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      CECR2 drives breast cancer metastasis by promoting NF-κB signaling and macrophage-mediated immune suppression

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          Abstract

          Metastasis is the major cause of cancer-related deaths due to the lack of effective therapies. Emerging evidence suggests that certain epigenetic and transcriptional regulators drive cancer metastasis and could be targeted for metastasis treatment. To identify epigenetic regulators of breast cancer metastasis, we profiled the transcriptomes of matched pairs of primary breast tumors and metastases from human patients. We found that distant metastases are more immune inert with increased M2 macrophages compared to their matched primary tumors. The acetyl-lysine reader, cat eye syndrome chromosome region candidate 2 (CECR2), was the top up-regulated epigenetic regulator in metastases associated with an increased abundance of M2 macrophages and worse metastasis-free survival. CECR2 was required for breast cancer metastasis in multiple mouse models, with more profound effect in the immunocompetent setting. Mechanistically, the nuclear factor κB (NF-κB) family member v-rel avian reticuloendotheliosis viral oncogene homolog A (RELA) recruits CECR2 to increase chromatin accessibility and activate the expression of their target genes. These target genes include multiple metastasis-promoting genes, such as TNC , MMP2 , and VEGFA , and cytokine genes CSF1 and CXCL1 , which are critical for immunosuppression at metastatic sites. Consistent with these results, pharmacological inhibition of CECR2 bromodomain impeded NF-κB–mediated immune suppression by macrophages and inhibited breast cancer metastasis. These results reveal that targeting CECR2 may be a strategy to treat metastatic breast cancer.

          Abstract

          Depletion or inhibition of CECR2 impedes breast cancer metastasis by suppressing NF-κB signaling, migration, invasion, and immune suppression.

          Modulating metastasis

          Breast cancer metastasis is thought to be driven through both epigenetic and transcriptional regulators, either of which could be targeted as a therapeutic strategy. Here, Zhang et al. identified the acetyl-lysine reader, CECR2, as an epigenetic regulator required for breast cancer metastasis in mouse models. CECR2 promoted M2 macrophage polarization and increased expression of metastasis-associated signaling molecules. Deletion or pharmacological inhibition of CECR2 prevented breast cancer metastasis in mouse models, suggesting that CECR2 should be explored as a therapeutic target for breast cancer.

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          Most cited references84

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          Is Open Access

          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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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              The Sequence Alignment/Map format and SAMtools

              Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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                Author and article information

                Contributors
                Journal
                Science Translational Medicine
                Sci. Transl. Med.
                American Association for the Advancement of Science (AAAS)
                1946-6234
                1946-6242
                February 02 2022
                February 02 2022
                : 14
                : 630
                Affiliations
                [1 ]Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA.
                [2 ]Laboratory of Comparative Pathology, Department of Veterinary Clinical Sciences, Faculty of Veterinary Medicine, Hokkaido University, Sapporo 060-0818, Japan.
                [3 ]Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA 15232, USA.
                [4 ]Department of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.
                [5 ]Yale Cancer Center, Yale School of Medicine, New Haven, CT 06520, USA.
                [6 ]Breast Medical Oncology, Yale Cancer Center, Yale University, New Haven, CT 06520, USA.
                [7 ]Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA.
                [8 ]Yale Center for Immuno-Oncology, Yale School of Medicine, New Haven, CT 06520, USA.
                Article
                10.1126/scitranslmed.abf5473
                35108062
                f5bb71e8-75e8-46eb-a6eb-48d6535830ae
                © 2022
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