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Universal cancer tasks, evolutionary tradeoffs, and the functions of driver mutations

View ORCID ProfileJean Hausser, Pablo Szekely, Noam Bar, Anat Zimmer, Hila Sheftel, Carlos Caldas, View ORCID ProfileUri Alon
doi: https://doi.org/10.1101/382291
Jean Hausser
1department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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  • For correspondence: jean.hausser@weizmann.ac.il carlos.caldas@cruk.cam.ac.uk uri.alon@weizmann.ac.il
Pablo Szekely
1department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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Noam Bar
1department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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Anat Zimmer
1department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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Hila Sheftel
1department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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Carlos Caldas
2Department of Oncology and Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK
3Breast Cancer Programme, Cancer Research UK Cambridge Cancer Centre, Cambridge, CB2 0RE
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Uri Alon
1department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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  • ORCID record for Uri Alon
  • For correspondence: jean.hausser@weizmann.ac.il carlos.caldas@cruk.cam.ac.uk uri.alon@weizmann.ac.il
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Abstract

Recent advances have led to an appreciation of the vast molecular diversity of cancer. Detailed data has enabled powerful methods to sort tumors into groups with benefits for prognosis and treatment. We are still missing, however, a general theoretical framework to understand the diversity of tumor gene-expression and mutations. To address this, we present a framework based on multi-task evolution theory, using the fact that tumors evolve in the body, and that tumors are faced with multiple tasks that contribute to their fitness. In accordance with the theory, we find that tradeoff between tasks constrains tumor gene-expression to a continuum bounded by a polyhedron. The vertices of the polyhedron are gene-expression profiles each specializing in one task, allowing the tasks to be identified. We find five universal cancer tasks across tissue-types: cell-division, biomass & energy, lipogenesis, immune-interaction and invasion & tissue remodeling. Tumors whose gene-expression lies close to a vertex are task specialists. We find evidence that such specialists are more sensitive to drugs that interfere with this task. We find that driver mutations, but not passenger mutations, tune gene-expression towards specialization in specific tasks. This approach can integrate additional types of molecular data into a theoretically-based framework for understanding tumor diversity.

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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-ND 4.0 International license.
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Posted August 01, 2018.
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Universal cancer tasks, evolutionary tradeoffs, and the functions of driver mutations
Jean Hausser, Pablo Szekely, Noam Bar, Anat Zimmer, Hila Sheftel, Carlos Caldas, Uri Alon
bioRxiv 382291; doi: https://doi.org/10.1101/382291
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Universal cancer tasks, evolutionary tradeoffs, and the functions of driver mutations
Jean Hausser, Pablo Szekely, Noam Bar, Anat Zimmer, Hila Sheftel, Carlos Caldas, Uri Alon
bioRxiv 382291; doi: https://doi.org/10.1101/382291

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