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Inflammatory Biomarkers as Predictors of Response to Immunotherapy in Urological Tumors

Immunotherapy represents the new era of cancer treatment because of its promising results in various cancer types. In urological tumors, the use of the immune-checkpoint inhibitors (ICIs) is increasingly spreading. Although not all patients and not all diseases respond equally well to immunotherapy,...

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Detalles Bibliográficos
Autores principales: Schepisi, Giuseppe, Brighi, Nicole, Cursano, Maria Concetta, Gurioli, Giorgia, Ravaglia, Giorgia, Altavilla, Amelia, Burgio, Salvatore Luca, Testoni, Sara, Menna, Cecilia, Farolfi, Alberto, Casadei, Chiara, Tonini, Giuseppe, Santini, Daniele, De Giorgi, Ugo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6770345/
https://www.ncbi.nlm.nih.gov/pubmed/31641355
http://dx.doi.org/10.1155/2019/7317964
Descripción
Sumario:Immunotherapy represents the new era of cancer treatment because of its promising results in various cancer types. In urological tumors, the use of the immune-checkpoint inhibitors (ICIs) is increasingly spreading. Although not all patients and not all diseases respond equally well to immunotherapy, there is an increasing need to find predictive markers of response to ICIs. Patient- and tumor-related factors may be involved in primary and secondary resistance to immunotherapy: tumor-derived protein and cytokines, tumor mutational burden, and patient performance status and comorbidities can condition tumor response to ICIs. Recently, some of these factors have been evaluated as potential biomarkers of response, with conflicting results. To date, the expression of programmed death-ligand 1 (PD-L1) and the presence of deficient mismatch repair (dMMR) in tumor tissue are the only biomarkers capable of guiding the clinician's decision in urothelial cancer and prostate cancer, respectively. In this review, we performed a comprehensive search of the main publications on biomarkers that are predictive of response to ICIs in urological cancers. Our aim was to understand whether existing data have the potential to drive clinical decision-making in the near future.