A major new research study has identified potential new ways to treat the most common type of bowel cancer. 

The study, conducted by an international research team led by The Institute of Cancer Research, London and RCSI University of Medicine and Health Sciences, provides a roadmap for repurposing existing drugs and developing new ones. 

Of the 48,213 new bowel cancer cases diagnosed annually in the UK, Microsatellite stable (MSS) colorectal cancer accounts for 80-85% of these, but remains challenging to treat, with limited response to many newer therapies.  

Now, researchers have discovered vulnerabilities in these tumours and have identified the drug combinations – including drugs already approved to treat other tumour types – that could be used to target them. 

Using 2,000 patient tumour samples, the researchers analysed genetic, metabolic protein and clinical data with the help of artificial intelligence (AI) tools, revealing previously unrecognised ways in which the cancer cells divide, grow, adapt and interact with their environment. 

To do this, the team developed an AI approach called iPhenMap, which can create a biological map of the tumour. Using this map, they were able to spot connections between the different elements of the tumour that have been missed in previous studies that looked at the data in isolation. 

A strong foundation for further development 

They tested the discovered vulnerabilities in laboratory models and showed that certain drug combinations could work well to target them and treat the cancer. 

For example, the targeted drug trametinib – approved to treat various cancers including melanoma, lung cancer, and thyroid cancer, with a specific mutation – was shown to significantly reduce tumour growth and extend survival in the laboratory models when combined with other drugs. 

Professor Annette Byrne, Head of the Precision Cancer Medicine Group, RCSI University of Medicine and Health Sciences, said: “While these findings remain preclinical, they highlight promising therapeutic opportunities and provide a strong foundation for further development. The next step will be to identify the biological features that predict response and determine how these approaches can be advanced safely towards clinical evaluation.”