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Molecular predictors of response to PD-1/PD-L1 inhibition in urothelial cancer.
World Journal of Urology 2018 October 30
INTRODUCTION: The survival of patients with metastatic urothelial cancer (mUC) is poor. During the last 40 years, chemotherapy was the predominant treatment modality for mUC. The discovery of the immune checkpoint inhibitors (ICI), especially the inhibitors of the programmed cell death 1 and its ligand (PD-1/PD-L1), has revolutionized cancer immunotherapy. The PD-1 and PD-L1 inhibitors provide a new and effective treatment option for patients with UC, particularly for patients with recurrence after platinum-based therapy and those who are ineligible for cisplatin.
METHODS: A literature search on PubMed, ClinicalTrials.gov and selected annual congress abstracts was conducted in May 2018, using a combination of keywords, medical subject headings (MeSH) terms and free text incorporating urothelial bladder cancer; immunotherapy; immune checkpoint inhibition, biomarkers, PD1/PD-L1.
RESULTS: Although some patients demonstrate complete and/or durable responses under ICI, the reliable prediction of response to ICI is not possible. In the clinical setting, physicians are not able to predict response to ICI in mUC and to adequately select patients who will benefit. Exploratory analysis of clinical trial data revealed that PD-L1 expression, tumor mutation burden, tumor-infiltrating lymphocytes and gene expression profiles might have some predictive and/or prognostic value in different patient populations.
CONCLUSION: Validated robust biomarkers are still needed to overcome this hurdle to forecast response of ICI in UC patients.
METHODS: A literature search on PubMed, ClinicalTrials.gov and selected annual congress abstracts was conducted in May 2018, using a combination of keywords, medical subject headings (MeSH) terms and free text incorporating urothelial bladder cancer; immunotherapy; immune checkpoint inhibition, biomarkers, PD1/PD-L1.
RESULTS: Although some patients demonstrate complete and/or durable responses under ICI, the reliable prediction of response to ICI is not possible. In the clinical setting, physicians are not able to predict response to ICI in mUC and to adequately select patients who will benefit. Exploratory analysis of clinical trial data revealed that PD-L1 expression, tumor mutation burden, tumor-infiltrating lymphocytes and gene expression profiles might have some predictive and/or prognostic value in different patient populations.
CONCLUSION: Validated robust biomarkers are still needed to overcome this hurdle to forecast response of ICI in UC patients.
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