Predicting responses to chemotherapy in bowel cancer patients
Bowel cancer is the fourth most common cancer in the UK, with around 42,300 people diagnosed with the disease every year. For many patients, the main treatment option is surgery, which is sometimes followed by chemotherapy. But this post-surgery chemotherapy only improves outcomes for a small number of patients, and it’s not possible to determine who will benefit from it and who won’t.
At Queen’s University in Belfast, Professor Daniel Longley and his team are tackling this challenge by using a new approach called ‘multi-omics’. This allows them to look at lots of types of biological data simultaneously, giving them a broad understanding of a patient’s DNA and other key molecules that might be involved in their cancer. They hope to find unique proteins and genetic markers that may help distinguish which patients will respond to chemotherapy after surgery. The result could drastically reduce the number of people who go through chemotherapy and its potentially debilitating side effects.
Identifying these biomarkers could also lead to the development of new treatments for people who don’t respond well to chemotherapy. Professor Longley is particularly interested in a molecule called PD-L1, which is found in large quantities in some bowel cancers and helps the tumour avoid detection and destruction by the immune system. Recent research suggests people with high levels of PD-L1 in their bowel tumour often don’t benefit from chemotherapy and may even be harmed by it, so Professor Longley is looking to build on these findings and identify why this is the case. He also wants to know if high levels of PD-L1 could be used as a biomarker to identify people who won’t benefit from chemotherapy and if these people could benefit from an immunotherapy drug that specifically targets the PD-L1 molecule instead.
Ultimately, Professor Longley’s research could save hundreds of people the trauma of undergoing chemotherapy they won’t benefit from and also provide them with an important alternative option.