ILC2-modulated T cell–to-MDSC balance is associated with bladder cancer recurrence
Mathieu F. Chevalier, … , Camilla Jandus, Laurent Derré
Mathieu F. Chevalier, … , Camilla Jandus, Laurent Derré
Published August 1, 2017; First published June 26, 2017
Citation Information: J Clin Invest. 2017;127(8):2916-2929. https://doi.org/10.1172/JCI89717.
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Research Article Immunology Oncology

ILC2-modulated T cell–to-MDSC balance is associated with bladder cancer recurrence

Abstract

Non-muscle–invasive bladder cancer (NMIBC) is a highly recurrent tumor despite intravesical immunotherapy instillation with the bacillus Calmette-Guérin (BCG) vaccine. In a prospective longitudinal study, we took advantage of BCG instillations, which increase local immune infiltration, to characterize immune cell populations in the urine of patients with NMIBC as a surrogate for the bladder tumor microenvironment. We observed an infiltration of neutrophils, T cells, monocytic myeloid-derived suppressor cells (M-MDSCs), and group 2 innate lymphoid cells (ILC2). Notably, patients with a T cell–to-MDSC ratio of less than 1 showed dramatically lower recurrence-free survival than did patients with a ratio of greater than 1. Analysis of early and later time points indicated that this patient dichotomy existed prior to BCG treatment. ILC2 frequency was associated with detectable IL-13 in the urine and correlated with the level of recruited M-MDSCs, which highly expressed IL-13 receptor α1. In vitro, ILC2 were increased and potently expressed IL-13 in the presence of BCG or tumor cells. IL-13 induced the preferential recruitment and suppressive function of monocytes. Thus, the T cell–to-MDSC balance, associated with a skewing toward type 2 immunity, may predict bladder tumor recurrence and influence the mortality of patients with muscle-invasive cancer. Moreover, these results underline the ILC2/IL-13 axis as a targetable pathway to curtail the M-MDSC compartment and improve bladder cancer treatment.

Authors

Mathieu F. Chevalier, Sara Trabanelli, Julien Racle, Bérengère Salomé, Valérie Cesson, Dalila Gharbi, Perrine Bohner, Sonia Domingos-Pereira, Florence Dartiguenave, Anne-Sophie Fritschi, Daniel E. Speiser, Cyrill A. Rentsch, David Gfeller, Patrice Jichlinski, Denise Nardelli-Haefliger, Camilla Jandus, Laurent Derré

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Figure 1

Identification of immune cells infiltrating the urine during BCG therapy.

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Identification of immune cells infiltrating the urine during BCG therapy...
Flow cytometric analysis of urine-infiltrating cells in urine samples obtained from 28 patients with NMIBC during the 6-week intravesical BCG therapy. Urine samples were obtained before and 4 hours after each BCG instillation. Pre-BCG1 data are not shown due to low urine cell content, which is typical at that time point and does not allow for measurement of immune cell subsets in most patients. (A) Samples were gated on live leukocytes and neutrophils (CD15+), and CD3+ T cells (comprising both CD4+ and CD8+ T cells) were assessed. (B and C) The frequencies (mean ± SEM) of both cell subsets in urine are depicted during the follow-up period. (D) When gating on lineage-negative (i.e., CD3–CD56–CD19–) cells, M-MDSCs were identified as CD15–CD14+CD11b+CD33+HLA-DRlo. (E and F) Urine Lin–CD14+CD33+HLA-DRlo and their HLA-DRhi counterpart cells were sorted from 7 urine samples, and mRNA levels of CEBPB, ARG1, and INOS were measured relative to the levels detected in circulating LPS-activated monocytes from HDs (n = 3). Levels (mean ± SEM) of CEBPB are shown for the indicated cell subsets (E) and correlated with ARG1 and INOS mRNA levels (F). A 2-tailed, paired Student’s t test was performed to compare both cell populations, and Spearman’s rank correlation coefficients (R) and the corresponding P values are indicated on each panel in F. Lines indicate linear regression. (G) Frequencies (mean ± SEM) of urine M-MDSCs during the follow-up period. (H) Graphs show the mean (± SEM) of total cell numbers in pre- and post-BCG urine samples and absolute numbers of the indicated cells subsets in post-BCG samples. *P < 0.05, **P < 0.01, and ****P < 0.0001, by 1-way ANOVA, followed by a post test for linear trend to assess longitudinal changes.