Leighton Jake, Hu Min, Sei Emi, Meric-Bernstam Funda, Navin Nicholas E
Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA.
Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA.
Cell Genom. 2022 Nov 9;3(1):100215. doi: 10.1016/j.xgen.2022.100215. eCollection 2023 Jan 11.
Single-cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells; however, most genomic regions sequenced in single cells are non-informative. To overcome this issue, we developed a multi-patient-targeted (MPT) scDNA-seq method. MPT involves first performing bulk exome sequencing across a cohort of cancer patients to identify somatic mutations, which are then pooled together to develop a single custom targeted panel for high-throughput scDNA-seq using a microfluidics platform. We applied MPT to profile 330 mutations across 23,500 cells from 5 patients with triple negative-breast cancer (TNBC), which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From these data, we reconstructed mutational lineages and identified early mutational and copy-number events, including early mutations that occurred in all five patients. Collectively, our data suggest that MPT can overcome a major technical obstacle for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites.
单细胞DNA测序(scDNA-seq)方法是分析癌细胞突变的强大工具;然而,单细胞中测序的大多数基因组区域并无信息价值。为克服这一问题,我们开发了一种多患者靶向(MPT)scDNA-seq方法。MPT首先对一组癌症患者进行外显子组测序以识别体细胞突变,然后将这些突变汇集在一起,使用微流控平台开发一个单一的定制靶向面板用于高通量scDNA-seq。我们应用MPT对5例三阴性乳腺癌(TNBC)患者的23500个细胞中的330个突变进行分析,结果显示3个肿瘤为单克隆性,2个肿瘤为多克隆性。从这些数据中,我们重建了突变谱系并识别了早期突变和拷贝数事件,包括所有5例患者中发生的早期突变。总体而言,我们的数据表明,MPT可以通过分析信息丰富的突变位点来克服使用scDNA-seq研究肿瘤进化的一个主要技术障碍。