Gerstner Sloan Kettering Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Nat Commun. 2023 Feb 10;14(1):749. doi: 10.1038/s41467-023-36344-z.
Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high-throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimize a highly automated nuclei extraction workflow that achieves fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals genomic evolution patterns of pancreatic ductal adenocarcinoma as well.
尽管通过对癌症进行大量 DNA 测序获得了一些见解,但要解决正常细胞和肿瘤细胞的混合问题,以及/或不同肿瘤亚克隆的混合问题仍然具有挑战性;高通量单细胞 DNA 测序解决了这些问题,并使癌症基因组研究达到更高的分辨率。然而,由于缺乏可扩展的工作流程来处理实体肿瘤样本,其应用一直受到限制,主要是因为缺乏可扩展的工作流程来处理实体肿瘤样本。在这里,我们优化了一种高度自动化的核提取工作流程,该流程可快速可靠地靶向制备 16 名胰腺导管腺癌患者的 38 个样本的单细胞核 DNA 文库,每个样本的平均文库产量为 2867 个单细胞核。我们证明,该工作流程不仅可以很好地处理低细胞数或低肿瘤纯度的样本,而且还可以揭示胰腺导管腺癌的基因组进化模式。