A guide to understanding tumour evolution through the lens of population genetics.
Population genetics reveals that cancer evolution can be quantitatively understood through models of mutation, selection, and drift, transforming genomic data into evolutionary insights.
- Why it matters: Understanding the timing and strength of key adaptations in tumors is crucial for predicting relapse and treatment outcomes, but current sequencing methods only provide static snapshots of dynamic processes.
- What they did: The authors review how population genetics models analyze allele frequencies from cancer genomes to estimate clonal fitness, evolutionary timings, and extend to factors like epigenetics and ecological interactions.
- The result: Applying these principles enables researchers to interpret cancer genomes as records of evolutionary dynamics, paving the way for better prediction and management of cancer progression.