Analyzing tumor heterogeneity and driver genes in single myeloid leukemia cells with SBCapSeq
Karen M Mann1,2, Justin Y Newberg1, Michael A Black3
1Cancer Research Program, Houston Methodist Research Institute, Houston, Texas, USA.
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.
Insights
This study introduces a new single-cell sequencing method, Sleeping Beauty (SB) capture hybridization sequencing (SBCapSeq), to analyze tumor cell mutations. SBCapSeq effectively identifies cancer drivers and cooperating genes in heterogeneous tumors, advancing oncology research.
Area of Science:
- Oncology
- Genetics
- Bioinformatics
Background:
- Tumor heterogeneity poses a significant challenge in cancer treatment.
- Current single-cell analysis methods for identifying cancer-driving mutations are limited by bias, low sequencing depth, or high cost.
- Transposon-based mutagenesis is valuable for discovering early cancer drivers, but requires advanced single-cell sequencing capabilities.
Purpose of the Study:
- To develop and validate a novel single-cell sequencing pipeline for analyzing transposon insertion sites in heterogeneous tumors.
- To overcome the limitations of existing methods in identifying cooperating cancer genes at the single-cell level.
- To apply the new method to a mouse model of myeloid leukemia to reveal tumor clonal architecture.
Main Methods:
- Development of a liquid-phase, capture-based sequencing and bioinformatics pipeline named Sleeping Beauty (SB) capture hybridization sequencing (SBCapSeq).
- Application of SBCapSeq to analyze transposon insertion sites in single tumor cells from a SB mouse model of myeloid leukemia (ML).
- Bioinformatic analysis to identify clonal subpopulations, insertion events, and cooperating cancer genes.
Main Results:
- SBCapSeq successfully sequenced transposon insertion sites from single tumor cells.
- Analysis of just 26 cells revealed major clonal subpopulations within the tumor.
- The method detected clonal insertion events missed by other techniques and identified dominant subclones with unique interacting gene drivers and cooperating cancer genes.
Conclusions:
- SBCapSeq is a powerful new tool for single-cell analysis of transposon-induced mutations in cancer research.
- This method enables a deeper understanding of tumor heterogeneity and the cooperative roles of cancer genes.
- The findings advance the identification of therapeutic targets in heterogeneous tumors.
