was constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. This signature confirmed its robustness and accuracy by external validation in multiple databases. It could be an independent risk factor for LUAD, and the nomograms possessed moderately accurate performance with the C-index of 0.755 (95% confidence interval: 0.706–0.804) and 0.691 (95% confidence interval: 0.636–0.746) in training set and testing set. This signature could reveal the metabolic features according to the results of gene set enrichment analysis (GSEA) and meanwhile monitor the status of TME through ESTIMATE scores and the infiltration levels of immune cells. In conclusion, this gene signature is a cost-effective tool which could indicate the status of TME to provide more clues in the exploration of new diagnostic and therapeutic strategy.

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“…Therefore, examining the molecular mechanisms involved in these alterations by using publicly available data may contribute to the development and design of therapeutic targets for personalized/precision medicine in subsets of patients. Several emerging studies including our recent study on lung cancer have identified an NRF2-regulated gene signature and potential biomarkers for patient survival and NRF2 activity [ 15 – 18 ].…”

Section: Introductionmentioning

confidence: 99%

Gene-expression signature regulated by the KEAP1-NRF2-CUL3 axis is associated with a poor prognosis in head and neck squamous cell cancer

et al. 2018

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BackgroundNRF2 is the key regulator of oxidative stress in normal cells and aberrant expression of the NRF2 pathway due to genetic alterations in the KEAP1 (Kelch-like ECH-associated protein 1)-NRF2 (nuclear factor erythroid 2 like 2)-CUL3 (cullin 3) axis leads to tumorigenesis and drug resistance in many cancers including head and neck squamous cell cancer (HNSCC). The main goal of this study was to identify specific genes regulated by the KEAP1-NRF2-CUL3 axis in HNSCC patients, to assess the prognostic value of this gene signature in different cohorts, and to reveal potential biomarkers.MethodsRNA-Seq V2 level 3 data from 279 tumor samples along with 37 adjacent normal samples from patients enrolled in the The Cancer Genome Atlas (TCGA)-HNSCC study were used to identify upregulated genes using two methods (altered KEAP1-NRF2-CUL3 versus normal, and altered KEAP1-NRF2-CUL3 versus wild-type). We then used a new approach to identify the combined gene signature by integrating both datasets and subsequently tested this signature in 4 independent HNSCC datasets to assess its prognostic value. In addition, functional annotation using the DAVID v6.8 database and protein-protein interaction (PPI) analysis using the STRING v10 database were performed on the signature.ResultsA signature composed of a subset of 17 genes regulated by the KEAP1-NRF2-CUL3 axis was identified by overlapping both the upregulated genes of altered versus normal (251 genes) and altered versus wild-type (25 genes) datasets. We showed that increased expression was significantly associated with poor survival in 4 independent HNSCC datasets, including the TCGA-HNSCC dataset. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and PPI analysis revealed that most of the genes in this signature are associated with drug metabolism and glutathione metabolic pathways.ConclusionsAltogether, our study emphasizes the discovery of a gene signature regulated by the KEAP1-NRF2-CUL3 axis which is strongly associated with tumorigenesis and drug resistance in HNSCC. This 17-gene signature provides potential biomarkers and therapeutic targets for HNSCC cases in which the NRF2 pathway is activated.Electronic supplementary materialThe online version of this article (10.1186/s12885-017-3907-z) contains supplementary material, which is available to authorized users.

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NRF2-regulated metabolic gene signature as a prognostic biomarker in non-small cell lung cancer

Cited by 41 publications

References 81 publications

Integrated data analysis reveals significant associations of KEAP1 mutations with DNA methylation alterations in lung adenocarcinomas

Integrated data analysis reveals significant associations of KEAP1 mutations with DNA methylation alterations in lung adenocarcinomas

Identification of a 5-Gene Metabolic Signature for Predicting Prognosis Based on an Integrated Analysis of Tumor Microenvironment in Lung Adenocarcinoma

Gene-expression signature regulated by the KEAP1-NRF2-CUL3 axis is associated with a poor prognosis in head and neck squamous cell cancer

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