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      Sex-Biased ZRSR2 Mutations in Myeloid Malignancies Impair Plasmacytoid Dendritic Cell Activation and Apoptosis

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      1 , 1 , 2 , 1 , 1 , 1 , 3 , 4 , 1 , 5 , 6 , 6 , 2 , 1 , 7 , 7 , 8 , 8 , 5 , 9 , 5 , 10 , 11 , 12 , 13 , 1 , 6 , 1 , 2 , 14 , 14 , 7 , 3 , 2 , 15 , 16 , 1 , 6 , 17 , * ,
      Cancer Discovery
      American Association for Cancer Research

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          Abstract

          BPDCN, a male-biased leukemia, was found to harbor frequent male-restricted ZRSR2 mutations, with loss of this X chromosome gene causing poor dendritic cell response to inflammatory stimuli and impaired subsequent cell death.

          Abstract

          Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is an aggressive leukemia of plasmacytoid dendritic cells (pDC). BPDCN occurs at least three times more frequently in men than in women, but the reasons for this sex bias are unknown. Here, studying genomics of primary BPDCN and modeling disease-associated mutations, we link acquired alterations in RNA splicing to abnormal pDC development and inflammatory response through Toll-like receptors. Loss-of-function mutations in ZRSR2, an X chromosome gene encoding a splicing factor, are enriched in BPDCN, and nearly all mutations occur in males. ZRSR2 mutation impairs pDC activation and apoptosis after inflammatory stimuli, associated with intron retention and inability to upregulate the transcription factor IRF7. In vivo, BPDCN-associated mutations promote pDC expansion and signatures of decreased activation. These data support a model in which male-biased mutations in hematopoietic progenitors alter pDC function and confer protection from apoptosis, which may impair immunity and predispose to leukemic transformation.

          Significance:

          Sex bias in cancer is well recognized, but the underlying mechanisms are incompletely defined. We connect X chromosome mutations in ZRSR2 to an extremely male-predominant leukemia. Aberrant RNA splicing induced by ZRSR2 mutation impairs dendritic cell inflammatory signaling, interferon production, and apoptosis, revealing a sex- and lineage-related tumor suppressor pathway.

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          Most cited references76

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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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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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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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                Author and article information

                Journal
                Cancer Discov
                Cancer Discov
                Cancer Discovery
                American Association for Cancer Research
                2159-8274
                2159-8290
                01 February 2022
                06 October 2021
                : 12
                : 2
                : 522-541
                Affiliations
                [1 ]Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.
                [2 ]Cancer Science Institute of Singapore, National University of Singapore, Singapore.
                [3 ]Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York.
                [4 ]Division of Hematology, Department of Medicine, Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine, Miami, Florida.
                [5 ]Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
                [6 ]Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
                [7 ]Université Bourgogne Franche-Comté, INSERM, EFS BFC, UMR1098, Interactions Hôte-Greffon-Tumeur/Ingénierie Cellulaire et Génique, Besançon, France.
                [8 ]H3 Biomedicine, Cambridge, Massachusetts.
                [9 ]Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts.
                [10 ]Inserm U1245, Centre Henri Becquerel, Université de Rouen, IRIB, Rouen, France.
                [11 ]Department of Experimental, Diagnostic, and Specialty Medicine, Bologna University Medical School, Bologna, Italy.
                [12 ]Department of Biomolecular Strategies, Genetics, Avant-Garde Therapies and Neurosciences (SBGN), Euro-Mediterranean Institute of Science and Technology (IEMEST), Palermo, Italy.
                [13 ]School of Health, Department of Pathology, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya.
                [14 ]Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas.
                [15 ]Cedars-Sinai Medical Center, Division of Hematology/Oncology, UCLA School of Medicine, Los Angeles, California.
                [16 ]Department of Hematology-Oncology, National University Cancer Institute of Singapore (NCIS), National University Hospital, Singapore.
                [17 ]Ludwig Center at Harvard, Boston, Massachusetts.
                Author notes
                [* ] Corresponding Author: Andrew A. Lane, Dana-Farber Cancer Institute, 450 Brookline Avenue, Mayer 413, Boston, MA 02215. Phone: 617-632-4589; E-mail: andrew_lane@ 123456dfci.harvard.edu
                Author information
                https://orcid.org/0000-0001-8422-0008
                https://orcid.org/0000-0002-7340-3359
                https://orcid.org/0000-0001-7876-624X
                https://orcid.org/0000-0003-3841-6637
                https://orcid.org/0000-0002-2991-328X
                https://orcid.org/0000-0003-4407-6325
                https://orcid.org/0000-0002-6477-5679
                https://orcid.org/0000-0003-1897-2265
                https://orcid.org/0000-0001-9013-0105
                https://orcid.org/0000-0001-5880-9337
                https://orcid.org/0000-0002-6804-7943
                https://orcid.org/0000-0002-9432-0595
                https://orcid.org/0000-0002-8724-3907
                https://orcid.org/0000-0002-1670-6513
                https://orcid.org/0000-0001-7380-0226
                Article
                CD-20-1513
                10.1158/2159-8290.CD-20-1513
                8831459
                34615655
                bf0b49c2-0e63-46b6-9eb2-ec6bc7ec3712
                ©2021 The Authors; Published by the American Association for Cancer Research

                This open access article is distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.

                History
                : 16 October 2020
                : 17 August 2021
                : 01 October 2021
                Page count
                Pages: 20
                Funding
                Funded by: NCI, DOI https://doi.org/10.13039/100000054;
                Award ID: R37 CA225191
                Funded by: NCI, DOI https://doi.org/10.13039/100000054;
                Award ID: R35 CA231958
                Funded by: Department of Defense, DOI https://doi.org/10.13039/100000005;
                Award ID: W81XWH-20-1-0683
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                Research Articles

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