Find the flame: Predictive biomarkers for immunotherapy in melanoma
| Autor: | Fabio Puglisi, Iris Zalaudek, S. Buriolla, Serena Bonin, Mattia Garutti, Maria Antonietta Pizzichetta, E. Bertoli |
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| Přispěvatelé: | Garutti, M., Bonin, S., Buriolla, S., Bertoli, E., Pizzichetta, M. A., Zalaudek, I., Puglisi, F. |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Oncology Cancer Research medicine.medical_specialty medicine.medical_treatment Context (language use) Pembrolizumab Review Biomarkers Checkpoint inhibitors CTLA-4 Immunotherapy Melanoma Meta-analysis Nivolumab PD-1 PDL-1 lcsh:RC254-282 meta-analysi 03 medical and health sciences 0302 clinical medicine Internal medicine melanoma medicine Predictive biomarker nivolumab business.industry biomarkers immunotherapy checkpoint inhibitors pembrolizumab meta-analysis lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens medicine.disease checkpoint inhibitor 030104 developmental biology 030220 oncology & carcinogenesis biomarker business |
| Zdroj: | Cancers Cancers, Vol 13, Iss 1819, p 1819 (2021) |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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