Research Papers:

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

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

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Oncotarget. 2017; 8:69847-69862. https://doi.org/10.18632/oncotarget.19349

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Akhileshwar Namani1,*, Qin Qin Cui1,*, Yihe Wu2, Hongyan Wang1,3, Xiu Jun Wang3 and Xiuwen Tang1

1Department of Biochemistry, Zhejiang University, Hangzhou 310058, PR China

2Department of Thoracic Surgery, First Affiliated Hospital, Zhejiang University, Hangzhou 310058, PR China

3Department of Pharmacology, School of Medicine, Zhejiang University, Hangzhou 310058, PR China

*These authors have contributed equally to this work

Correspondence to:

Xiuwen Tang, email: [email protected]

Keywords: KEAP1, NRF2, NSCLC, biomarker, metabolism

Received: February 02, 2017    Accepted: June 19, 2017    Published: July 18, 2017


Mutations in Kelch-like ECH-associated protein 1 (KEAP1) cause the aberrant activation of nuclear factor erythroid-derived 2-like 2 (NRF2), which leads to oncogenesis and drug resistance in lung cancer cells. Our study was designed to identify the genes involved in lung cancer progression targeted by NRF2. A series of microarray experiments in normal and cancer cells, as well as in animal models, have revealed regulatory genes downstream of NRF2 that are involved in wide variety of pathways. Specifically, we carried out individual and combinatorial microarray analysis of KEAP1 overexpression and NRF2 siRNA-knockdown in a KEAP1 mutant-A549 non-small cell lung cancer (NSCLC) cell line. As a result, we identified a list of genes which were mainly involved in metabolic functions in NSCLC by using functional annotation analysis. In addition, we carried out in silico analysis to characterize the antioxidant responsive element sequences in the promoter regions of known and putative NRF2-regulated metabolic genes. We further identified an NRF2-regulated metabolic gene signature (NRMGS) by correlating the microarray data with lung adenocarcinoma RNA-Seq gene expression data from The Cancer Genome Atlas followed by qRT-PCR validation, and finally showed that higher expression of the signature conferred a poor prognosis in 8 independent NSCLC cohorts. Our findings provide novel prognostic biomarkers for NSCLC.

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