研究动态
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非编码调节功能对胰岛素瘤发展的影响。

Implications of noncoding regulatory functions in the development of insulinomas.

发表日期:2024 Jul 02
作者: Mireia Ramos-Rodríguez, Marc Subirana-Granés, Richard Norris, Valeria Sordi, Ángel Fernández, Georgina Fuentes-Páez, Beatriz Pérez-González, Clara Berenguer Balaguer, Helena Raurell-Vila, Murad Chowdhury, Raquel Corripio, Stefano Partelli, Núria López-Bigas, Silvia Pellegrini, Eduard Montanya, Montserrat Nacher, Massimo Falconi, Ryan Layer, Meritxell Rovira, Abel González-Pérez, Lorenzo Piemonti, Lorenzo Pasquali
来源: BIOMEDICINE & PHARMACOTHERAPY

摘要:

胰岛素瘤是由胰腺β细胞产生的罕见神经内分泌肿瘤,其特征是异常增殖和胰岛素分泌改变,导致葡萄糖稳态失败。为了揭示非编码调控区及其畸变在这些肿瘤发展中的作用,我们将表观遗传和转录组分析与全基因组测序结合起来。结果,我们揭示了与调节功能变化相关的体细胞突变。至关重要的是,这些区域影响胰岛素分泌、肿瘤发展和表观遗传修饰基因,包括多梳复合体成分。染色质重塑在患者之间共享的胰岛素瘤选择性域中很明显,其中包含一组由 SOX17 结合基序主导的特定调节序列。此外,许多这些区域在 β 细胞中被 H3K27me3 抑制,这表明肿瘤转变涉及多梳靶向结构域的去抑制。我们的工作提供了影响β细胞在胰岛素瘤进展过程中的功能和命运的异常顺式调控元件的概要,以及识别编码和非编码驱动突变的框架。版权所有©2024。由爱思唯尔公司出版。保留所有权利。
Insulinomas are rare neuroendocrine tumors arising from pancreatic β cells, characterized by aberrant proliferation and altered insulin secretion, leading to glucose homeostasis failure. With the aim of uncovering the role of noncoding regulatory regions and their aberrations in the development of these tumors, we coupled epigenetic and transcriptome profiling with whole-genome sequencing. As a result, we unraveled somatic mutations associated with changes in regulatory functions. Critically, these regions impact insulin secretion, tumor development, and epigenetic modifying genes, including polycomb complex components. Chromatin remodeling is apparent in insulinoma-selective domains shared across patients, containing a specific set of regulatory sequences dominated by the SOX17 binding motif. Moreover, many of these regions are H3K27me3 repressed in β cells, suggesting that tumoral transition involves derepression of polycomb-targeted domains. Our work provides a compendium of aberrant cis-regulatory elements affecting the function and fate of β cells in their progression to insulinomas and a framework to identify coding and noncoding driver mutations.Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.