转录可塑性驱动多发性骨髓瘤的 IMiD 和 p300 抑制剂抗药性

IF 11.5 Q1 HEMATOLOGY

Blood Cancer Discovery Pub Date : 2024-01-08 DOI:10.1158/2643-3230.BCD-23-0223

Seongseok Yun, John L Cleveland

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引用次数: 0

摘要

摘要：在本期《血癌发现》（Blood Cancer Discovery）杂志上，Neri及其同事和Welsh及其同事进行了RNA测序、染色质免疫沉淀测序、利用测序法测定转座酶可进入的染色质以及遗传学研究，以描述多发性骨髓瘤免疫调节药物（IMiD）耐药性的潜在机制。他们证明，IMiD耐药性是由MYC和IRF4通过转录可塑性持续表达驱动的，转录可塑性涉及ETV4和BATF蛋白的诱导、这些蛋白与其超级增强子的结合以及BRD4和p300的招募。最后，这些研究表明，IMiD和p300抑制剂的组合是治疗多发性骨髓瘤的一种很有前景的策略。参见 Neri 等人的相关文章(9)。参见 Welsh 等人的相关文章（10）。

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Transcriptional Plasticity Drives IMiD and p300 Inhibitor Resistance in Multiple Myeloma.

Summary: In this issue of Blood Cancer Discovery, Neri, Barwick, and colleagues and Welsh, Barwick, and colleagues performed RNA sequencing, chromatin immunoprecipitation sequencing, assay for transposase-accessible chromatin using sequencing, and genetic studies to characterize the underlying mechanisms of immunomodulatory drug (IMiD) resistance in multiple myeloma. They demonstrated that IMiD resistance is driven by sustained expression of MYC and IRF4 via transcriptional plasticity that involves induction of ETV4 and BATF proteins, the binding of these proteins to their super-enhancers, and the recruitment of BRD4 and p300. Finally, these studies suggest IMiD and p300 inhibitor combination as a promising therapeutic strategy in multiple myeloma. See related article by Neri, Barwick, et al., p. 56 (9). See related article by Welsh, Barwick, et al., p. 34 (10).

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来源期刊

Blood Cancer Discovery Multiple-

CiteScore

12.70

自引率

1.80%

发文量

139

期刊介绍： The journal Blood Cancer Discovery publishes high-quality Research Articles and Briefs that focus on major advances in basic, translational, and clinical research of leukemia, lymphoma, myeloma, and associated diseases. The topics covered include molecular and cellular features of pathogenesis, therapy response and relapse, transcriptional circuits, stem cells, differentiation, microenvironment, metabolism, immunity, mutagenesis, and clonal evolution. These subjects are investigated in both animal disease models and high-dimensional clinical data landscapes. The journal also welcomes submissions on new pharmacological, biological, and living cell therapies, as well as new diagnostic tools. They are interested in prognostic, diagnostic, and pharmacodynamic biomarkers, and computational and machine learning approaches to personalized medicine. The scope of submissions ranges from preclinical proof of concept to clinical trials and real-world evidence. Blood Cancer Discovery serves as a forum for diverse ideas that shape future research directions in hematooncology. In addition to Research Articles and Briefs, the journal also publishes Reviews, Perspectives, and Commentaries on topics of broad interest in the field.