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The Promising Connection Between Data Science and Evolutionary Theory in Oncology
Jonathan R Goodman1, Hutan Ashrafian2
1Leverhulme Centre for Human Evolutionary Studies, University of Cambridge, Cambridge, United Kingdom.
Frontiers in Oncology
|February 11, 2020
Summary
Cancer drug resistance can be better managed by viewing cancer progression as an evolutionary process influenced by human treatment choices. Applying evolutionary oncology principles and machine learning can improve patient outcomes and shift medical paradigms.
Area of Science:
- Evolutionary biology
- Oncology
- Computational biology
Background:
- Cancer progression and oncogenesis are increasingly understood through an evolutionary lens.
- Current anti-cancer drug resistance strategies often overlook the role of human-driven selection.
- Treating cancer as an isolated biological agent, separate from human activity, limits treatment efficacy.
Purpose of the Study:
- To advocate for integrating evolutionary principles into cancer treatment strategies.
- To highlight the potential of understanding drug resistance as a product of artificial selection.
- To propose a paradigm shift in medicine by uniting evolutionary theory with clinical practice.
Main Methods:
- Reviewing theoretical and empirical work on cancer evolution.
- Analyzing current anti-resistance strategies in oncology.
- Exploring the application of machine learning algorithms to predict drug resistance-related genetic changes.
Main Results:
- Drug resistance in cancer can be framed as a consequence of anthropogenic selection, not solely natural processes.
- Machine learning models can identify genetic markers associated with drug resistance across various cancer types.
- Integrating evolutionary insights with technological tools offers practical clinical applications.
Conclusions:
- Understanding cancer as an evolutionary process influenced by treatment is crucial for improving patient outcomes.
- Consulting evolutionary oncology studies and utilizing predictive algorithms can enhance clinical trial and treatment design.
- A synthesis of evolutionary theory and technology may herald a new era in cancer medicine.
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