Spatial analysis of NQO1 in non-small cell lung cancer shows its expression is independent of NRF1 and NRF2 in the tumor microenvironment
Abstract
Nuclear factor erythroid 2-related factor 1 (NFE2L1, NRF1) and nuclear factor erythroid 2-related factor 2 (NFE2L2, NRF2) are distinct oxidative stress response transcription factors, both of which have been shown to perform cytoprotective functions, modulating cell stress response and homeostasis. NAD(P)H:quinone oxidoreductase (NQO1) is a mutual downstream antioxidant gene target that catalyzes the two-electron reduction of an array of substrates, protecting against reactive oxygen species (ROS) generation. NQO1 is upregulated in non-small cell lung cancer (NSCLC) and is proposed as a predictive biomarker and therapeutic target. Antioxidant protein expression of immune cells within the NSCLC tumor microenvironment (TME) remains undetermined and may affect immune cell effector functions and survival outcomes. Multiplex immunofluorescence was performed to examine the co-localization of NQO1, NRF1 and NRF2 within the tumor and TME of 162 chemotherapy-naïve, early-stage NSCLC patients treated by primary surgical resection. This study demonstrates that NQO1 protein expression is high in normal, tumor-adjacent tissue and that NQO1 expression varies depending on the cell type. Inter and intra-patient heterogenous NQO1 expression was observed in lung cancer. Co-expression analysis showed NQO1 is independent of NRF1 and NRF2 in tumors. Density-based co-expression analysis demonstrated NRF1 and NRF2 double-positive expression in cancer cells is associated with improved overall survival.
Citation
Kaghazchi , B , Um , I H , Elshani , M , Read , O J & Harrison , D J 2022 , ' Spatial analysis of NQO1 in non-small cell lung cancer shows its expression is independent of NRF1 and NRF2 in the tumor microenvironment ' , Biomolecules , vol. 12 , no. 11 , 1652 . https://doi.org/10.3390/biom12111652
Publication
Biomolecules
Status
Peer reviewed
ISSN
2218-273XType
Journal article
Rights
Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Description
Funding: This work was funded in part by NuCana plc, Lothian NHS and the Industrial Centre for AI Research in Digital Diagnostics (iCAIRD), which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [project number: 104690].Collections
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