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

转录因子 基因表达谱 基因表达调控
作者
Benjamin G. Barwick,Vikas Gupta,Shannon M. Matulis,Jonathan C. Patton,Doris R. Powell,Yanyan Gu,David L. Jaye,Karen N. Conneely,Yin C. Lin,Craig C. Hofmeister,Ajay K. Nooka,Jonathan J Keats,Sagar Lonial,Paula M. Vertino,Lawrence H. Boise
出处
期刊:Clinical Cancer Research [American Association for Cancer Research]
卷期号:27 (11): 3178-3189 被引量:3
标识
DOI:10.1158/1078-0432.ccr-20-2931
摘要

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.

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