Hughes Andrew E O, Magrini Vincent, Demeter Ryan, Miller Christopher A, Fulton Robert, Fulton Lucinda L, Eades William C, Elliott Kevin, Heath Sharon, Westervelt Peter, Ding Li, Conrad Donald F, White Brian S, Shao Jin, Link Daniel C, DiPersio John F, Mardis Elaine R, Wilson Richard K, Ley Timothy J, Walter Matthew J, Graubert Timothy A
Center for Genome Sciences and Systems Biology, Washington University, St. Louis, Missouri, United States of America.
The Genome Institute, Washington University, St. Louis, Missouri, United States of America; Department of Genetics, Washington University, St. Louis, Missouri, United States of America.
PLoS Genet. 2014 Jul 10;10(7):e1004462. doi: 10.1371/journal.pgen.1004462. eCollection 2014 Jul.
Next-generation sequencing has been used to infer the clonality of heterogeneous tumor samples. These analyses yield specific predictions-the population frequency of individual clones, their genetic composition, and their evolutionary relationships-which we set out to test by sequencing individual cells from three subjects diagnosed with secondary acute myeloid leukemia, each of whom had been previously characterized by whole genome sequencing of unfractionated tumor samples. Single-cell mutation profiling strongly supported the clonal architecture implied by the analysis of bulk material. In addition, it resolved the clonal assignment of single nucleotide variants that had been initially ambiguous and identified areas of previously unappreciated complexity. Accordingly, we find that many of the key assumptions underlying the analysis of tumor clonality by deep sequencing of unfractionated material are valid. Furthermore, we illustrate a single-cell sequencing strategy for interrogating the clonal relationships among known variants that is cost-effective, scalable, and adaptable to the analysis of both hematopoietic and solid tumors, or any heterogeneous population of cells.
新一代测序已被用于推断异质性肿瘤样本的克隆性。这些分析产生了特定的预测结果——单个克隆的群体频率、它们的基因组成以及它们的进化关系——我们通过对三名被诊断为继发性急性髓系白血病患者的单个细胞进行测序来验证这些预测,这三名患者之前均已通过对未分离的肿瘤样本进行全基因组测序进行了特征分析。单细胞突变谱分析有力地支持了对大量样本分析所暗示的克隆结构。此外,它解决了最初不明确的单核苷酸变异的克隆归属问题,并识别出了以前未被认识到的复杂区域。因此,我们发现,通过对未分离材料进行深度测序来分析肿瘤克隆性的许多关键假设是有效的。此外,我们阐述了一种用于探究已知变异之间克隆关系的单细胞测序策略,该策略具有成本效益、可扩展性,并且适用于造血肿瘤和实体肿瘤或任何异质性细胞群体的分析。