Criticality in tumor evolution and clinical outcome
A partir de données issues du projet "The Cancer Genome Atlas" et portant sur 6 721 échantillons tumoraux (23 types de cancer), cette étude analyse la relation entre le nombre de mutations somatiques ponctuelles et la survie des patients puis, à l'aide d'une approche évolutionniste, identifie l'existence d'un état critique dans l'évolution des tumeurs en fonction de ce nombre de mutations
How mutation and selection co-determine the course of cancer evolution remains an open, fundamental question. We construct a mutation-selection phase diagram, using tumor mutation load (ML) and selection strength (dN/dS) as key variables, and assess their association with clinical outcome. The results reveal a biphasic evolutionary regime whereby beyond a critical ML, tumor fitness decreases with the number of mutations, although the proteome evolves near neutrality—that is, without strong selection. Deviations from neutrality at extreme ML show how positive selection (at low ML) and purifying selection (at high ML) may act to maintain tumor fitness. These results corroborate the existence of a critical state in cancer evolution predicted by theory and have fundamental and likely clinical implications.
How mutation and selection determine the fitness landscape of tumors and hence clinical outcome is an open fundamental question in cancer biology, crucial for the assessment of therapeutic strategies and resistance to treatment. Here we explore the mutation-selection phase diagram of 6,721 tumors representing 23 cancer types by quantifying the overall somatic point mutation load (ML) and selection (dN/dS) in the entire proteome of each tumor. We show that ML strongly correlates with patient survival, revealing two opposing regimes around a critical point. In low-ML cancers, a high number of mutations indicates poor prognosis, whereas high-ML cancers show the opposite trend, presumably due to mutational meltdown. Although the majority of cancers evolve near neutrality, deviations are observed at extreme MLs. Melanoma, with the highest ML, evolves under purifying selection, whereas in low-ML cancers, signatures of positive selection are observed, demonstrating how selection affects tumor fitness. Moreover, different cancers occupy specific positions on the ML–dN/dS plane, revealing a diversity of evolutionary trajectories. These results support and expand the theory of tumor evolution and its nonlinear effects on survival.
Proceedings of the National Academy of Sciences , article en libre accès, 2017