Literature DB >> 33731366

Chromatin Accessibility Identifies Regulatory Elements Predictive of Gene Expression and Disease Outcome in Multiple Myeloma.

Paula M Vertino1, Lawrence H Boise2,3, Benjamin G Barwick2,3, Vikas A Gupta4,3, Shannon M Matulis4,3, Jonathan C Patton5, Doris R Powell4,3, Yanyan Gu4,3, David L Jaye3,6, Karen N Conneely7, Yin C Lin8, Craig C Hofmeister4,3, Ajay K Nooka4,3, Jonathan J Keats9, Sagar Lonial4,3.   

Abstract

PURPOSE: Multiple myeloma is a malignancy of plasma cells. Extensive genetic and transcriptional characterization of myeloma has identified subtypes with prognostic and therapeutic implications. In contrast, relatively little is known about the myeloma epigenome. EXPERIMENTAL
DESIGN: CD138+CD38+ myeloma cells were isolated from fresh bone marrow aspirate or the same aspirate after freezing for 1-6 months. Gene expression and chromatin accessibility were compared between fresh and frozen samples by RNA sequencing (RNA-seq) and assay for transpose accessible chromatin sequencing (ATAC-seq). Chromatin accessible regions were used to identify regulatory RNA expression in more than 700 samples from newly diagnosed patients in the Multiple Myeloma Research Foundation CoMMpass trial (NCT01454297).
RESULTS: Gene expression and chromatin accessibility of cryopreserved myeloma recapitulated that of freshly isolated samples. ATAC-seq performed on a series of biobanked specimens identified thousands of chromatin accessible regions with hundreds being highly coordinated with gene expression. More than 4,700 of these chromatin accessible regions were transcribed in newly diagnosed myelomas from the CoMMpass trial. Regulatory element activity alone recapitulated myeloma gene expression subtypes, and in particular myeloma subtypes with immunoglobulin heavy chain translocations were defined by transcription of distal regulatory elements. Moreover, enhancer activity predicted oncogene expression implicating gene regulatory mechanisms in aggressive myeloma.
CONCLUSIONS: These data demonstrate the feasibility of using biobanked specimens for retrospective studies of the myeloma epigenome and illustrate the unique enhancer landscapes of myeloma subtypes that are coupled to gene expression and disease progression. ©2021 American Association for Cancer Research.

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Year:  2021        PMID: 33731366      PMCID: PMC8172525          DOI: 10.1158/1078-0432.CCR-20-2931

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  62 in total

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3.  STAR: ultrafast universal RNA-seq aligner.

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4.  Significant biological role of sp1 transactivation in multiple myeloma.

Authors:  Mariateresa Fulciniti; Samir Amin; Puru Nanjappa; Scott Rodig; Rao Prabhala; Cheng Li; Stephane Minvielle; Yu-Tzu Tai; Pierfrancesco Tassone; Herve Avet-Loiseau; Teru Hideshima; Kenneth C Anderson; Nikhil C Munshi
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Journal:  Blood       Date:  1997-04-01       Impact factor: 22.113

6.  The MMSET protein is a histone methyltransferase with characteristics of a transcriptional corepressor.

Authors:  Jotin Marango; Manabu Shimoyama; Hitomi Nishio; Julia A Meyer; Dong-Joon Min; Andres Sirulnik; Yolanda Martinez-Martinez; Marta Chesi; P Leif Bergsagel; Ming-Ming Zhou; Samuel Waxman; Boris A Leibovitch; Martin J Walsh; Jonathan D Licht
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Authors:  Matthew D Wilkerson; D Neil Hayes
Journal:  Bioinformatics       Date:  2010-04-28       Impact factor: 6.937

8.  The t(4;14) translocation in myeloma dysregulates both FGFR3 and a novel gene, MMSET, resulting in IgH/MMSET hybrid transcripts.

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Journal:  Blood       Date:  1998-11-01       Impact factor: 22.113

9.  ARNT/HIF-1β links high-risk 1q21 gain and microenvironmental hypoxia to drug resistance and poor prognosis in multiple myeloma.

Authors:  Chuan Wu; Ting Yang; Yingmin Liu; Yicheng Lu; Yanping Yang; Xiaobo Liu; Xuelian Liu; Long Ye; Yue Sun; Xue Wang; Qingchao Li; Peiyu Yang; Xiaoyuan Yu; Sujun Gao; Shaji Kumar; Fengyan Jin; Yun Dai; Wei Li
Journal:  Cancer Med       Date:  2018-06-21       Impact factor: 4.452

10.  Plasma cell differentiation is coupled to division-dependent DNA hypomethylation and gene regulation.

Authors:  Benjamin G Barwick; Christopher D Scharer; Alexander P R Bally; Jeremy M Boss
Journal:  Nat Immunol       Date:  2016-08-08       Impact factor: 25.606

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  3 in total

1.  Structural variants shape the genomic landscape and clinical outcome of multiple myeloma.

Authors:  Cody Ashby; Eileen M Boyle; Michael A Bauer; Aneta Mikulasova; Christopher P Wardell; Louis Williams; Ariel Siegel; Patrick Blaney; Marc Braunstein; David Kaminetsky; Jonathan Keats; Francesco Maura; Ola Landgren; Brian A Walker; Faith E Davies; Gareth J Morgan
Journal:  Blood Cancer J       Date:  2022-05-30       Impact factor: 9.812

2.  Subtype-Independent ANP32E Reduction During Breast Cancer Progression in Accordance with Chromatin Relaxation.

Authors:  Paula M Vertino; Patrick J Murphy; Garrett L Ruff; Kristin E Murphy; Zachary R Smith
Journal:  BMC Cancer       Date:  2021-12-18       Impact factor: 4.430

3.  Bone Marrow Stroma-Induced Transcriptome and Regulome Signatures of Multiple Myeloma.

Authors:  Sebastian A Dziadowicz; Lei Wang; Halima Akhter; Drake Aesoph; Tulika Sharma; Donald A Adjeroh; Lori A Hazlehurst; Gangqing Hu
Journal:  Cancers (Basel)       Date:  2022-02-13       Impact factor: 6.639

  3 in total

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