PO.TB09.02 · 肿瘤生物学
跨越80,000个癌症细胞基因组的致癌基因扩增动态演化
Dynamic evolution of oncogene amplification across 80,000 cancer cell genomes
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
拷贝数（CN）扩增是致癌基因激活的主要机制，也是一个治疗靶点，但其在人类癌症中的演化尚未被完全理解。我们分析了来自主要癌症类型（卵巢、乳腺、肺和脑）100例肿瘤中>80,000个癌细胞的单细胞全基因组测序（scWGS）数据以及实验模型，以解析致癌基因扩增的机制和演化。跨细胞的CN分布揭示了两种模式：源自对称分离的窄而均匀的峰，与染色体内扩增（ICamp）一致；以及具有极端离群值（>100拷贝/细胞）的宽而重尾的变异，提示染色体外环状DNA（ecDNA）。这些分布的概率混合模型将503个扩增区域中的74个（15%）分类为ecDNA。这些ecDNA最常涉及MYC、EGFR和MDM2，并在胶质母细胞瘤和肺癌中富集，而卵巢癌和三阴性乳腺癌则主要表现为ICamp。值得注意的是，ICamp事件表现出显著的亚克隆特异性，429个事件中有227个（53%）在CN分布中显示多种模式。这些模式与系统发育分析的其他基因组特征一致，提示对称分裂和克隆扩增的谱系遗传模式。多样化通过数量机制（非整倍体或基因组倍增）和亚克隆特异性结构变异（如断裂-融合-桥循环或染色体碎裂）产生。CN调节是双向的，包括通过亚克隆特异性非整倍体丢失扩增的衍生染色体。在单细胞分辨率下对拷贝数和结构变异的联合分析揭示了几种ecDNA驱动的癌症演化机制。首先，经常观察到通过内部重排和不同物种之间的重组对ecDNA进行重塑，导致致癌基因共选择。其次，在一例胶质母细胞瘤中观察到通过获得不同的含EGFR的ecDNA而发生的趋同演化，提示ecDNA丢失在塑造后续演化中的潜在作用。第三，同基因细胞系的scWGS区分了现存ecDNA与经历基因组重排导致染色体重新整合的历史ecDNA。最后，我们表明，基于环状基因组图预测与基于CN分布预测的ecDNA之间的比较揭示了显著差异，并具有明显的组织类型特异性。总之，本研究揭示了与不同ICamp和ecDNA生成过程一致的、可解释的致癌基因扩增分布。这种超越标准基因组图来完善ecDNA识别的方法，进一步阐明了不同的致癌基因扩增机制如何使癌细胞群体多样化。我们认为，这些新见解将为新兴的ecDNA靶向疗法的患者选择提供指导。
查看英文原文 English abstract
Copy-number (CN) amplification is a major mechanism of oncogene activation and a therapeutic target, yet its evolution in human cancers is incompletely understood. We analyzed single-cell whole-genome sequencing (scWGS) data from >80,000 cancer cells in 100 tumors from major cancer types (ovary, breast, lung, and brain) and experimental models to resolve mechanisms and evolution of oncogene amplification. CN distributions across cells revealed two patterns: narrow, uniform peaks from symmetric segregation, consistent with intrachromosomal amplifications (ICamps), and broad, heavy-tailed variation with extreme outliers (>100 copies/cell) indicative of extrachromosomal circular DNA (ecDNA). A probabilistic mixture model of these distributions classified 74 (15%) of 503 amplified regions as ecDNA. These ecDNAs most frequently involved MYC , EGFR , and MDM2 , and were enriched in glioblastoma and lung cancers, whereas ovarian and triple-negative breast cancers predominantly showed ICamps. Notably, ICamp events showed significant subclonal specificity, with 227 (53%) of 429 events displaying multiple modes in the CN distribution. These modes were congruent with other genomic features from phylogenetic analysis, suggesting lineage inheritance patterns of symmetric division and clonal expansion. Diversification arose via numeric mechanisms (aneuploidy or genome doubling) and subclone-specific structural variants (e.g., breakage-fusion-bridge cycles or chromothripsis). CN modulation was bidirectional, including loss of amplified derivative chromosome via subclone-specific aneuploidy. Joint analysis of copy-number and structural variants at single-cell resolution uncovered several mechanisms of ecDNA-driven cancer evolution. First, remodeling of ecDNAs through internal rearrangements and recombination between distinct species was often observed, leading to oncogene co-selection. Second, convergent evolution via acquisition of distinct EGFR -containing ecDNAs was observed in a glioblastoma, suggesting the potential role of ecDNA loss in shaping subsequent evolution. Third, scWGS of isogenic cell lines distinguished present ecDNAs from historical ecDNAs that underwent genomic rearrangements resulting in chromosomal re-integration. Finally, we show that comparison between circular genome graph-based prediction versus the CN distribution-based prediction of ecDNAs revealed substantial discrepancy with notable tissue-type specificity. In conclusion, this study reveals interpretable distributions of oncogene amplifications consistent with distinct ICamp and ecDNA generative processes. This approach, refining ecDNA identification beyond standard genome graphs, further elucidates how distinct mechanisms of oncogene amplification diversify cancer cell populations. We suggest these new insights will inform patient selection for emerging ecDNA-directed therapies.
利益披露 Disclosure
J. J. Lee, None..
J. Lee, None.