How Does AI Help Cancer Research?

From robotic bartenders to mechanical surgeons, artificial intelligence is moving forward in leaps and bounds. Now, scientists are breaking new ground and pioneering AI technology as a means of predicting how cancers will progress and evolve. According to the team, the exciting new algorithm could help doctors customise treatment strategies for individual patients.  

Introducing REVOLVER

A joint effort from the Institute of Cancer Research London (ICR) and the University of Edinburgh, the project saw researchers develop an algorithm that analyses multi-region sequencing data and uses it to pinpoint DNA mutation patterns within cancers. The technology is known as REVOLVER (Repeated Evolution of Cancer) and could help doctors predict the ever-changing nature of tumours and manage the risk of cells evolving into drug-resistant forms, which is one of the biggest challenges associated with treating cancer.

"Cancer evolution is the biggest challenge we face in creating treatments that will work more effectively for patients," explains ICR chief executive Professor Paul Workman. "If we are able to predict how a tumour will evolve, the treatment could be altered before adaptation and drug resistance ever occur, putting us one step ahead of the cancer."

Prediction and prevention

Armed with the capacity to predict how tumours will evolve and develop resistance, doctors could intervene at earlier stages, develop more powerful treatment strategies and ultimately, increase chances of survival.

"With this tool we hope to remove one of cancer's trump cards - the fact that it evolves unpredictably, without us knowing what is going to happen next," says Dr Andrea Sottoriva, leader of the study and head of evolutionary genomics and modelling at the Institute of Cancer Research London.

Using AI to forecast a tumour's next move

Drawing on 768 tumour samples extracted from 178 patients, the researchers analysed data for each cancer type. The findings were used to develop an intelligent machine learning algorithm that transfers tumour knowledge across patients to actively identify genetic mutation patterns and predict the trajectory of tumour growth.

The findings were published in the journal Nature Methods, with Sottoriva explaining that knowledge of drug resistance patterns could step up as a formidable tool in the fight against cancer.

"With this tool we hope to remove one of cancer's trump cards - the fact that it evolves unpredictably, without us knowing what is going to happen next," she says. By giving us a peek into the future, we could potentially use this AI tool to intervene at an earlier stage, predicting cancer's next move."

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