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      Canagliflozin mediates tumor suppression alone and in combination with radiotherapy in non‐small cell lung cancer (NSCLC) through inhibition of HIF‐1α

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          Abstract

          Non‐small cell lung cancer (NSCLC) has a poor prognosis, and effective therapeutic strategies are lacking. The diabetes drug canagliflozin inhibits NSCLC cell proliferation and the mammalian target of rapamycin (mTOR) pathway, which mediates cell growth and survival, but it is unclear whether this drug can enhance response rates when combined with cytotoxic therapy. Here, we evaluated the effects of canagliflozin on human NSCLC response to cytotoxic therapy in tissue cultures and xenografts. Ribonucleic acid sequencing (RNA‐seq), real‐time quantitative PCR (RT‐qPCR), metabolic function, small interfering ribonucleic acid (siRNA) knockdown, and protein expression assays were used in mechanistic analyses. We found that canagliflozin inhibited proliferation and clonogenic survival of NSCLC cells and augmented the efficacy of radiotherapy to mediate these effects and inhibit NSCLC xenograft growth. Canagliflozin treatment alone moderately inhibited mitochondrial oxidative phosphorylation and exhibited greater antiproliferative capacity than specific mitochondrial complex‐I inhibitors. The treatment downregulated genes mediating hypoxia‐inducible factor (HIF)‐1α stability, metabolism and survival, activated adenosine monophosphate‐activated protein kinase (AMPK) and inhibited mTOR, a critical activator of hypoxia‐inducible factor‐1α (HIF‐1α) signaling. HIF‐1α knockdown and stabilization experiments suggested that canagliflozin mediates antiproliferative effects, in part, through suppression of HIF‐1α. Transcriptional regulatory network analysis pinpointed histone deacetylase 2 ( HDAC2), a gene suppressed by canagliflozin, as a key mediator of canagliflozin's transcriptional reprogramming. HDAC2 knockdown eliminated HIF‐1α levels and enhanced the antiproliferative effects of canagliflozin. HDAC2‐regulated genes suppressed by canagliflozin are associated with poor prognosis in several clinical NSCLC datasets. In addition, we include evidence that canagliflozin also improves NSCLC response to chemotherapy. In summary, canagliflozin may be a promising therapy to develop in combination with cytotoxic therapy in NSCLC.

          Abstract

          The diabetes drug canagliflozin suppresses non‐small cell lung cancer growth and enhances the efficacy of radiotherapy. Canagliflozin inhibits the cell cycle, mitochondrial respiration, and growth‐promoting pathways. Here, the authors uncovered that canagliflozin mediates its effects partly by suppressing hypoxia‐inducible factor‐1α and histone deacetylase 2.

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

            In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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              Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

              The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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                Author and article information

                Contributors
                tsakirt@mcmaster.ca
                Journal
                Mol Oncol
                Mol Oncol
                10.1002/(ISSN)1878-0261
                MOL2
                Molecular Oncology
                John Wiley and Sons Inc. (Hoboken )
                1574-7891
                1878-0261
                27 August 2023
                November 2023
                : 17
                : 11 ( doiID: 10.1002/mol2.v17.11 )
                : 2235-2256
                Affiliations
                [ 1 ] Centre for Metabolism, Obesity and Diabetes Research McMaster University Hamilton Canada
                [ 2 ] Centre for Discovery in Cancer Research McMaster University Hamilton Canada
                [ 3 ] Department of Oncology McMaster University Hamilton Canada
                [ 4 ] Department of Medicine McMaster University Hamilton Canada
                [ 5 ] Radiotherapy Program Juravinski Cancer Centre Hamilton Canada
                [ 6 ] Radiation Physics Program Juravinski Cancer Centre Hamilton Canada
                [ 7 ] Department of Oncology McGill University Montréal Canada
                [ 8 ] Division of Radiation Oncology Juravinski Cancer Centre Hamilton Canada
                [ 9 ] Department of Pathology and Molecular Medicine McMaster University Hamilton Canada
                [ 10 ] Michael DeGroote Institute for Infectious Disease Research McMaster University Hamilton Canada
                [ 11 ] Department of Biomedical, Surgical and Dental Sciences University of Milan Italy
                [ 12 ] Department of Biochemistry and Biomedical Sciences McMaster University Hamilton Canada
                Author notes
                [*] [* ] Correspondence

                T. Tsakiridis, Radiation Oncology, Juravinski Cancer Center, Department of Oncology, McMaster University, 699 Concession Street, Hamilton, ON L8V 5C2, Canada

                Tel: +1 905 387 9495 x63123

                E‐mail: tsakirt@ 123456mcmaster.ca

                Author information
                https://orcid.org/0000-0002-1750-0605
                https://orcid.org/0000-0002-8675-4422
                Article
                MOL213508 MOLONC-23-0156.R1
                10.1002/1878-0261.13508
                10620129
                37584455
                93a23226-3200-4b29-8332-f691591a9ade
                © 2023 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 May 2023
                : 17 February 2023
                : 14 August 2023
                Page count
                Figures: 10, Tables: 0, Pages: 2256, Words: 13799
                Funding
                Funded by: Canadian Institutes of Health Research , doi 10.13039/501100000024;
                Award ID: 201709FDN‐CEBA‐116200
                Funded by: Diabetes Canada , doi 10.13039/100013528;
                Award ID: DI‐5‐17‐5302‐GS
                Funded by: Hamilton Health Sciences , doi 10.13039/100008360;
                Award ID: 20010779
                Categories
                Lung Cancer
                Research Article
                Research Articles
                Custom metadata
                2.0
                November 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.4 mode:remove_FC converted:02.11.2023

                Oncology & Radiotherapy
                canagliflozin,hif‐1α,lung cancer,mtor,radiotherapy
                Oncology & Radiotherapy
                canagliflozin, hif‐1α, lung cancer, mtor, radiotherapy

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