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      NOX4 links metabolic regulation in pancreatic cancer to endoplasmic reticulum redox vulnerability and dependence on PRDX4

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          Abstract

          Reductive power in the cytosol of pancreatic cancer cells drives a dependency on the endoplasmic reticulum protein PRDX4.

          Abstract

          There is an urgent need to identify vulnerabilities in pancreatic ductal adenocarcinoma (PDAC). PDAC cells acquire metabolic changes that augment NADPH production and cytosolic redox homeostasis. Here, we show that high NADPH levels drive activity of NADPH oxidase 4 (NOX4) expressed in the endoplasmic reticulum (ER) membrane. NOX4 produces H 2O 2 metabolized by peroxiredoxin 4 (PRDX4) in the ER lumen. Using functional genomics and subsequent in vitro and in vivo validations, we find that PDAC cell lines with high NADPH levels are dependent on PRDX4 for their growth and survival. PRDX4 addiction is associated with increased reactive oxygen species, a DNA-PKcs–governed DNA damage response and radiosensitivity, which can be rescued by depletion of NOX4 or NADPH. Hence, this study has identified NOX4 as a protein that paradoxically converts the reducing power of the cytosol to an ER-specific oxidative stress vulnerability in PDAC that may be therapeutically exploited by targeting PRDX4.

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          limma powers differential expression analyses for RNA-sequencing and microarray studies

          Matthew E. Ritchie, Belinda Phipson, Di Wu … (2015)
          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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            ROS function in redox signaling and oxidative stress.

            Michael Schieber, Navdeep S. Chandel (2014)
            Oxidative stress refers to elevated intracellular levels of reactive oxygen species (ROS) that cause damage to lipids, proteins and DNA. Oxidative stress has been linked to a myriad of pathologies. However, elevated ROS also act as signaling molecules in the maintenance of physiological functions--a process termed redox biology. In this review we discuss the two faces of ROS--redox biology and oxidative stress--and their contribution to both physiological and pathological conditions. Redox biology involves a small increase in ROS levels that activates signaling pathways to initiate biological processes, while oxidative stress denotes high levels of ROS that result in damage to DNA, protein or lipids. Thus, the response to ROS displays hormesis, given that the opposite effect is observed at low levels compared with that seen at high levels. Here, we argue that redox biology, rather than oxidative stress, underlies physiological and pathological conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.
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              Genomic analyses identify molecular subtypes of pancreatic cancer.

              Peter Bailey, David K Chang, Katia Nones … (2016)
              Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Sci Adv
                Journal ID (iso-abbrev): Sci Adv
                Journal ID (publisher-id): SciAdv
                Journal ID (hwp): advances
                Title: Science Advances
                Publisher: American Association for the Advancement of Science
                ISSN (Electronic): 2375-2548
                Publication date Collection: May 2021
                Publication date (Electronic): 07 May 2021
                Volume: 7
                Issue: 19
                Electronic Location Identifier: eabf7114
                Affiliations
                [1 ]Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
                [2 ]Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
                [3 ]University of Maastricht, Maastricht, Netherlands.
                [4 ]Institute of Medical Science, University of Toronto, Toronto, Canada.
                [5 ]Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Ontario, Canada.
                [6 ]Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
                [7 ]Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
                [8 ]Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
                [9 ]Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
                [10 ]Departments of Human Genetics and Urology, University of California, Los Angeles, Los Angeles, CA, USA.
                [11 ]Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada.
                Author notes
                [* ]Corresponding author. Email: marianne.koritzinsky@ 123456uhnresearch.ca
                [†]

                Present address: Otolaryngology—Head and Neck Surgery, McMaster University, Hamilton, Ontario, Canada.

                [‡]

                These authors’ contributions to the manuscript were completed during affiliations as specified above and are not related to their current employers.

                [§]

                Present address: Hoffmann–La Roche Limited, Mississauga, Ontario, Canada.

                [||]

                Present address: Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada.

                [¶]

                Present address: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

                Article
                Publisher ID: abf7114
                DOI: 10.1126/sciadv.abf7114
                PMC ID: 8104867
                PubMed ID: 33962950
                SO-VID: 4553945d-6297-469e-a6a2-75b1d21ae107
                Copyright © Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                Date received : 16 November 2020
                Date accepted : 18 March 2021
                Funding
                Funded by: doi http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: P30CA016042
                Funded by: doi http://dx.doi.org/10.13039/100009326, Cancer Research Society;
                Award ID: 2132
                Funded by: doi http://dx.doi.org/10.13039/100009812, Princess Margaret Cancer Foundation;
                Funded by: doi http://dx.doi.org/10.13039/501100004376, Terry Fox Research Institute;
                Award ID: PPG09-020005
                Categories
                Subject: Research Article
                Subject: Research Articles
                Subject: SciAdv r-articles
                Subject: Cancer
                Subject: Cell Biology
                Subject: Cancer
                Custom metadata
                Copyeditor Kyle Solis

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