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Solving challenges posed by cancer mutations to help cancer patients


Cancer ranks as the leading cause of death in a growing number of Member States in the European Union. Yet, for such a major disease, it takes just a handful of mutations to turn a cell cancerous.  

And while scientists speak of “cancer pathways”, involving hundreds or thousands of genes and their proteins, each cancer is quite unique to a patient. ‘Every tumour is different,’ said Dr Bodo Lange, cancer researcher and CEO of Alacris Theranostics, a diagnostic cancer company in Berlin. ‘Each has a different combination of mutations.’

Cancer cells ignore orders from the body to stop proliferating and refuse to die. Instead, they go rogue and evolve to survive. The traditional approach is to introduce agents that rapidly kill dividing cells – chemotherapies. This kills cancer but also healthy cells, thereby causing severe side effects, such as fatigue, nausea, hair loss and pain in toes and fingers. 

A newer treatment strategy is to turn off some genes or interfere with specific proteins in a way that will slow proliferation or kill off the rogue cells. But the sprawling network of genes and proteins involved is incredibly complicated. It can be viewed as a vast subway map, with thousands of stations, each influencing others.

Cancer scientists want to understand the real reason behind cancer progression to help them to identify new drugs that impact the sprawling network of genes and proteins. Predicting the effect of drugs usually requires experiments in cells, mice, and finally clinical trials in patients. Now, an international project with 10 partners, led by Dr Lange has developed a computer tool that can explore the behaviour of such complex cancer networks, predict the effect of a drug on networks (in cells and mice) and answer whether a drug has the potential to stop cancer cells proliferating.

‘By making the first predictions in a computer model we can test the effect of drugs on cancer signalling,’ said Dr Lange, which will allow for better experiments and save time and money for academics, biotech and industry. ‘This will also greatly reduce the need for animal experiments.’ Forty-five cancer pathways, 500 genes, and 5,500 reactions are accounted for in his prediction tool, which was developed by the CanPathPro project, coordinated by Alacris. 

‘For the pharma industry, we can say give us the drug information, so we can test it and tell you which type of cancer it will work for, and under what kind of circumstances,’ Dr Lange explained. This will in future allow for virtual clinical trials, in which a drug can be screened to identify which tumours it will likely work best on.

Since the experiment is in silico (in the computer), drug combinations are easier to try out and their outcome predicted, greatly reducing the need for lab tests. Already, the tool matched the drug response predictions with over 80% precision. 

The drugs in question should not hit all dividing cells, as most chemotherapies do, but impair tumours in more subtle and targeted ways, and so crucially reduce injury to healthy tissues.

Dr Bodo Lange, CEO of Alacris Theranostics

It will not predict whether a potential drug will work in a patient, but rather help move drug candidates towards the clinic faster. The drugs in question should not hit all dividing cells, as most chemotherapies do, but impair tumours in more subtle and targeted ways, and so crucially reduce injury to healthy tissues.

Knowing you, knowing me

There is an increasing need to better understand each patient’s tumour to deliver precision medicine. Each cancer cell starts off in its own way, and then evolves by mutating. This can allow cancers to dodge our immune system and resist treatments. There is optimism, nonetheless, that we can deal better with these shape shifters.

‘In future, we will turn cancer into a chronic disease,’ predicts Dr Lange. ‘You will take a biopsy at one point, find the best drug to treat a patient, and get the cancer under control.’ Subsequent mutations might allow this cancer to escape from the drug, he adds, but every new test could point to a drug to control the evolving cancer. The patient would avoid the debilitating side effects of chemo and radiotherapy and have a better quality of life. 

Still, this great hope for new drugs will require scientists to gain yet more knowledge about cancer. ‘It is very important that we identify which specific mutations drive tumorigenesis (where normal cells are transformed in cancer cells),’ said Prof. Núria López-Bigas, ICREA researcher at IRB Barcelona, who added that usually between two and seven mutations drive cancer to begin with. In recent years some drugs have been developed to counteract the effect of such driver mutations. But knowing about them is key.

Our ordinary cells also divide and accumulate mutations throughout our lives.  Consequently, cancer cells carry thousands of mutations from previous cell divisions, and it is difficult to pinpoint those that initiated the cancer. To identify those, Prof. López-Bigas has developed a machine-learning approach as part of her project, NONCODRIVERS.

The project analysed mutations from 28,000 tumours from 66 types of cancer. This allowed a computational tool to be created that identifies cancer driver mutations for each tumour type. This cancer blueprint will help interpret a patient’s own tumour, and was reported in the prestigious science publication Nature.   

Understanding the mechanism of cancer at a molecular level gives ideas for new targeted treatments

Prof. Núria López-Bigas, ICREA researcher at IRB Barcelona

Today it is possible to sequence the entire DNA of a cancer cell and identify which mutations it contains. ‘But you will still have the problem of interpreting them, and that is what our tool helps with,’ Prof. López-Bigas explained. Such knowledge is also useful for identifying proteins that might make for good targets for new cancer drugs. 

‘Understanding the mechanism of cancer at a molecular level gives ideas for new targeted treatments,’ Prof. López-Bigas said.  ‘And knowing the mutations in the cancer of a specific patient can give you the information needed to choose an available treatment or one that is under development.’

The research in this article was funded by the EU. If you liked this article, please consider sharing it on social media.

EU Policy on Cancer

By joining efforts across Europe, the Horizon Europe Mission on Cancer together with Europe’s Beating Cancer Plan will provide a better understanding of cancer, allow for earlier diagnosis and optimise treatment and improve cancer patients’ quality of life during and beyond their cancer treatment.

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