Robot war on cancer
A COMPUTER tool that uses artificial intelligence could save the lives of thousands of cancer patients. The machine, designed in Britain, can learn to predict how tumours will grow, evolve and spread, scientists revealed last night.
That will enable doctors to tackle the disease earlier and tailor drug treatment to each individual.
The technology has the potential to forecast whether a tumour will become aggressive, how likely it is to respond to treatment and what drug combinations might work.
The new technique, which has been shown to work in tests on historic tissue samples, could be in use in cancer clinics within a few years.
The work is being carried out by a team led by the Institute of Cancer Research in London.
The institute’s Dr Andrea Sottoriva said: “It’s an exciting breakthrough and extremely important because ultimately making predictions means we cannot just prevent the disease but in those with advanced cancer we can control it.
“Patients fear cancer but in the future it will be like people living with diabetes or HIV, many of whom live normal lives. We want to make the next generation not so afraid of cancer.”
The AI tool is called Revolver, which stands for repeated evolution of cancer. It studies the genetic make-up of vast numbers of tumour samples to spot patterns which are used to forecast the future.
The ever-changing nature of tumours is one of the biggest challenges in treating cancer.
The disease often evolves into a drug-resistant form.
The new system, developed by scientists at the ICR and the University of Edinburgh working with the University of Birmingham, Stanford University in California and Queen Mary University, London, is able to identify common patterns and sequences buried deep within a confusing mass of DNA data.
It has been tested on 768 samples from 178 lung, breast, kidney and bowel cancer patients.
Dr Sottoriva said: “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. “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.
“I would liken our efforts to a game of chess. The best chance we have of beating cancer at its own game is to predict its next move and we are developing our play. “Instead of simply responding to cancer’s every move, we want to become more akin to a grandmaster – looking several steps ahead, seeing the patterns in play and devising our own strategy to thwart it.”
Unearthing repeating patterns of DNA mutations could be used to predict whether patients will develop resistance to drugs, the research published in the journal Nature Methods shows.
Professor Paul Workman, the institute’s chief executive, said: “Cancer evolution is the biggest challenge we face in creating treatments that will work more effectively for patients.
“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.
“This new approach using AI could allow treatment to be personalised in a more detailed way and at an earlier stage than is currently possible, tailoring it to the characteristics of each individual tumour and to predictions of what that tumour will look like in the future.”
Study co-leader Professor Guido Sanguinetti, of Edinburgh University, said: “By solving a statistical machine learning problem we were able to shed light on cancer evolution. It is an example of how the power of AI to detect complex patterns in data can be harnessed to further our scientific understanding to improve human health.”
Professor Karen Vousden, Cancer Research UK’s chief scientist, said: “This study highlights that among the genetic chaos within tumours, there are patterns that we can use to our advantage to understand and even possibly predict cancer’s next move.
“It’s important that we now test whether machine learning could be applied when treating patients and if we can use these mathematical methods to inform which treatments are most likely to be effective. As we enter a new age of technological innovation, artif cial intelligence and machine learning are opening up many exciting areas of exploration for improving the detection and treatment of different cancers.”
The search for novel ways to beat cancer comes as forecasts show half of us will develop the disease at some point in our lives.
Meanwhile, tens of thousands of sufferers are waiting more than two months to start treatment.
The NHS has failed to meet its 62-day target for the past two-and-a-half years. It was missed again in June, with statistics showing only 79 per cent of patients in England started treatment within two months of being urgently referred by their GP, against a target of 85 per cent.