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      Targeting mitochondrial respiration and the BCL2 family in high‐grade MYC‐associated B‐cell lymphoma

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          Abstract

          Multiple molecular features, such as activation of specific oncogenes (e.g., MYC, BCL2) or a variety of gene expression signatures, have been associated with disease course in diffuse large B‐cell lymphoma (DLBCL), although their relationships and implications for targeted therapy remain to be fully unraveled. We report that MYC activity is closely correlated with—and most likely a driver of—gene signatures related to oxidative phosphorylation (OxPhos) in DLBCL, pointing to OxPhos enzymes, in particular mitochondrial electron transport chain (ETC) complexes, as possible therapeutic targets in high‐grade MYC‐associated lymphomas. In our experiments, indeed, MYC sensitized B cells to the ETC complex I inhibitor IACS‐010759. Mechanistically, IACS‐010759 triggered the integrated stress response (ISR) pathway, driven by the transcription factors ATF4 and CHOP, which engaged the intrinsic apoptosis pathway and lowered the apoptotic threshold in MYC‐overexpressing cells. In line with these findings, the BCL2‐inhibitory compound venetoclax synergized with IACS‐010759 against double‐hit lymphoma (DHL), a high‐grade malignancy with concurrent activation of MYC and BCL2. In BCL2‐negative lymphoma cells, instead, killing by IACS‐010759 was potentiated by the Mcl‐1 inhibitor S63845. Thus, combining an OxPhos inhibitor with select BH3‐mimetic drugs provides a novel therapeutic principle against aggressive, MYC‐associated DLBCL variants.

          Abstract

          We show that MYC activity is closely correlated with OxPhos‐associated gene signatures in human B‐cell lymphomas and sensitizes B cells to the mitochondrial complex I inhibitor IACS‐010759. This molecule shows synergy with select BH3‐mimetic drugs in killing cancer cells, and in particular with the BCL2 inhibitor venetoclax against the aggressive double‐hit lymphoma subtype, with promising antitumoral effects in preclinical models.

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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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            Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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              The Molecular Signatures Database (MSigDB) hallmark gene set collection.

              The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.
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                Author and article information

                Contributors
                giulio.donati@ieo.it
                bruno.amati@ieo.it
                Journal
                Mol Oncol
                Mol Oncol
                10.1002/(ISSN)1878-0261
                MOL2
                Molecular Oncology
                John Wiley and Sons Inc. (Hoboken )
                1574-7891
                1878-0261
                11 November 2021
                March 2022
                : 16
                : 5 ( doiID: 10.1002/mol2.v16.5 )
                : 1132-1152
                Affiliations
                [ 1 ] European Institute of Oncology (IEO)—IRCCS Milan Italy
                [ 2 ] IRCCS San Raffaele Scientific Institute Milan Italy
                [ 3 ] Translational Research to Advance Therapeutics and Innovation in Oncology (TRACTION) Houston TX USA
                [ 4 ] Department of Genomic Medicine University of Texas MD Anderson Cancer Center Houston TX USA
                [ 5 ]Present address: IRCCS San Raffaele Scientific Institute Milan Italy
                Author notes
                [*] [* ] Correspondence

                G. Donati and B. Amati, European Institute of Oncology, Via Adamello 16, 20139 Milan, Italy

                Fax: +39 02 9437 5990

                Tel: +39 02 5748 9824

                E‐mails: giulio.donati@ 123456ieo.it (G.D.); bruno.amati@ 123456ieo.it (B.A.)

                Author information
                https://orcid.org/0000-0002-2958-1799
                Article
                MOL213115
                10.1002/1878-0261.13115
                8895457
                34632715
                8177a377-d42c-47ed-9495-3758e615b6a9
                © 2021 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
                : 27 August 2021
                : 17 May 2021
                : 08 October 2021
                Page count
                Figures: 8, Tables: 0, Pages: 1152, Words: 12149
                Funding
                Funded by: Associazione Italiana per la Ricerca sul Cancro , doi 10.13039/501100005010;
                Award ID: IG2015‐16768
                Award ID: IG2018‐21594
                Award ID: IG2019‐23513
                Funded by: Fondazione Umberto Veronesi , doi 10.13039/501100004710;
                Funded by: Ministero della Salute , doi 10.13039/501100003196;
                Award ID: RF‐2011‐02346976
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                March 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.2 mode:remove_FC converted:04.03.2022

                Oncology & Radiotherapy
                bcl2,chemotherapy,dlbcl,integrated stress response,myc,oxphos
                Oncology & Radiotherapy
                bcl2, chemotherapy, dlbcl, integrated stress response, myc, oxphos

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