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      Mutant NPM1 Hijacks Transcriptional Hubs to Maintain Pathogenic Gene Programs in Acute Myeloid Leukemia

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          Abstract

          Mutant NPM1 in leukemia obtains neomorphic activity to hijack active HOXA/B and MEIS1 transcription on chromatin via the association of XPO1 and blocks the histone deacetylase activity associated with myeloid differentiation.

          Abstract

          Nucleophosmin (NPM1) is a ubiquitously expressed nucleolar protein with a wide range of biological functions. In 30% of acute myeloid leukemia (AML), the terminal exon of NPM1 is often found mutated, resulting in the addition of a nuclear export signal and a shift of the protein to the cytoplasm (NPM1c). AMLs carrying this mutation have aberrant expression of the HOXA/B genes, whose overexpression leads to leukemogenic transformation. Here, for the first time, we comprehensively prove that NPM1c binds to a subset of active gene promoters in NPM1c AMLs, including well-known leukemia-driving genes— HOXA/B cluster genes and MEIS1. NPM1c sustains the active transcription of key target genes by orchestrating a transcription hub and maintains the active chromatin landscape by inhibiting the activity of histone deacetylases. Together, these findings reveal the neomorphic function of NPM1c as a transcriptional amplifier for leukemic gene expression and open up new paradigms for therapeutic intervention.

          Significance:

          NPM1 mutation is the most common mutation in AML, yet the mechanism of how the mutant protein results in AML remains unclear. Here, for the first time, we prove mutant NPM1 directly binds to active chromatin regions and hijacks the transcription of AML-driving genes.

          See related article by Uckelmann et al., p. 746.

          This article is highlighted in the In This Issue feature, p. 517

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          Most cited references62

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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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            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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              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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                Author and article information

                Journal
                Cancer Discov
                Cancer Discov
                Cancer Discovery
                American Association for Cancer Research
                2159-8274
                2159-8290
                01 March 2023
                01 December 2022
                : 13
                : 3
                : 724-745
                Affiliations
                [1 ]Department of Epigenetics, Van Andel Research Institute, Grand Rapids, Michigan.
                [2 ]Institute of Biomedical Big Data, Wenzhou Medical University, Wenzhou, China.
                [3 ]Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California.
                [4 ]Department of Cancer Biology and Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
                [5 ]Department of Pathology, University of Michigan, Ann Arbor, Michigan.
                [6 ]Department of Biochemistry and Molecular Biology, University of Texas Health Science Center at Houston, McGovern Medical School, Houston, Texas.
                Author notes
                [#]

                Note: X.Q.D. Wang, D. Fan, Q. Han, and Y. Liu contributed equally to this article.

                [##]

                J. Su, S. Chong, L. Wan, and X. Zhang jointly supervised this article.

                Current address for X.Q.D. Wang: Department of Biochemistry, University of Southern California, Los Angeles, California.

                [* ] Corresponding Authors: Xiaotian Zhang, University of Texas Health Science Center at Houston, Room MSB 6.202, 6431 Fannin Street, Houston, TX 77030. Phone: 713-500-5146; E-mail: Xiaotian.Zhang@ 123456uth.tmc.edu ; Liling Wan, University of Pennsylvania, BRB II/III, RM751, 421 Curie Boulevard, Philadelphia, PA 19104. Phone: 215-898-3116; E-mail: liling.wan@ 123456pennmedicine.upenn.edu ; and Shasha Chong, California Institute of Technology, 1200 East California Boulevard, MC 147-75, Pasadena, CA 91125. Phone: 626-395-5736; E-mail: schong@ 123456caltech.edu

                Cancer Discov 2023;13:724–45

                Author information
                https://orcid.org/0000-0003-4951-5788
                https://orcid.org/0000-0002-1471-1183
                https://orcid.org/0000-0003-3464-8967
                https://orcid.org/0000-0002-2223-7223
                https://orcid.org/0000-0003-4862-9484
                https://orcid.org/0000-0003-0806-4335
                https://orcid.org/0000-0003-0160-8774
                https://orcid.org/0000-0003-2210-1024
                https://orcid.org/0000-0001-8993-6611
                https://orcid.org/0000-0001-5721-1974
                https://orcid.org/0000-0002-5080-9604
                https://orcid.org/0000-0003-2058-0658
                https://orcid.org/0000-0002-6180-9095
                https://orcid.org/0000-0003-1054-6042
                https://orcid.org/0000-0002-5372-311X
                https://orcid.org/0000-0002-5444-0437
                https://orcid.org/0000-0002-9533-4761
                Article
                CD-22-0424
                10.1158/2159-8290.CD-22-0424
                9975662
                36455589
                88a082d1-6e22-4882-9794-c1e1dacd4418
                ©2022 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
                : 15 April 2022
                : 15 September 2022
                : 30 November 2022
                Page count
                Pages: 22
                Funding
                Funded by: American Society of Hematology (ASH), https://doi.org/10.13039/100001422;
                Award ID: Fellow 2018
                Award Recipient :
                Funded by: Edward P. Evans Foundation, https://doi.org/10.13039/100008884;
                Award ID: Young Investigator award 2018
                Award Recipient :
                Funded by: Pew Charitable Trusts (Pew), https://doi.org/10.13039/100000875;
                Award Recipient :
                Funded by: NIH Office of the Director (OD), https://doi.org/10.13039/100000052;
                Award ID: 1DP2HG012443
                Award Recipient :
                Funded by: Pew Charitable Trusts (Pew), https://doi.org/10.13039/100000875;
                Award ID: 00036068
                Award Recipient :
                Funded by: Searle Scholars Program (SSP), https://doi.org/10.13039/100014185;
                Award ID: SSP-2022-108
                Award Recipient :
                Funded by: Shurl and Kay Curci Foundation (SKCF), https://doi.org/10.13039/100010319;
                Award Recipient :
                Funded by: National Cancer Institute (NCI), https://doi.org/10.13039/100000054;
                Award ID: R01CA207272
                Award Recipient :
                Funded by: National Cancer Institute (NCI), https://doi.org/10.13039/100000054;
                Award ID: R01CA240514
                Funded by: National Cancer Institute (NCI), https://doi.org/10.13039/100000054;
                Award ID: R01CA160467
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                Research Articles

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