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Four evolutionary trajectories underlie genetic intratumoral variation in childhood cancer

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Abstract

A major challenge to personalized oncology is that driver mutations vary among cancer cells inhabiting the same tumor. Whether this reflects principally disparate patterns of Darwinian evolution in different tumor regions has remained unexplored1,2,3,4,5. We mapped the prevalence of genetically distinct clones over 250 regions in 54 childhood cancers. This showed that primary tumors can simultaneously follow up to four evolutionary trajectories over different anatomic areas. The most common pattern consists of subclones with very few mutations confined to a single tumor region. The second most common is a stable coexistence, over vast areas, of clones characterized by changes in chromosome numbers. This is contrasted by a third, less frequent, pattern where a clone with driver mutations or structural chromosome rearrangements emerges through a clonal sweep to dominate an anatomical region. The fourth and rarest pattern is the local emergence of a myriad of clones with TP53 inactivation. Death from disease was limited to tumors exhibiting the two last, most dynamic patterns.

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Fig. 1: Dissection of clonal landscapes over anatomic space.
Fig. 2: Examples of evolutionary trajectories.
Fig. 3: TP53 inactivation causes regional evolutionary explosion and anaplasia.
Fig. 4: Mutational spectra of evolutionary patterns.
Fig. 5: Branching evolution and clinical impact.

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Acknowledgements

This study was supported by grants to D.G. from the Swedish Research Foundation (2016-01022), the Swedish Cancer Society (CAN2015/284), the Swedish Childhood Cancer Foundation (PR2016-024, NCP2015-0035), the Crafoord Foundation, the Royal Physiographic Society and the Medical Faculty of Lund University Sweden. We also acknowledge technical support from the Science for Life Laboratory, the Knut and Alice Wallenberg Foundation, the National Genomics Infrastructure founded by the Swedish Research Council and Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We also thank the Swegene Centre for Integrative Biology at Lund University for assistance.

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Contributions

J.K., A.V. and D.G. conceived and designed the project. J.K., A.V., L.H.M., J.S., B.V., T.J. and A.I. coordinated and analyzed whole-genome genotyping and sequencing data, while A.V. performed phylogenetic analysis. S.B., I.Ø., A.B., T.B., B.S., N.P., B.G.L., N.B., D.B. and D.G. performed clinical correlation studies and contributed tumor material. L.C. prepared knockout cell lines. C.J. and A.W. performed technical work.

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Correspondence to David Gisselsson.

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Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–19 and Supplementary Tables 1 and 2

Reporting Summary

Supplementary Data 1

Overview of patients and analytical platforms

Supplementary Data 2

Segmented allelic imbalances

Supplementary Data 3

Mutations detected by whole-exome sequencing

Supplementary Data 4

Variants identified with deep resequencing

Supplementary Data 5

Analysis performed on each sample

Supplementary Data 6

Genome profiles from whole-genome genotyping

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Karlsson, J., Valind, A., Holmquist Mengelbier, L. et al. Four evolutionary trajectories underlie genetic intratumoral variation in childhood cancer. Nat Genet 50, 944–950 (2018). https://doi.org/10.1038/s41588-018-0131-y

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