Research showed that prescribing based solely on levels of proteins present is unlikely to be suitable

With a focus on advancing personalised cancer treatment, scientists have demonstrated that biomarkers are not enough to tell which patients are likely to respond best to immunotherapy.

According to a study from University of Bath’s Centre for Therapeutic Innovation (CTI-Bath), clinicians also need to understand how immune cells and tumours are interacting within a patient, rather than relying on the levels of associated proteins present when prescribing the optimum treatment.

The research team – alongside colleagues in Bordeaux – has published the study in the journal Cancers. Results validate a quantitative imaging platform incorporated at CTI-Bath, which can predict whether a cancer patient would respond to immunotherapy treatment.

Cancers typically evade detection by the immune system, making themselves invisible to the natural anti-tumour response and actively blocking it. One type of immunotherapy – immune checkpoint inhibitors – remove the brakes which the tumour has applied to the immune system. This re-activates the natural anti-cancer response, which in turn destroys the tumour.

To investigate the role of these types of the immune check point regulators in cancer patients, the research team recruited 15 patients with metastatic lung tumours who were undergoing a treatment called radiofrequency ablation (RFA). Furthermore, In some cases, treating tumours in one lung using RFA can cause tumours in the other lung to also reduce in size.

Researchers compared levels of the regulators and their targets with how they were interacting – using the immune-FRET molecular imaging platform which was developed by Professor Larijani and co-workers in UK and the EU. The technology can establish how molecules interact at a nanoscale level in single cells and tissue samples.

It is the first time these interactions have been quantified within RFA patients and they show that engagement did not correlate with the quantity of protein present. In conclusion, this means that prescribing based on the levels of proteins present is unlikely to be suitable.

Professor Banafshe Larijani explained: “The results show that you can get a better picture of what’s happening within a patient by measuring engagement of immune checkpoint interactions, thus more accurately predicting level of immune suppression and likely response to RFA treatment, instead of simply the levels of the proteins involved.

“Ultimately we hope this can result in a change in how immunotherapy is prescribed to RFA patients so it’s personalised to an individual,” he added