Journal
EXPERT OPINION ON BIOLOGICAL THERAPY
Volume 22, Issue 5, Pages 563-576Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/14712598.2022.2038132
Keywords
CTLA-4; immune checkpoint inhibitors; immunotherapy; irAE; melanoma; PD-1; PD-L1; predictive biomarkers to immunotherapy
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Immune checkpoint inhibitors (ICIs) are an important part of melanoma treatment, but their efficacy is limited by immune escape mechanisms. Therefore, further studies are needed to confirm the effectiveness of combining different classes of ICIs and combining ICIs with other types of therapies. In addition, new and more effective predictive biomarkers are needed to more accurately define the therapeutic algorithms for melanoma patients.
Introduction Immune checkpoint inhibitor (ICI) based immunotherapy is dramatically changing the management of many types of cancers including melanoma. In this malignancy, ICIs prolong disease and progression-free survival as well as overall survival of a percentage of treated patients, becoming the cornerstone of melanoma treatment. Areas covered In this review, first, we will describe the mechanisms of immune checkpoint activation and inhibition, second, we will summarize the results obtained with ICIs in melanoma treatment in terms of efficacy as well as toxicity, third, we will discuss the potential mechanisms of immune escape from ICI, and lastly, we will review the potential predictive biomarkers of clinical efficacy of ICI-based immunotherapy in melanoma. Expert opinion ICIs represent one of the pillars of melanoma treatment. The success of ICI-based therapy is limited by the development of escape mechanisms, which allow melanoma cells to avoid recognition and destruction by immune cells. These results emphasize the need of additional studies to confirm the efficacy of therapies, which combine different classes of ICIs as well as ICIs with other types of therapies. Furthermore, novel and more effective predictive biomarkers are needed to better stratify melanoma patients in order to define more precisely the therapeutic algorithms.
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