Revue : Evolutionary Applications
Arnal A., Ujvari B., Crespi B., Gatenby R., Tissot T., Vittecoq M., Ewald P., Casali A., Ducasse H., Jacqueline C., Misse D., Renaud F., Roche B., Thomas F.
* Auteur correspondant : Frédéric Thomas
The evolutionary perspective of cancer (which origins and dynamics result from evolutionary processes) has gained significant international recognition over the past decade and generated a wave of enthusiasm among researchers. In this context, several authors proposed that insights into evolutionary and adaptation dynamics of cancers can be gained by studying the evolutionary strategies of organisms. Although this reasoning is fundamentally correct, in our opinion, it contains a potential risk of excessive adaptationism, potentially leading to the suggestion of complex adaptations that are unlikely to evolve among cancerous cells. For example, the ability of recognizing related conspecifics and adjusting accordingly behaviors as in certain free-living species appears unlikely in cancer. Indeed, despite their rapid evolutionary rate, malignant cells are under selective pressures for their altered lifestyle for only few decades. In addition, even though cancer cells can theoretically display highly sophisticated adaptive responses, it would be crucial to determine the frequency of their occurrence in patients with cancer, before therapeutic applications can be considered. Scientists who try to explain oncogenesis will need in the future to critically evaluate the metaphorical comparison of selective processes affecting cancerous cells with those affecting organisms. This approach seems essential for the applications of evolutionary biology to understand the origin of cancers, with prophylactic and therapeutic applications.
Référence bibliographique complète :
Arnal A., Ujvari B., Crespi B., Gatenby R., Tissot T., Vittecoq M., Ewald P., Casali A., Ducasse H., Jacqueline C., Misse D., Renaud F., Roche B., Thomas F. (2015), Evolutionary perspective of cancer: myth, metaphors, and reality, Evolutionary Applications 8:6, DOI : 10.1111/eva.12265