Ewing Ailith, Meynert Alison, Silk Ryan, Aitken Stuart, Bendixsen Devin P, Churchman Michael, Brown Stuart L, Hamdan Alhafidz, Mattocks Joanne, Grimes Graeme R, Ballinger Tracy, Hollis Robert L, Simon Herrington C, Thomson John P, Sherwood Kitty, Parry Thomas, Esiri-Bloom Edward, Bartos Clare, Croy Ian, Ferguson Michelle, Lennie Mairi, McGoldrick Trevor, McPhail Neil, Siddiqui Nadeem, Glasspool Rosalind, Mackean Melanie, Nussey Fiona, McDade Brian, Ennis Darren, McMahon Lynn, Matakidou Athena, Dougherty Brian, March Ruth, Carl Barrett J, McNeish Iain A, Biankin Andrew V, Roxburgh Patricia, Gourley Charlie, Semple Colin A
MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Cancer Research UK Scotland Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Nat Commun. 2025 Jul 1;16(1):5586. doi: 10.1038/s41467-025-60655-y.
Deciphering the structural variation across tumour genomes is crucial to determine the events driving tumour progression and better understand tumour adaptation and evolution. High grade serous ovarian cancer (HGSOC) is an exemplar tumour type showing extreme, but poorly characterised structural diversity. Here, we comprehensively describe the mutational landscape driving HGSOC, exploiting a large (N = 324), deeply whole genome sequenced dataset. We reveal two divergent evolutionary trajectories, affecting patient survival and involving differing genomic environments. One involves homologous recombination repair deficiency (HRD) while the other is dominated by whole genome duplication (WGD) with frequent chromothripsis, breakage-fusion-bridges and extra-chromosomal DNA. These trajectories contribute to structural variation hotspots, containing candidate driver genes with significantly altered expression. While structural variation predominantly drives tumorigenesis, we find high mtDNA mutation loads associated with shorter patient survival. We show that a combination of mutations in the mitochondrial and nuclear genomes impact prognosis, suggesting strategies for patient stratification.
解析肿瘤基因组中的结构变异对于确定驱动肿瘤进展的事件以及更好地理解肿瘤适应和进化至关重要。高级别浆液性卵巢癌（HGSOC）是一种典型的肿瘤类型，表现出极端但特征不明的结构多样性。在这里，我们利用一个大型（N = 324）、深度全基因组测序数据集，全面描述了驱动HGSOC的突变图谱。我们揭示了两条不同的进化轨迹，影响患者生存并涉及不同的基因组环境。一条涉及同源重组修复缺陷（HRD），而另一条则以全基因组复制（WGD）为主，伴有频繁的染色体碎裂、断裂-融合-桥接和染色体外DNA。这些轨迹导致了结构变异热点，其中包含表达显著改变的候选驱动基因。虽然结构变异主要驱动肿瘤发生，但我们发现高线粒体DNA突变负荷与患者较短的生存时间相关。我们表明，线粒体和核基因组中的突变组合影响预后，为患者分层提供了策略。
