Find the Flame: Predictive Biomarkers for Immunotherapy in Melanoma

SIMPLE SUMMARY: Immunotherapy has revolutionized the therapeutic landscape of melanoma. However, the absence of clinically validated predictive biomarkers is one of the major causes of unpredictable efficacy of immunotherapy. Indeed, the availability of predictive biomarkers could allow a better stratification of patients, suggesting which type of drugs should be used in a certain clinical context and guiding clinicians in escalating or de-escalating therapy. However, the difficulty in obtaining clinically useful predictive biomarkers reflects the deep complexity of tumor biology. Herein, we review the available literature to depict the most useful or promising biological biomarker able to predict immunotherapy response in melanoma. We also make a meta-analysis regarding PDL1 expression in melanoma and immune checkpoint response. ABSTRACT: Immunotherapy has revolutionized the therapeutic landscape of melanoma. In particular, checkpoint inhibition has shown to increase long-term outcome, and, in some cases, it can be virtually curative. However, the absence of clinically validated predictive biomarkers is one of the major causes of unpredictable efficacy of immunotherapy. Indeed, the availability of predictive biomarkers could allow a better stratification of patients, suggesting which type of drugs should be used in a certain clinical context and guiding clinicians in escalating or de-escalating therapy. However, the difficulty in obtaining clinically useful predictive biomarkers reflects the deep complexity of tumor biology. Biomarkers can be classified as tumor-intrinsic biomarkers, microenvironment biomarkers, and systemic biomarkers. Herein we review the available literature to classify and describe predictive biomarkers for checkpoint inhibition in melanoma with the aim of helping clinicians in the decision-making process. We also performed a meta-analysis on the predictive value of PDL-1.