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癌症中遗传变异及其病理效应的三维基因组图谱

A 3D Genome Atlas of Genetic Variants and Their Pathological Effects in Cancer.

作者信息

Tang Li, Hill Matthew C, He Mingxing, Chen Junhao, Wang Zirui, Ellinor Patrick T, Li Min

机构信息

School of Computer Science and Engineering, Central South University, Changsha, 410083, China.

Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, 02129, USA.

出版信息

Adv Sci (Weinh). 2025 May;12(19):e2408420. doi: 10.1002/advs.202408420. Epub 2025 Mar 25.

Abstract

The hierarchical organization of the eukaryotic genome is crucial for nuclear activities and cellular development. Genetic aberrations can disrupt this 3D genomic architecture, potentially driving oncogenesis. However, current research often lacks a comprehensive perspective, focusing on specific mutation types and singular 3D structural levels. Here, pathological changes from chromosomes to nucleotides are systematically cataloged, including 10 789 interchromosomal translocations (ICTs), 18 863 structural variants (SVs), and 162 769 single nucleotide polymorphisms (SNPs). The multilayered analysis reveals that fewer than 10% of ICTs disrupt territories via potent 3D interactions, and only a minimal fraction of SVs disrupt compartments or intersect topologically associated domain structures, yet these events significantly influence gene expression. Pathogenic SNPs typically show reduced interactions within the 3D genomic space. To investigate the effects of variants in the context of 3D organization, a two-phase scoring algorithm, 3DFunc, is developed to evaluate the pathogenicity of variant-gene pairs in cancer. Using 3DFunc, IGHV3-23's critical role in chronic lymphocytic leukemia is identified and it is found that three pathological SNPs (rs6605578, rs7814783, rs2738144) interact with DEFA3. Additionally, 3DGAtlas is introduced, which provides a highly accessible 3D genome atlas and a valuable resource for exploring the pathological effects of genetic mutations in cancer.

摘要

真核生物基因组的层次结构对于核活动和细胞发育至关重要。基因畸变会破坏这种三维基因组结构,有可能推动肿瘤发生。然而,目前的研究往往缺乏全面的视角,专注于特定的突变类型和单一的三维结构水平。在这里,系统地梳理了从染色体到核苷酸的病理变化,包括10789个染色体间易位(ICTs)、18863个结构变异(SVs)和162769个单核苷酸多态性(SNPs)。多层次分析表明,不到10%的ICTs通过强大的三维相互作用破坏结构域,只有极小一部分SVs破坏区室或与拓扑相关结构域结构相交,但这些事件会显著影响基因表达。致病性SNP通常在三维基因组空间内表现出相互作用减少。为了在三维组织背景下研究变异的影响,开发了一种两阶段评分算法3DFunc,以评估癌症中变异-基因对的致病性。使用3DFunc,确定了IGHV3-23在慢性淋巴细胞白血病中的关键作用,并发现三个病理SNP(rs6605578、rs7814783、rs2738144)与DEFA3相互作用。此外,还引入了3DGAtlas,它提供了一个高度可访问的三维基因组图谱,是探索癌症中基因突变病理效应的宝贵资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5109/12097094/67d5c83d00f6/ADVS-12-2408420-g004.jpg

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