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利用多重骨髓瘤中的连锁读长进行体细胞突变定相和单倍型扩展。

Somatic mutation phasing and haplotype extension using linked-reads in multiple myeloma.

作者信息

Foltz Steven M, Li Yize, Yao Lijun, Terekhanova Nadezhda V, Weerasinghe Amila, Gao Qingsong, Dong Guanlan, Schindler Moses, Cao Song, Sun Hua, Jayasinghe Reyka G, Fulton Robert S, Fronick Catrina C, King Justin, Kohnen Daniel R, Fiala Mark A, Chen Ken, DiPersio John F, Vij Ravi, Ding Li

机构信息

Department of Medicine, Washington University in St. Louis, St. Louis, MO, 63110, USA.

McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO, 63108, USA.

出版信息

bioRxiv. 2024 Aug 10:2024.08.09.607342. doi: 10.1101/2024.08.09.607342.

Abstract

Somatic mutation phasing informs our understanding of cancer-related events, like driver mutations. We generated linked-read whole genome sequencing data for 23 samples across disease stages from 14 multiple myeloma (MM) patients and systematically assigned somatic mutations to haplotypes using linked-reads. Here, we report the reconstructed cancer haplotypes and phase blocks from several MM samples and show how phase block length can be extended by integrating samples from the same individual. We also uncover phasing information in genes frequently mutated in MM, including , , , , and , phasing 79.4% of 20,705 high-confidence somatic mutations. In some cases, this enabled us to interpret clonal evolution models at higher resolution using pairs of phased somatic mutations. For example, our analysis of one patient suggested that two hotspot mutations occurred on the same haplotype but were independent events in different subclones. Given sufficient tumor purity and data quality, our framework illustrates how haplotype-aware analysis of somatic mutations in cancer can be beneficial for some cancer cases.

摘要

体细胞突变定相有助于我们理解癌症相关事件,如驱动突变。我们为14例多发性骨髓瘤(MM)患者不同疾病阶段的23个样本生成了连锁读长全基因组测序数据,并使用连锁读长将体细胞突变系统地分配到单倍型。在此,我们报告了几个MM样本中重建的癌症单倍型和定相块,并展示了如何通过整合来自同一个体的样本来延长定相块长度。我们还揭示了MM中频繁突变基因的定相信息,包括 、 、 、 和 ,对20,705个高置信度体细胞突变中的79.4%进行了定相。在某些情况下,这使我们能够使用成对的定相体细胞突变以更高分辨率解释克隆进化模型。例如,我们对一名患者的分析表明,两个热点突变发生在同一单倍型上,但在不同亚克隆中是独立事件。鉴于足够的肿瘤纯度和数据质量,我们的框架说明了癌症中体细胞突变的单倍型感知分析如何对某些癌症病例有益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5681/11326269/24046572aa3e/nihpp-2024.08.09.607342v1-f0001.jpg

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