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Sophisticated new computer software can be used to predict how cancers may respond to a new drug before it has ever been given to patients.
The new program could transform the discovery of cancer drugs by predicting how tumours will become resistant to treatment long before it would first become apparent in clinical trials.
Based on the software’s predictions, researchers could start working on second-generation drugs to tackle treatment resistance before the first-generation drug is taken to patients.
It could also lead to the development of tests to assess patients for resistance mutations before and during treatment – delivering precision medicine at the earliest stage.
The new prediction tool was developed by scientists at The Institute of Cancer Research, London, with funding from Cancer Research UK, and is described in the journal Cell Chemical Biology today (Thursday).
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First prediction tool to include evolutionary impact
The approach begins by analysing all the possible mutations that could occur around a drug target – generally between 350 and 1,200.
The researchers then apply the prediction software to prioritise the mutations down to only 9 or 10 most likely to cause drug resistance - a more feasible number to investigate further in the laboratory.
The researchers tested their method on existing cancer drugs and drug targets – including 17 different drugs that target the important cancer-related proteins MAPK1, KIT, EGFR, Abl and ALK. It was able to accurately predict many of the mutations that doctors see in the clinic, and for MAPK many that were generated in the lab.
The prediction tool is the first to include the evolutionary impact of a mutation on cancer cells. If a mutation meant the drug target could no longer perform its role in a cell, then that cell is unlikely to survive and go on to form drug-resistant tumours.
Mutations could be either single- or double-letter changes in genes that would lead to a change in the building blocks (known as amino acids) that make up a protein.
Mutations also had to be in close vicinity to the site where the drug binds its target, and had to affect the drug target in a way that means the drug binds less tightly.
Lastly, the prediction tool identifies regions in the drug target where resistance ‘hotspots’ – areas predicted to have multiple mutations – are likely to occur and prioritised mutations at these ‘hotspots’ based on their likelihood of being formed in the cancer type under investigation.
'Hugely beneficial in designing new cancer drugs'
For the cancer drug imatinib, the program accurately predicted a common mutation that causes resistance to the drug in some patients. This approach also correctly predicted that the second-generation drug sunitinib wouldn’t be affected by this resistance mutation in the clinic.
Dr Teresa Kaserer, Higher Scientific Officer at The Institute of Cancer Research, London, who developed the new prediction tool, said:
“Our new approach can predict which mutations are likely to arise in response to drug treatment in different types of tumours.
“This will be hugely beneficial in designing new cancer drugs. Instead of reacting to what we see in the clinic – when it’s too late as patients have stopped responding to treatment – we can use our computational method to predict during the drug design stage how resistance will arise.
“It means we can begin designing second-generation treatments much earlier, as well as developing tests to select patients for treatment and monitor them while on the drug. This could be great news for patients, who could be switched to a second generation drug as soon as a resistance mutation appears.”
'Important first step'
Professor Julian Blagg, Deputy Director of the CRUK Cancer Therapeutics Unit at The Institute of Cancer Research, London, and study co-author said:
“In recent years, targeted cancer therapies have brought significant benefits to patients, but the eventual emergence of drug resistance remains a major challenge.
“Predicting how a cancer drug target may mutate to kick out the therapeutic agents whilst maintaining its normal function can help us stay one step ahead of tumour evolution by creating new treatments that block a cancer’s escape routes.
“Our study has explored one of the ways tumours can become resistant to cancer drugs, but there are other escape routes cancer cells can take to avoid destruction.
“Our approach is an important first step, and we, along with other colleagues at the ICR, are looking to develop similar tools to identify, right at the start of cancer drug discovery, the alternative roads to drug resistance.”
Alex Pemberton, head of therapeutic discovery funding at Cancer Research UK, said:
“This early study marks progress towards developing new tools to tackle one of the biggest issues in cancer treatment – drug resistance.
“By developing and using such tools, researchers funded at Cancer Research UK’s Drug Discovery Units and elsewhere can design drugs and treatment approaches that could prevent or delay the emergence of drug resistance and deliver real benefit to patients.”