Artificial intelligence used to predict how cancers progress

A close-up of ovarian cancer
A close-up of ovarian cancer
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Scientists have used artificial intelligence to predict how cancers will progress and evolve, which could help doctors design the most effective treatment for each patient.

A team led by the Institute of Cancer Research London (ICR) and the University of Edinburgh developed a new technique known as Revolver (Repeated evolution of cancer), which picks out patterns in DNA mutation within cancers and uses the information to forecast future genetic changes.

They said the ever-changing nature of tumours is one of the biggest challenges in treating cancer - with cancers often evolving to a drug-resistant form.

But if doctors can predict how a tumour will evolve, they could intervene earlier to stop cancer in its tracks before it has had a chance to evolve or develop resistance, increasing the patient’s chances of survival. The team also found a link between certain sequences of repeated tumour mutations and survival outcome. This suggests that repeating patterns of DNA mutations could be used as an indicator of prognosis, helping to shape future treatment. For example, researchers found that breast tumours which had a sequence of errors in the genetic material that codes for the tumour-suppressing protein p53, followed by mutations in chromosome 8, survived less time than those with other similar trajectories of genetic changes. The team developed a new machine learning technique which transfers knowledge about tumours across similar patients. This method identifies patterns in the order that genetic mutations occur in tumours that are repeated both within and between patients’ tumours, applying one tumour’s pattern of mutations to predict another’s.

Researchers used 768 tumour samples from 178 patients reported in previous studies for lung, breast, kidney and bowel cancer, and analysed the data within each cancer type respectively to accurately detect and compare changes in each tumour. By identifying repeating patterns and combining this with current knowledge of cancer biology and evolution, scientists could predict the future trajectory of tumour development.

If tumours with certain patterns are found to develop resistance to a particular treatment, this novel methodology could be used to predict if patients will develop resistance in the future.

Dr Andrea Sottoriva, who led the study said: “We’ve developed a powerful artificial intelligence tool which can make predictions about future steps in the evolution of tumours based on certain patterns of mutation that so far remained hidden within complex data sets.”