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Quantifying local malignant adaptation in tissue-specific evolutionary trajectories by harnessing cancer’s repeatability at the genetic level

N Tokutomi, View ORCID ProfileC Moyret-Lalle, View ORCID ProfileA Puisieux, View ORCID ProfileS Sugano, View ORCID ProfileP Martinez
doi: https://doi.org/10.1101/401059
N Tokutomi
1Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan.
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C Moyret-Lalle
2Univ Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon Bérard, Cancer Research Center of Lyon, Lyon, 69008, France, INSERM U1052, Cancer Research Center of Lyon, Lyon, F-69008, France.
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A Puisieux
2Univ Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon Bérard, Cancer Research Center of Lyon, Lyon, 69008, France, INSERM U1052, Cancer Research Center of Lyon, Lyon, F-69008, France.
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S Sugano
1Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan.
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P Martinez
2Univ Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon Bérard, Cancer Research Center of Lyon, Lyon, 69008, France, INSERM U1052, Cancer Research Center of Lyon, Lyon, F-69008, France.
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Abstract

Cancer is a potentially lethal disease, in which patients with nearly identical genetic backgrounds can develop a similar pathology through distinct combinations of genetic alterations. We aimed to reconstruct the evolutionary process underlying tumour initiation, using the combination of convergence and discrepancies observed across 2,742 cancer genomes from 9 tumour types. We developed a framework using the repeatability of cancer development to score the local malignant adaptation (LMA) of genetic clones, as their potential to malignantly progress and invade their environment of origin. Using this framework, we found that pre-malignant skin and colorectal lesions appeared specifically adapted to their local environment, yet insufficiently for full cancerous transformation. We found that metastatic clones were more adapted to the site of origin than to the invaded tissue, suggesting that genetics may be more important for local progression than for the invasion of distant organs. In addition, we used network analyses to investigate evolutionary properties at the system-level, highlighting that different dynamics of malignant progression can be modelled by such a framework in tumour-type-specific fashion. We find that occurrence-based methods can be used to specifically recapitulate the process of cancer initiation and progression, as well as to evaluate the adaptation of genetic clones to given environments. The repeatability observed in the evolution of most tumour types could therefore be harnessed to better predict the trajectories likely to be taken by tumours and pre-neoplastic lesions in the future.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted September 04, 2018.
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Quantifying local malignant adaptation in tissue-specific evolutionary trajectories by harnessing cancer’s repeatability at the genetic level
N Tokutomi, C Moyret-Lalle, A Puisieux, S Sugano, P Martinez
bioRxiv 401059; doi: https://doi.org/10.1101/401059
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Quantifying local malignant adaptation in tissue-specific evolutionary trajectories by harnessing cancer’s repeatability at the genetic level
N Tokutomi, C Moyret-Lalle, A Puisieux, S Sugano, P Martinez
bioRxiv 401059; doi: https://doi.org/10.1101/401059

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