Jürgen Wolf, MD, University Hospital of Cologne, Cologne, Germany, talks about strategies to select the patients most likely to benefit from immune checkpoint inhibitors, a class of drugs that activate the immune system against tumour cells.
Current selection strategies are based on the expression levels of PD-L1 in the tumour, with higher levels of expression associated with a higher likelihood of response to treatment. However, Prof Wolf points out that PD-L1 expression is not always associated with a good response to immunotherapy. There are cases of PD-L1 positive patients who do not respond to treatment and conversely, cases of PD-L1 negative-patients who benefit from treatment. Therefore, there is a need for better predictive biomarkers to enable more precise treatment decisions. Prof Wolf discusses two strategies for patient selection that go beyond PD-L1 testing.
The first is overall mutational burden, the sum of all mutations present in a tumour cell. The higher the mutation burden, the higher the probability of a response to immunotherapy.
The second strategy aims to look at the tumour micro-environment and the multiple interactions that take place between the different components of the immune system. Transcriptome analysis looks at the activity of the tumour’s whole genome as opposed to gene mutations. By looking at activity of the whole genome, Prof Wolf’s research aims to identify patterns that differentiate patients who will respond to immunotherapy from those who will not. These strategies are currently under investigation and not yet ready to be translated into clinical practice.
Recorded at the 2017 meeting of the British Thoracic Oncology Group (BTOG) in Dublin, Ireland.
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