A. Aktipis, Life history trade-offs in cancer evolution, Nature Rev. Cancer, vol.13, pp.883-892, 2013.

T. Boveri, The origins of malignant tumors, 1929.

B. Brutovsky and D. Horvath, Structure of Intratumor Heterogeneity: Is Cancer Hedging Its Bets? arXiv, 2013.

K. J. Bussey, Ancestral gene regulatory networks drive cancer, vol.114, pp.6160-6162, 2017.

C. Carrère, Optimization of an in vitro chemotherapy to avoid resistant tumours, J. Theor. Biol, vol.413, pp.24-33, 2017.

R. H. Chisholm, Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation, Biochem. Biophys. Acta, vol.1860, pp.2627-2645, 2016.

H. Cho and D. Levy, The Impact of Competition Between Cancer Cells and Healthy Cells on Optimal Drug Delivery, Math. Mod. Nat. Phenom, 2019.

L. H. Cisneros, Ancient genes establish stress-induced mutation as a hallmark of cancer, PLoS One, vol.12, issue.4, p.176258, 2017.

A. S. Cleary, Tumour cell heterogeneitymaintained by cooperating subclones in Wnt-driven mammary cancers, Nature Lett, vol.508, pp.113-117, 2014.

P. C. Davies and C. H. Lineweaver, Cancer tumors as metazoa 1.0: tapping genes of ancient ancestors, Phys. Biol, vol.8, issue.1, p.15001, 2011.

T. Dobzhansky, Nothing in Biology Makes Sense Except in the Light of Evolution, American Biology Teacher, vol.35, issue.3, pp.125-129, 1973.

T. Domazet-lo?o and D. Tautz, An ancient evolutionary origin of genes associated with human genetic diseases, Mol. Biol. Evol, vol.25, issue.12, pp.2699-2707, 2008.

T. Domazet-lo?o and D. Tautz, Phylostratigraphic tracking of cancer genes suggests a link to the emergence of multicellularity in metazoa, BMC Biol, vol.8, issue.1, p.66, 2010.

R. J. Gillies, Evolutionary dynamics of carcinogenesis and why targeted therapy does not work, Nat. Rev. Cancer, vol.12, issue.7, pp.487-493, 2012.

A. Goldman, Integrating Biological and Mathematical Models to Explain and Overcome Drug Resistance in Cancer, Part 1: Biological Facts and Studies in Drug Resistance, Current Stem Cell Reports, vol.3, pp.253-259, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01558477

A. Goldman, Integrating Biological and Mathematical Models to Explain and Overcome Drug Resistance in Cancer, From Theoretical Biology to Mathematical Models, vol.2, pp.260-268, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01558477

M. M. Gottesman, Mechanisms of cancer drug resistance, Annu. Rev. Med, vol.53, pp.615-627, 2002.

M. M. Gottesman, Multidrug resistance in cancer: role of ATPdependent transporters, Nat. Rev. Cancer, vol.2, issue.1, pp.48-58, 2002.

P. Hirsch, Genetic hierarchy and temporal variegation in the clonal history of acute myeloid leukaemia, Nature Comm, vol.7, p.12475, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01358183

C. A. Gravenmier, Adaptation to Stochastic Temporal Variations in Intratumoral Blood Flow: The Warburg Effect as a Bet Hedging Strategy, Bull Math Biol, vol.80, issue.5, pp.954-970, 2017.

S. Huang, On the intrinsic inevitability of cancer: From foetal to fatal attraction, Sem. Canc. Biol, vol.21, pp.183-199, 2011.

S. Huang, Genetic and non-genetic instability in tumor progression: link between the fitness landscape and the epigenetic landscape of cancer cells, Canc. Metastasis Rev, vol.32, pp.423-448, 2013.

L. Israel, Tumour progression: random mutations or an integrated survival response to cellular stress conserved from unicellular organisms?, J. Theor. Biol, vol.178, issue.4, pp.375-380, 1996.

P. E. Jabin and G. , On selection dynamics for competitive interactions, J. Math. Biol, vol.63, pp.493-551, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00602077

F. Jacob, Evolution and tinkering, Science, vol.196, issue.4295, pp.1161-1166, 1977.

C. H. Lineweaver, Targeting cancers weaknesses (not its strengths): therapeutic strategies suggested by the atavistic model, Bioessays, vol.36, issue.9, pp.827-835, 2014.

T. Lorenzi, Dissecting thedynamics of epigenetic changes in phenotype-structured populations exposed to fluctuating environments, J. Theor. Biol, vol.386, pp.166-176, 2015.

T. Lorenzi, Tracking the evolution of cancer cell populations through the mathematical lens of phenotype-structured equations, Biology Direct, vol.11, p.43, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01321535

A. Lorz, Populational adaptive evolution, chemotherapeutic resistance and multiple anticancer therapies, ESAIM Math. Model. Numer. Anal, vol.47, issue.2, pp.377-399, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00714274

A. Lorz, Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors, Bull. Math. Biol, vol.77, issue.1, p.122, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00921266

A. Marusyk, Intra-tumour heterogeneity: a looking glass for cancer?, Nature Rev. Cancer, vol.12, pp.323-334, 2012.

J. M. Smith and E. Szathmáry, The major transitions in evolution, 1995.

R. E. Michod and D. Roze, Cooperation and conflict in the evolution of multicellularity, Heredity, vol.36, pp.1-7, 2001.

R. E. Michod and D. Roze, Cooperation and conflict during evolutionary transitions in individuality, J. Evol. Biol, vol.19, pp.1406-1409, 2006.

R. E. Michod, Life-history evolution and the origin of multicellularity, J. Theor. Biol, vol.239, pp.257-272, 2006.

K. Polyak and A. Marusyk, Clonal cooperation, Nature, vol.508, pp.52-53, 2014.

A. O. Pisco, Non-Darwinian dynamics in therapy-induced cancer drug resistance, Nat. Commun, vol.4, p.2467, 2013.

A. O. Pisco and S. Huang, Non-genetic cancer cell plasticity and therapy-induced stemness in tumour relapse: 'What does not kill me strengthens me, Br. J. Cancer, vol.112, issue.11, pp.1725-1757, 2015.

C. Pouchol, Asymptotic analysis and optimal control of an integro-differential system modelling healthy and cancer cells exposed to chemotherapy, J. Math. Pures Appl, vol.116, pp.268-308, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01673589

C. Pouchol and E. Trélat, Global stability with selection in integrodifferential Lotka-Volterra systems modelling trait-structured populations, J. Biol. Dynamics, vol.12, issue.1, pp.872-893, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01470722

S. V. Sharma, A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations, Cell, vol.141, pp.69-80, 2010.

D. P. Tabassum and K. Polyak, Tumorigenesis: it takes a village, Nature Rev. Cancer, vol.15, pp.473-483, 2015.

A. S. Trigos, Altered interactions between unicellular and multicellular genes drive hallmarks of transformation in a diverse range of solid tumors, vol.114, pp.6406-6411, 2017.

A. S. Trigos, How the evolution of multicellularity set the stage for cancer, Br. J. Cancer, vol.118, pp.145-152, 2018.

J. E. Trosko, Mechanisms of tumor promotion: possible role of inhibited intercellular communication, Eur. J. Cancer Clin. Oncol, vol.23, issue.6, pp.599-601, 1987.

J. E. Trosko, Gap Junctional Intercellular Communication as a Biological "Rosetta Stone" in Understanding, in a Systems Biological Manner, Stem Cell Behavior, Mechanisms of Epigenetic Toxicology, Chemoprevention and Chemotherapy, J. Membrane Biol, vol.218, pp.93-100, 2007.

J. E. Trosko, A conceptual integration of extra-, intra-and gap junctional-intercellular communication in the evolution of multi-cellularity and stem cells: how disrupted cell-cell communication during development can affect diseases later in life, Int. J. Stem Cell Res. Ther, vol.3, issue.1, p.21, 2016.

M. D. Vincent, Cancer: a de-repression of a default survival program common to all cells?: a lifehistory perspective on the nature of cancer, Bioessays, vol.34, issue.1, pp.72-82, 2011.

C. H. Waddington, The strategies of the genes, George Allen & Unwin, 1957.

A. Wu, Ancient hot and cold genes and chemotherapy resistance emergence, Proc. Nat. Acad. Sci, vol.112, pp.10467-10472, 2015.

J. S. You and P. A. Jones, Cancer genetics and epigenetics: two sides of the same coin?, Cancer Cell, vol.22, issue.1, pp.9-20, 2012.

J. X. Zhou, Phylostratigraphic analysis of tumor and developmental transcriptomes reveals relationship between oncogenesis, phylogenesis and ontogenesis, Converg. Sci. Phys. Oncol, vol.4, p.25002, 2018.