Cancer Evolution and the Limits of Predictability in Precision Cancer Medicine
| Autor: | Ka, Lipinski, Lj, Barber, Mn, Davies, Ashenden M, Sottoriva A, Marco Gerlinger |
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| Rok vydání: | 2016 |
| Předmět: | |
| Zdroj: | Europe PubMed Central Trends in Cancer |
| ISSN: | 2405-8033 |
| DOI: | 10.1016/j.trecan.2015.11.003 |
| Popis: | The ability to predict the future behavior of an individual cancer is crucial for precision cancer medicine. The discovery of extensive intratumor heterogeneity and ongoing clonal adaptation in human tumors substantiated the notion of cancer as an evolutionary process. Random events are inherent in evolution and tumor spatial structures hinder the efficacy of selection, which is the only deterministic evolutionary force. This review outlines how the interaction of these stochastic and deterministic processes, which have been extensively studied in evolutionary biology, limits cancer predictability and develops evolutionary strategies to improve predictions. Understanding and advancing the cancer predictability horizon is crucial to improve precision medicine outcomes. Trends Large-scale genomic cancer medicine initiatives are under way in several countries across the globe. However, it remains a major challenge to use genomic information to make accurate predictions for individual cancer patients. Multiple genomic studies substantiated the notion of cancer as an evolutionary process that can readily adapt within the lifetime of a patient. Evolutionary adaptation results from the interplay of mutation generation and genetic drift, which are both stochastic processes, and clonal selection, which is deterministic in nature. The influence of stochastic factors fundamentally limits the predictability of cancer evolution. Understanding the limits of predictability and the development of more accurate prediction algorithms using evolutionary models is key to improving outcomes through genomic cancer medicine. |
| Databáze: | OpenAIRE |
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