Biomarkers that predict response to immunotherapy - no magic bullet
Immunotherapeutic agents have shown impressive clinical efficacy in a broad range of tumour types, particularly in non-small cell lung cancer and melanoma. An effective predictive biomarker is needed to provide patients with the most effective available treatments, avoid unnecessary toxicity and improve cost effectiveness. While it has been an area of very active research in recent years, the ideal biomarker for predicting response to immune check point inhibitor therapy has not yet been universally agreed upon. Approaches to date have focussed on assessment of tumour related factors such as immunohistochemical expression of programmed death ligand-1 (PD-L1), mutational load and DNA mismatch repair gene or protein status. Alternatively, assessment of the immune microenvironment by techniques such as gene expression profiling or measurement of tumour infiltrating lymphocytes can also be informative. Identifying and validating effective biomarkers is particularly challenging for immunotherapy because the dynamic and multifactorial nature of the interaction between tumours and host immunity. In this review, we discuss the relative advantages and disadvantages of different biomarker approaches in the quest to identify a clinically effective predictive biomarker that can improve the overall utility for immune checkpoint inhibitors.
|Authors||Cooper, W. A.; Barnet, M. B.; Kao, S. C.; Scolyer, R. A.|
|Responsible Garvan Author||Megan Barnet|
|Publisher Name||Cancer Forum|
|URL link to publisher's version||<Go to ISI>://WOS:000431012700009|