Analyzing tumor heterogeneity and driver genes in single myeloid leukemia cells with SBCapSeq

• Published in: Nature biotechnology Vol. 34; no. 9; pp. 962 - 972
• Main Authors: Mann, Karen M, Newberg, Justin Y, Black, Michael A, Jones, Devin J, Amaya-Manzanares, Felipe, Guzman-Rojas, Liliana, Kodama, Takahiro, Ward, Jerrold M, Rust, Alistair G, van der Weyden, Louise, Yew, Christopher Chin Kuan, Waters, Jill L, Leung, Marco L, Rogers, Keith, Rogers, Susan M, McNoe, Leslie A, Selvanesan, Luxmanan, Navin, Nicholas, Jenkins, Nancy A, Copeland, Neal G, Mann, Michael B
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.09.2016; Nature Publishing Group
• Subjects: 38/91; 45/23; 45/47; 631/1647/334/1874/345; 631/1647/514/2254; 631/208/212/2305; 631/67/1990/283/1897; 631/67/69; 64/110; 64/60; Agriculture; Algorithms; Animals; Bioinformatics; Biomarkers, Tumor - genetics; Biomedical Engineering/Biotechnology; Biomedicine; Biotechnology; Cancer cells; Cells; DNA sequencing; DNA Transposable Elements; DNA, Neoplasm - genetics; Female; Gene expression; Genes, Neoplasm - genetics; Genetic aspects; Health aspects; Heterogeneity; High-Throughput Nucleotide Sequencing - methods; In Situ Hybridization - methods; Leukemia; Leukemia, Myeloid - genetics; Leukemia, Myeloid - pathology; Life Sciences; Male; Methods; Mice; Mutagenesis, Insertional - genetics; Myeloid leukemia; Neoplasm Proteins - genetics; Oncology; Sequence Analysis, DNA - methods; Software; Subpopulations; Transposases - genetics; Tumors
• ISSN: 1087-0156; 1546-1696
• DOI: 10.1038/nbt.3637

Oncogenic driver mutations are identified in single cells by a transposon-based sequencing method. A central challenge in oncology is how to kill tumors containing heterogeneous cell populations defined by different combinations of mutated genes. Identifying these mutated genes and understanding how they cooperate requires single-cell analysis, but current single-cell analytic methods, such as PCR-based strategies or whole-exome sequencing, are biased, lack sequencing depth or are cost prohibitive. Transposon-based mutagenesis allows the identification of early cancer drivers, but current sequencing methods have limitations that prevent single-cell analysis. We report a liquid-phase, capture-based sequencing and bioinformatics pipeline, Sleeping Beauty (SB) capture hybridization sequencing (SBCapSeq), that facilitates sequencing of transposon insertion sites from single tumor cells in a SB mouse model of myeloid leukemia (ML). SBCapSeq analysis of just 26 cells from one tumor revealed the tumor's major clonal subpopulations, enabled detection of clonal insertion events not detected by other sequencing methods and led to the identification of dominant subclones, each containing a unique pair of interacting gene drivers along with three to six cooperating cancer genes with SB-driven expression changes.