| Literature DB >> 33920288 |
Mattia Garutti1, Serena Bonin2, Silvia Buriolla3,4, Elisa Bertoli1,3, Maria Antonietta Pizzichetta1,5, Iris Zalaudek5, Fabio Puglisi1,3.
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.Entities:
Keywords: CTLA-4; PD-1; PDL-1; biomarkers; checkpoint inhibitors; immunotherapy; melanoma; meta-analysis; nivolumab; pembrolizumab
Year: 2021 PMID: 33920288 DOI: 10.3390/cancers13081819
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639