Damien BALDIN, Histoire des animaux domestiques, XIXe-XXe siècles

Les animaux occupent une place structurante dans la société française du XIXe siècle  : de par leur omniprésence sur le territoire et leur importance au sein de la vie économique et sociale d’une part ; à travers le discours à caractère affectif et politique qui se constituent à leur propos d’autre part. Partant de ce constat, Damien Baldin entend étudier le lien de domestication que l’homme instaure avec les animaux : ceux-ci sont dès lors définis par ce statut de « domestique » qui leur est..

Tumour growth and drug resistance: an evolutionary view with perspectives in therapeutics

International audienceBACKGROUND Drug-induced drug resistance in cancer hasbeen attributed to diverse biological mechanisms at the individualcell or cell population scale, relying on stochastically or epigeneticallyvarying expression of phenotypes at the single cell level,and on the adaptability of tumours at the cell population level.SCOPE OF THIS REVIEW We focus on intra-tumour heterogeneity,namely between-cell variability within cancer cell populations,to account for drug resistance. To shed light on such heterogeneity,we review evolutionary mechanisms that encompassthe great evolution that has designed multicellular organisms, aswell as smaller windows of evolution on the time scale of humandisease. We also present mathematical models used to predictdrug resistance in cancer and optimal control methods that cancircumvent it in combined therapeutic strategies.MAJOR CONCLUSIONS Plasticity in cancer cells, i.e., partialreversal to a stem-like status in individual cells and resultingadaptability of cancer cell populations, may be viewed as backwardevolution making cancer cell populations resistant to druginsult. This reversible plasticity is captured by mathematical modelsthat incorporate between-cell heterogeneity through continuousphenotypic variables. Such models have the benefit of beingcompatible with optimal control methods for the design of optimisedtherapeutic protocols involving combinations of cytotoxicand cytostatic treatments with epigenetic drugs and immunotherapies.GENERAL SIGNIFICANCE Gathering knowledge from cancerand evolutionary biology with physiologically based mathematicalmodels of cell population dynamics should provide oncologistswith a rationale to design optimised therapeutic strategiesto circumvent drug resistance, that still remains a major pitfall ofcancer therapeutics

Tumour growth and drug resistance: an evolutionary view with perspectives in therapeutics

International audienceBACKGROUND Drug-induced drug resistance in cancer hasbeen attributed to diverse biological mechanisms at the individualcell or cell population scale, relying on stochastically or epigeneticallyvarying expression of phenotypes at the single cell level,and on the adaptability of tumours at the cell population level.SCOPE OF THIS REVIEW We focus on intra-tumour heterogeneity,namely between-cell variability within cancer cell populations,to account for drug resistance. To shed light on such heterogeneity,we review evolutionary mechanisms that encompassthe great evolution that has designed multicellular organisms, aswell as smaller windows of evolution on the time scale of humandisease. We also present mathematical models used to predictdrug resistance in cancer and optimal control methods that cancircumvent it in combined therapeutic strategies.MAJOR CONCLUSIONS Plasticity in cancer cells, i.e., partialreversal to a stem-like status in individual cells and resultingadaptability of cancer cell populations, may be viewed as backwardevolution making cancer cell populations resistant to druginsult. This reversible plasticity is captured by mathematical modelsthat incorporate between-cell heterogeneity through continuousphenotypic variables. Such models have the benefit of beingcompatible with optimal control methods for the design of optimisedtherapeutic protocols involving combinations of cytotoxicand cytostatic treatments with epigenetic drugs and immunotherapies.GENERAL SIGNIFICANCE Gathering knowledge from cancerand evolutionary biology with physiologically based mathematicalmodels of cell population dynamics should provide oncologistswith a rationale to design optimised therapeutic strategiesto circumvent drug resistance, that still remains a major pitfall ofcancer therapeutics