Tumor immune microenvironment in non-muscle-invasive urothelial carcinoma of the bladder.


Journal

Human pathology
ISSN: 1532-8392
Titre abrégé: Hum Pathol
Pays: United States
ID NLM: 9421547

Informations de publication

Date de publication:
07 2019
Historique:
received: 11 03 2019
revised: 09 04 2019
accepted: 14 04 2019
pubmed: 27 4 2019
medline: 27 5 2020
entrez: 27 4 2019
Statut: ppublish

Résumé

Immunotherapy has gained significance in a variety of tumor types including advanced urothelial carcinoma. Noninvasive urothelial lesions have been treated with intravesical Bacillus-Calmette-Guerin (BCG) for decades. Given treatment failure in a subset of these tumors, ongoing clinical trials investigating the role of checkpoint inhibitors are actively pursued in this group of patients. The present study aims to delineate PD-L1, CD8, and FOXP3 expression in tumor microenvironment in non-muscle-invasive urothelial carcinoma samples obtained via sequential biopsies and to assess its potential role in predicting disease outcome. Cases with >1% and> 5% PD-L1 expression in tumor cells showed lower relative risk (RR) to recur at any subsequent biopsy compared with those with lower PD-L1 expression (RRs, 0.83 [P = .009] and 0.81 [P = .03], respectively). Cases with higher expression of FOXP3 in peritumoral lymphocytes were at lower risk for tumor grade progression at any biopsy (RR, 0.2; P = .02). Tumors with FOXP3/CD8 expression ratio of >1 in intratumoral lymphocytes had lower risk of grade progression (RR, 0.28; P = .04). Although higher number of FOXP3-, CD8-, and PD-L1-positive lymphocytes were encountered after BCG treatment, the findings did not reach statistical significance. In patients without BCG treatment, PD-L1 expression in tumor cells and peritumoral lymphocytes varied across serial biopsies, suggesting the need for additional approaches to assess eligibility for immunotherapy in non-muscle-invasive urothelial carcinoma patients.

Identifiants

pubmed: 31026471
pii: S0046-8177(19)30068-1
doi: 10.1016/j.humpath.2019.04.003
pii:
doi:

Substances chimiques

B7-H1 Antigen 0
Biomarkers, Tumor 0
CD274 protein, human 0
FOXP3 protein, human 0
Forkhead Transcription Factors 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

24-32

Informations de copyright

Copyright © 2019 Elsevier Inc. All rights reserved.

Auteurs

Marie-Lisa Eich (ML)

Department of Pathology, The University of Alabama at Birmingham, Birmingham, AL 35249, USA.

Alcides Chaux (A)

Department of Scientific Research, School of Postgraduate Studies, Norte University, 1614 Asunción, Paraguay.

Gunes Guner (G)

Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.

Diana Taheri (D)

Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.

Maria Angélica Mendoza Rodriguez (MA)

Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.

Maria Del Carmen Rodriguez Peña (MDC)

Department of Pathology, The University of Alabama at Birmingham, Birmingham, AL 35249, USA.

Alexander S Baras (AS)

Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.

Noah M Hahn (NM)

Department of Urology, Johns Hopkins University, Baltimore, MD 21231, USA; Department of Oncology, Johns Hopkins University, Baltimore, MD 21231, USA.

Charles Drake (C)

Department of Urology, Johns Hopkins University, Baltimore, MD 21231, USA; Department of Oncology, Johns Hopkins University, Baltimore, MD 21231, USA.

Rajni Sharma (R)

Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.

Trinity J Bivalacqua (TJ)

Department of Urology, Johns Hopkins University, Baltimore, MD 21231, USA; Department of Oncology, Johns Hopkins University, Baltimore, MD 21231, USA.

Katayoon Rezaei (K)

Department of Pathology, George Washington University, Washington, DC 20037, USA.

George J Netto (GJ)

Department of Pathology, The University of Alabama at Birmingham, Birmingham, AL 35249, USA. Electronic address: gnetto@uabmc.edu.

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Classifications MeSH