ArticleNature biotechnology2016
Analyzing tumor heterogeneity and driver genes in single myeloid leukemia cells with SBCapSeq.
Article in Nature biotechnology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed.
- Exploring transposable elements: new horizons in cancer diagnostics and therapeutics.Mobile DNA · 2025Review
- DNA Barcoding Technology for Lineage Recording and Tracing to Resolve Cell Fate Determination.Cells · 2023Review
- Mutations in the histone methyltransferase Ezh2 drive context-dependent leukemia in Xenopus tropicalis.Leukemia · 2023Article
- Transposon mutagenesis identifies cooperating genetic drivers during keratinocyte transformation and cutaneous squamous cell carcinoma progression.PLoS genetics · 2021Article
- Retrospective cell lineage reconstruction in humans by using short tandem repeats.Cell reports methods · 2021Article
- Promoterless Transposon Mutagenesis Drives Solid Cancers via Tumor Suppressor Inactivation.Cancers · 2021Article
- Forward and Reverse Genetics of B Cell Malignancies: From Insertional Mutagenesis to CRISPR-Cas.Frontiers in immunology · 2021Review
- In vivo functional screening for systems-level integrative cancer genomics.Nature reviews. Cancer · 2020Review
- CRISPR and transposon in vivo screens for cancer drivers and therapeutic targets.Genome biology · 2020Review
- Intratumor Heterogeneity: The Rosetta Stone of Therapy Resistance.Cancer cell · 2020Review
- Transposon Insertion Mutagenesis in Mice for Modeling Human Cancers: Critical Insights Gained and New Opportunities.International journal of molecular sciences · 2020Review
- Detecting heterogeneity in and between breast cancer cell lines.Cancer convergence · 2020Article
- PiggyBac transposon tools for recessive screening identify B-cell lymphoma drivers in mice.Nature communications · 2019Article
- Understanding tumor ecosystems by single-cell sequencing: promises and limitations.Genome biology · 2018Review
- Molecular profiling of nonalcoholic fatty liver disease-associated hepatocellular carcinoma using SB transposon mutagenesis.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- SB Driver Analysis: a Sleeping Beauty cancer driver analysis framework for identifying and prioritizing experimentally actionable oncogenes and tumor suppressors.Nucleic acids research · 2018Article
- Advances in functional genetic screening with transposons and CRISPR/Cas9 to illuminate cancer biology.Current opinion in genetics & development · 2018Review
- High-dimension single-cell analysis applied to cancer.Molecular aspects of medicine · 2018Review
- SBCDDB: Sleeping Beauty Cancer Driver Database for gene discovery in mouse models of human cancers.Nucleic acids research · 2018Article
- Crotonoside exhibits selective post-inhibition effect in AML cells via inhibition of FLT3 and HDAC3/6.Oncotarget · 2017Article
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Authors and funding
21 authors.
Funding
Abstract
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.
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