Predictive Biomarkers for Checkpoint Blockade in Urothelial Cancer: A Systematic Review.

Autor:	Lavoie JM; Department of Medical Oncology, British Columbia Cancer Agency , Vancouver , British Columbia , Canada., Black PC; Department of Urologic Sciences, University of British Columbia , Vancouver , British Columbia , Canada., Eigl BJ; Department of Medical Oncology, British Columbia Cancer Agency , Vancouver , British Columbia , Canada.
Jazyk:	angličtina
Zdroj:	The Journal of urology [J Urol] 2019 Jul; Vol. 202 (1), pp. 49-56. Date of Electronic Publication: 2019 Jun 07.
DOI:	10.1097/JU.0000000000000136
Abstrakt:	Purpose: Immune checkpoint inhibitors have had a major impact on the management of advanced urothelial cancer. Despite the impact only a minority of patients derive benefit. In this context predictive biomarkers which can assist in patient selection are needed. In this systematic review we surveyed the current biomarkers which have been investigated in clinical studies and their potential for patient selection. Materials and Methods: We searched MEDLINE® and EMBASE®, and manually reviewed major meeting abstracts to find studies in humans of immune checkpoint inhibitors given for urothelial cancer that included biomarkers and clinical outcomes. Studies had to provide the correlation between biomarkers and outcomes to be included in analysis. Results published only in abstract form were included since several important biomarker studies have yet to be published. Results: We retrieved 1,236 studies, of which 921 were unique and screened, including 144 which met criteria for full review and 25 were included in the analysis. The manual search yielded 1 additional entry not included in our systematic review for a total of 26 entries. The checkpoint inhibitors used in these studies included atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab and pembrolizumab. The biomarkers tested included PD-L1 immunohistochemistry, molecular subtyping and immune gene expression analysis by RNA sequencing, targeted gene panels for mutations in DNA damage repair genes and estimation of the tumor mutational burden, genomic alterations and the total mutational burden by exome sequencing, analysis of tumor immune infiltrate by immunohistochemistry and T-cell receptor sequencing, and analysis of circulating immune cells and cytokines. Conclusions: No single biomarker has been able to accurately predict the response to immune checkpoint inhibitors. Most studies included only a treatment arm and without a comparator arm it is not possible to ascertain whether biomarkers are predictive or merely prognostic. While PD-L1 immunohistochemistry has been largely unsuccessful, other biomarkers reflecting the immunogenicity of the underlying tumor, the characteristics of the immune infiltrate and the properties of the patient immune system have shown promising data. However, all are in need of validation.
Databáze:	MEDLINE
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