A marker-independent lineage-tracing system to quantify clonal dynamics and stem cell functionality in cancer tissue

Abstract

Lineage tracing is a powerful tool that can be used to uncover cell fates. Here, we describe a novel method for the quantitative analysis of clonal dynamics in grafted cancer tissues. The protocol involves the preparation and validation of cells for lineage tracing, establishment of grafts and label induction, analysis of clone-size distribution and fitting of the experimental data to a mathematical tumor growth model. In contrast to other lineage-tracing strategies, the method described here assesses stem cell functionality and infers tumor expansion dynamics independently of molecular markers such as putative cancer stem cell (CSC)-specific genes. The experimental system and analytical framework presented can be used to quantify clonal advantages that specific mutations provide, in both the absence and presence of (targeted) therapeutic agents. This protocol typically takes ~20 weeks to complete from cell line selection to inference of growth dynamics, depending on the grafted cancer growth rate.

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Fig. 1: Schematic overview of the protocol.
Fig. 2: Lentiviral transduction of cell culture with pLV-indLS2 construct.
Fig. 3: Generation and selection of pLV-indLS2+ single-cell clones.
Fig. 4: Validation of stability and neutrality of single-cell clone.
Fig. 5: Determination of the optimal in vivo tamoxifen concentration.
Fig. 6: Tumor isolation and sectioning.
Fig. 7: Unbiased in vivo lineage tracing of HT55 cells.
Fig. 8: App for clone-size data inference.
Fig. 9: CloneFit app for clone-size data inference, instructions.
Fig. 10: Data interpretation: model parameters.
Fig. 11: Stochastic tumor growth model.

Data availability

Source data for Figs. 7, 8, 9 and 10 have been provided as Supplementary Data. All other data supporting the findings of this study are available from the corresponding authors on reasonable request.

Code availability

The custom clone-size quantification software can be downloaded from https://github.com/dmmiedema/Clone-Sizes-From-Image. The CloneFit app can be downloaded from https://github.com/dmmiedema/CloneFit. We have made available the programming code for the tumor growth model on GitHub: https://github.com/dmmiedema/Tumor-Growth-Model.

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Acknowledgements

We thank L.E. Nijman and M.C. Lecca for their help with the animal procedures. This work was supported by the Academic Medical Center (Amsterdam), The New York Stem Cell Foundation, Cancer Research UK, and grants from KWF (UVA2011-4969, UVA2014-7245 and 10529), the Maurits en Anna de Kock Stichting (2015-2), Worldwide Cancer Research (14-1164), the Maag Lever Darm Stichting (MLDS-CDG 14-03), the European Research Council (ERC-StG 638193) and ZonMw (Vidi 016.156.308) to L.V. L.V. is a New York Stem Cell Foundation—Robertson Investigator.

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K.J.L. and S.C.L. performed the experiments; D.M.M. and L.V. developed the quantitative models; D.M.M. developed the software; K.J.L., D.M.M., S.C.L., M.F.B. and L.V. analyzed the data; S.K.L. contributed reagents; K.J.L., D.M.M., M.F.B. and L.V. conceived and designed the research; K.J.L., S.C.L., D.M.M., M.F.B. and L.V. wrote the manuscript; L.V. directed the research. All authors approved the content of the manuscript.

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Correspondence to Daniël M. Miedema or Louis Vermeulen.

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Lenos, K. J. et al. Nat. Cell Biol. 20, 1193–1202 (2018): https://doi.org/10.1038/s41556-018-0179-z

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Lenos, K.J., Lodestijn, S.C., Lyons, S.K. et al. A marker-independent lineage-tracing system to quantify clonal dynamics and stem cell functionality in cancer tissue. Nat Protoc 14, 2648–2671 (2019). https://doi.org/10.1038/s41596-019-0194-y

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