OncoImmunology (Jan 2020)

Close proximity of immune and tumor cells underlies response to anti-PD-1 based therapies in metastatic melanoma patients

  • Tuba N. Gide,
  • Ines P. Silva,
  • Camelia Quek,
  • Tasnia Ahmed,
  • Alexander M. Menzies,
  • Matteo S. Carlino,
  • Robyn P.M. Saw,
  • John F. Thompson,
  • Marcel Batten,
  • Georgina V. Long,
  • Richard A. Scolyer,
  • James S. Wilmott

DOI
https://doi.org/10.1080/2162402X.2019.1659093
Journal volume & issue
Vol. 9, no. 1

Abstract

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Immune checkpoint blockade has greatly improved the clinical outcomes of many patients with metastatic melanoma, however, almost half do not respond. Whether the interspatial distribution of immune and tumor cells predicts response to anti-PD-1-based therapies and patient outcomes in any cancer, including melanoma, is currently unknown. Here, we examined the spatial distribution of immune and tumor cells via multiplex immunofluorescence. Pre-treatment melanoma specimens from 27 patients (n = 18 responders; n = 9 non-responders) treated with anti-PD-1 monotherapy and 34 patients (n = 22 responders; n = 12 non-responders) treated with combined ipilimumab and anti-PD-1 immunotherapy were studied. Responders displayed significantly higher densities of CD8+ tumor-infiltrating lymphocytes within a 20 µM distance from a melanoma cell compared to non-responders in both anti-PD-1 alone (p = .0024) and combination-treated patients (p = .0096), that were associated with improved progression-free survival for both therapies (anti-PD-1 p = .0158; combination therapy p = .0088). In multivariate analysis, the best model for 12-month progression-free survival for anti-PD-1 monotherapy included PD-L1+ cells within proximity to tumor cells and intratumoral CD8+ density (AUC = 0.80), and for combination therapy included CD8+ cells in proximity to tumor cells, intratumoral PD-L1+ density and LDH (AUC = 0.85). Assessment of the spatial distribution of immune cells in relation to tumor cells provides insight into their role in modulating immune response and highlights their potential role as predictors of response to anti-PD-1 based therapies.

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