Department of Pancreatic and Gastric Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, P. R. China.
Annoroad Gene Technology Co. Ltd, Beijing, 100176, P. R. China.
Adv Sci (Weinh). 2022 Jun;9(18):e2200818. doi: 10.1002/advs.202200818. Epub 2022 May 15.
Structural variations (SVs) are the greatest source of variations in the genome and can lead to oncogenesis. However, the identification and interpretation of SVs in human cancer remain technologically challenging. Here, long-read sequencing is first employed to depict the signatures of structural variations in carcinogenesis of human pancreatic ductal epithelium. Then widespread reprogramming of the 3D chromatin architecture is revealed by an in situ Hi-C technique. Integrative analyses indicate that the distribution pattern of SVs among the 3D genome is highly cell-type specific and the bulk remodeling effects of SVs in the chromatin organization partly depend on intercellular genomic heterogeneity. Meanwhile, contact domains tend to minimize these disrupting effects of SVs within local adjacent genomic regions to maintain overall stability. Notably, complex genomic rearrangements involving two key driver genes CDKN2A and SMAD4 are identified, and their influence on the expression of oncogenes MIR31HG, MYO5B, etc., are further elucidated from both a linear view and 3D perspective. Overall, this work provides a genome-wide resource and highlights the impact, complexity, and dynamicity of the interplay between structural variations and high-order chromatin organization, which expands the current understanding of the pathogenesis of SVs in human cancer.
结构变异(SVs)是基因组变异的最大来源,并可能导致肿瘤发生。然而,人类癌症中 SVs 的鉴定和解释仍然具有技术挑战性。在这里,首先采用长读测序来描绘人类胰腺导管上皮癌变过程中结构变异的特征。然后通过原位 Hi-C 技术揭示了广泛的 3D 染色质结构的重编程。综合分析表明,SV 在 3D 基因组中的分布模式具有高度的细胞类型特异性,并且 SV 在染色质组织中的大量重塑效应部分取决于细胞间基因组异质性。同时,接触域倾向于最小化 SV 在局部相邻基因组区域内的这些破坏效应,以保持整体稳定性。值得注意的是,鉴定出涉及两个关键驱动基因 CDKN2A 和 SMAD4 的复杂基因组重排,并从线性和 3D 角度进一步阐明它们对癌基因 MIR31HG、MYO5B 等表达的影响。总的来说,这项工作提供了一个全基因组资源,并强调了结构变异和高级染色质组织之间相互作用的影响、复杂性和动态性,这扩展了我们对人类癌症中 SV 发病机制的现有理解。