BGI-Shenzhen, Shenzhen, China.
Cell. 2012 Mar 2;148(5):873-85. doi: 10.1016/j.cell.2012.02.028.
Tumor heterogeneity presents a challenge for inferring clonal evolution and driver gene identification. Here, we describe a method for analyzing the cancer genome at a single-cell nucleotide level. To perform our analyses, we first devised and validated a high-throughput whole-genome single-cell sequencing method using two lymphoblastoid cell line single cells. We then carried out whole-exome single-cell sequencing of 90 cells from a JAK2-negative myeloproliferative neoplasm patient. The sequencing data from 58 cells passed our quality control criteria, and these data indicated that this neoplasm represented a monoclonal evolution. We further identified essential thrombocythemia (ET)-related candidate mutations such as SESN2 and NTRK1, which may be involved in neoplasm progression. This pilot study allowed the initial characterization of the disease-related genetic architecture at the single-cell nucleotide level. Further, we established a single-cell sequencing method that opens the way for detailed analyses of a variety of tumor types, including those with high genetic complex between patients.
肿瘤异质性给推断克隆进化和鉴定驱动基因带来了挑战。在这里,我们描述了一种在单细胞核苷酸水平上分析癌症基因组的方法。为了进行我们的分析,我们首先设计并验证了一种使用两个淋巴母细胞系单细胞的高通量全基因组单细胞测序方法。然后,我们对一名 JAK2 阴性骨髓增殖性肿瘤患者的 90 个细胞进行了全外显子组单细胞测序。通过我们的质量控制标准的测序数据来自 58 个细胞,这些数据表明这种肿瘤代表了单克隆进化。我们进一步鉴定了与特发性血小板增多症(ET)相关的候选突变,如 SESN2 和 NTRK1,它们可能参与肿瘤进展。这项初步研究允许在单细胞核苷酸水平上对疾病相关的遗传结构进行初步描述。此外,我们建立了一种单细胞测序方法,为详细分析各种肿瘤类型开辟了道路,包括那些在患者之间具有高度遗传复杂性的肿瘤类型。