BIOMEDICAL 14 THE SCIENTIST
OPINION One-to-one
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IMAGES: SCIENCE PHOTO LIBRARY/SHUTTERSTOCK
nderstanding how cancerous tumours evolve spatially and over time using real tissue is a complex process; it requires repeatedly taking multiple biopsies from various parts of a tumour. A computational model, however, developed by researchers at the Francis Crick Institute, the Royal Marsden NHS Foundation Trust and the Institute of Cancer Research, has identified links between tumour growth and shape, and how quickly a patient’s cancer might progress. The study used mathematical modelling, combined with detailed clinical, molecular, histological and radiological data from 66 real-life tumours from the TRACERx Renal study to understand how tumours come about and evolve. Cross-referencing their mathematical model with the other data, the researchers examined two types of tumour growth in kidney cancers. In the “volume growth model”, growth is consistent throughout the tumour, whereas in the “surface growth model”, growth is restricted to the tumour’s surface. They found that different rates of real-world tumour progression corresponded to different computational growth models. Tumours that rapidly progressed matched the scenario in the volume growth model where a single “fit” group of cells – which had gained an advantage through mutations that make them more likely to survive and divide even with low nutrient or oxygen levels – was present early on.
MODELLING BEHAVIOUR
Computational modelling has “provided a window into the evolution of a tumour”. Biological physicist Xiao Fu explains what this means for our knowledge of cancer progression.
Impact of tumour growth on shape Tumours that did not progress appeared to demonstrate that the original group of parental cancer cells remained dominant rather than a “fit” group forming – another scenario of the volume growth model. Extensive genetic diversity was found in the surface growth model of tumour progression, with different
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