PO.MCB08.04 · 分子与细胞生物学

来自单倍型特异性拷贝数改变泛癌图谱的染色体不稳定性基因组特征

Genomic signatures of chromosomal instability from a pan-cancer landscape of haplotype-specific copy-number alterations

编号 5934 展板 22 时间 4/21 02:00–05:00 区域 Section 21 主讲 Chunyang Bao, PhD

分会场 Genetic and Transcriptomic Dissection of Cancer Evolution

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作者与单位 Authors & Affiliations

Chunyang Bao¹, Matthew Leventhal², Hansol Park¹, Gang-Hee Lee¹, Ryul Kim¹, Won-Chul Lee¹, Jonghoon Lee¹, Yoonsuh Lee¹, Beomki Lee³, David Lehotzky⁴, Ron Solan⁴, Antonia Kowalewski⁴, Xavi Loinaz⁴, Vasuki Narasimha Swamy⁴, David I. Heiman⁴, Samantha Van Seters⁴, Saveliy Belkin⁴, Sam Wiseman⁴, Andrew D. Cherniack⁴, Luis Antonio Corchete Sanchez⁴, Brian P. Danysh⁴, Zachary Everton⁴, Chip Stewart⁴, Haruna Tomono⁴, Gengchao Wang⁴, Esther Rheinbay⁴, Gad Getz⁴, Cheng-Zhong Zhang², Young Seok Ju¹

¹Inocras Inc., San Diego, CA,²Department of Data Science, Dana-Farber Cancer Institute, Boston, MA,³Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Dajeon, Korea, Republic of,⁴Cancer Program, Broad Institute of MIT and Harvard, Cambridge, MA

摘要 Abstract

中文摘要

全染色体和节段性拷贝数变化在人类癌症中几乎无处不在。在此，我们基于The Cancer Genome Atlas（TCGA）全基因组测序（WGS）数据，呈现了首个横跨30种癌症类型、近9,000例癌症的单倍型特异性体细胞拷贝数改变（SCNA）泛癌图谱。该分析主要通过CancerVision完成，这是由Inocras开发的一套用于在癌症样本中检测体细胞和胚系变异的专有生物信息学工作流程。单倍型特异性拷贝数分析提供了以往分析无法获得的三方面信息。第一，单倍型特异性SCNA能够更准确地评估非整倍体，即发生拷贝数改变的癌症基因组比例。第二，单倍型分辨率可直接解析胚系变异基因型与SCNA之间的相互作用。最后，单倍型特异性SCNA可直接揭示染色体不稳定性的诱发机制。在本研究中，我们提供了展示上述每种情形的实例。值得注意的是，我们观察到一系列多样化的单倍型特异性SCNA模式，每种模式反映出一种独特的染色体不稳定性机制，包括与全基因组加倍（WGD）相关的臂级改变、提示断裂-融合-桥（BFB）的节段性变化、显示连续BFB循环和染色体碎裂（chromothripsis）特征的复杂重排，以及与染色体外DNA（ecDNA）形成相符的局灶性扩增。我们对TCGA中单倍型特异性SCNA的分析提示了一种基于机制的、与染色体不稳定性相关的拷贝数模式分类。将这一框架拓展至经治疗暴露的样本，可能为合成致死依赖性提供新的见解，并对癌症精准医学具有潜在的诊断和治疗意义。

查看英文原文 English abstract

Whole-chromosome and segmental copy-number changes are nearly ubiquitous in human cancers. Here, we present the first pan-cancer landscape of haplotype-specific somatic copy number alterations (SCNAs) in nearly 9,000 cancers across 30 cancer types from The Cancer Genome Atlas (TCGA) whole-genome sequencing (WGS) data. This analysis was primarily carried out with CancerVision, a proprietary bioinformatic workflow for detecting both somatic and germline variants in cancer samples developed by Inocras. The haplotype-specific copy-number analysis provides three pieces of information not available from previous analysis. First, the haplotype-specific SCNAs enables a more accurate assessment of aneuploidy, i.e., the fraction of the cancer genome with copy number alterations. Second, the haplotype resolution directly resolves interactions between germline variant genotypes and SCNAs. Finally, haplotype-specific SCNAs directly inform the instigating mechanisms of chromosomal instability. In this study, we provide examples demonstrating each scenario. Notably, we observed a diverse range of haplotype-specific SCNA patterns, each reflecting a distinct mechanism of chromosomal instability, including arm-level alterations related to WGD, segmental changes indicative of breakage-fusion-bridge (BFB), complex rearrangements displaying signatures of successive BFB cycles and chromothripsis, as well as focal amplifications consistent with extrachromosomal DNA (ecDNA) formation. Our analysis of haplotype-specific SCNAs in TCGA suggests a mechanism-based classification of copy-number patterns linked to chromosomal instability. Extending this framework to treatment-exposed samples could provide new insights into synthetic lethality dependencies, with potential diagnostic and therapeutic implications for cancer precision medicine.

利益披露 Disclosure

C. Bao, None.. M. Leventhal, None.. H. Park, None.. G. Lee, None.. R. Kim, None.. W. Lee, None.. J. Lee, None.. Y. Lee, None.. B. Lee, None.. D. Lehotzky, None.. R. Solan, None.. A. Kowalewski, None.. X. Loinaz, None.. V. Narasimha Swamy, None.. D. I. Heiman, None.. S. Van Seters, None.. S. Belkin, None.. S. Wiseman, None.. A. D. Cherniack, None.. L. Corchete Sanchez, None.. B. P. Danysh, None.. Z. Everton, None.. C. Stewart, None.. H. Tomono, None.. G. Wang, None.. E. Rheinbay, None.. G. Getz, None.. C. Zhang, None.. Y. Ju, None.

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