Scientists have developed a tool that can predict how bowel cancer adapts to treatment – helping researchers to design new personalised drugs that will keep patients living well for longer.
A team from the Institute of Cancer Research, London, and Queen Mary University of London have designed a new technology that uses evolutionary biology to measure and predict how cancer cells will evolve when they are exposed to a new treatment.
Bowel cancer is the fourth most common cancer in the UK. There are around 44,100 new bowel cancer cases in the UK every year, or around 120 every day. Most bowel cancers are treated with chemotherapies and these treatments haven't changed in almost 50 years.
Patients with late-stage disease typically die from drug resistance – when the cancer stops responding to treatment.
Drug resistance is caused by molecular changes in cancer cells that renders the treatment ineffective. Understanding exactly how this resistance develops will allow researchers design new and better drugs that target the mechanisms of resistance – ensuring cancer is kept at bay for longer. It will also allow clinicians to use existing drugs in the optimal way – altering doses if necessary.
There are two routes that cancer cells can take to escape a drug's action, but until now, it has been very hard to tell them apart.
In research published in the journal Nature Communications, the team from the Centre for Evolution and Cancer at The Institute of Cancer Research (ICR), and funded by the Wellcome Trust and Cancer Research UK, tracked bowel cancer cells as they evolved resistance to chemotherapy.
Together with colleagues from Queen Mary University of London, the researchers used mathematical modelling to pinpoint when resistance to the drug developed. They could then determine whether resistance was caused by a rare genetic mutation in one cell that was copied as the cell divided, or whether there was a non-genetic change responsible.
The researchers have now turned their method, called EIRAs (Evolutionary Informed Resistance Assays), into a tool that can be adopted into the process of developing new medicines. By using EIRAS, they hope that new personalised drugs can be designed which target the route that a patients' tumour has taken to evolve resistance.
The researchers are seeking commercial partners to further progress this work, as well as working with colleagues in the ICR's Centre for Cancer Drug Discovery. A patent has been submitted for the technology, which the researchers believe could be used to support the development of a number of cancer drugs – they have already begun exploring its use for ovarian and breast cancer.
Professor Trevor Graham , Professor of Genomics and Evolution and Director of the Centre for Evolution and Cancer at The Institute of Cancer Research, London, said:
"Just like bacteria evolve resistance to antibiotics, cancer cells can evolve resistance to chemotherapy, making treatment less effective. This treatment resistance is a long-standing problem that we are desperate to solve. Cancers may respond well for a while, but sadly then they usually become resistant and the drug stops working.
"By studying bowel cancer cells over time as we treat them with chemotherapy, we have been able to develop a machine learning technology that can unpick how and when these cells become resistant. We hope this information will allow us to design new, personalised drugs – ones that target these changes so that the cancer responds to treatment. We also believe we can use the technology to learn how to alter the dose of existing drugs, to keep them working for longer.
"I'm excited to work with colleagues and partners – including those in the ICR's Centre for Cancer Drug Discovery – to implement this technology, and to bring more treatment options to patients living with cancer."
Professor Kristian Helin, Chief Executive of The Institute of Cancer Research , London, said:
"As cancer researchers, we are constantly searching for ways to halt cancer's growth when treatments stop working. This work will help us to identify new targets to tackle cancer once resistance develops.
"The research brings together ideas in machine learning, cancer evolution, and drug discovery. The Institute of Cancer Research has an unrivalled track record of drug discovery, and I look forward to seeing this technology progress, through our Centre for Cancer Drug Discovery and through collaborations with partners, to drive the development of treatments that benefit patients for even longer."
Professor Richard Nichols, Professor of Evolutionary Genetics in the School of Biological and Behavioural Sciences at Queen Mary University London, said:
"These advances have come from treating cancer cells' resistance to chemotherapy as a question about evolution. We asked whether their resistance has a genetic basis, building on methods that were first developed to resolve disputes among biologists about the colour patterns of snails. The success of this project shows the value of cross-fertilization of ideas, sometimes between subject areas that seem distantly related."
