Molecular Cancer (Sep 2024)

CD16+ as predictive marker for early relapse in aggressive B-NHL/DLBCL patients

  • Sylvia Zöphel,
  • Nadja Küchler,
  • Johanna Jansky,
  • Cora Hoxha,
  • Gertrud Schäfer,
  • Julius J. Weise,
  • Joanne Vialle,
  • Lea Kaschek,
  • Gebhard Stopper,
  • Hermann Eichler,
  • Daniela Yildiz,
  • Alina Moter,
  • Philipp Wendel,
  • Evelyn Ullrich,
  • Claudia Schormann,
  • Torben Rixecker,
  • Onur Cetin,
  • Frank Neumann,
  • Patrick Orth,
  • Moritz Bewarder,
  • Markus Hoth,
  • Lorenz Thurner,
  • Eva C. Schwarz

DOI
https://doi.org/10.1186/s12943-024-02123-7
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 9

Abstract

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Abstract Assessing the prognosis of patients with aggressive non-Hodgkin B cell lymphoma mainly relies on a clinical risk score (IPI). Standard first-line therapies are based on a chemo-immunotherapy with rituximab, which mediates CD16-dependent antibody-dependent cellular cytotoxicity (ADCC). We phenotypically and functionally analyzed blood samples from 46 patients focusing on CD16+ NK cells, CD16+ T cells and CD16+ monocytes. Kaplan-Meier survival curves show a superior progression-free survival (PFS) for patients having more than 1.6% CD16+ T cells (p = 0.02; HR = 0.13 (0.007–0.67)) but an inferior PFS having more than 10.0% CD16+ monocytes (p = 0.0003; HR = 16.0 (3.1-291.9)) at diagnosis. Surprisingly, no correlation with NK cells was found. The increased risk of relapse in the presence of > 10.0% CD16+ monocytes is reversed by the simultaneous occurrence of > 1.6% CD16+ T cells. The unexpectedly strong protective function of CD16+ T cells could be explained by their high antibody-dependent cellular cytotoxicity as quantified by real-time killing assays and single-cell imaging. The combined analysis of CD16+ monocytes (> 10%) and CD16+ T cells (< 1.6%) provided a strong model with a Harrell’s C index of 0.80 and a very strong power of 0.996 even with our sample size of 46 patients. CD16 assessment in the initial blood analysis is thus a precise marker for early relapse prediction. Graphical abstract

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