EBioMedicine (Jun 2023)

Immunoscore immune checkpoint using spatial quantitative analysis of CD8 and PD-L1 markers is predictive of the efficacy of anti- PD1/PD-L1 immunotherapy in non-small cell lung cancerResearch in context

  • François Ghiringhelli,
  • Frederic Bibeau,
  • Laurent Greillier,
  • Jean-David Fumet,
  • Alis Ilie,
  • Florence Monville,
  • Caroline Laugé,
  • Aurélie Catteau,
  • Isabelle Boquet,
  • Amine Majdi,
  • Erwan Morgand,
  • Youssef Oulkhouir,
  • Nicolas Brandone,
  • Julien Adam,
  • Thomas Sbarrato,
  • Alboukadel Kassambara,
  • Jacques Fieschi,
  • Stéphane Garcia,
  • Anne Laure Lepage,
  • Pascale Tomasini,
  • Jérôme Galon

Journal volume & issue
Vol. 92
p. 104633

Abstract

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Summary: Background: Anti-PD-1 and PD-L1 antibodies (mAbs) are approved immunotherapy agents to treat metastatic non-small cell lung cancer (NSCLC) patients. Only a minority of patients responds to these treatments and biomarkers predicting response are currently lacking. Methods: Immunoscore-Immune-Checkpoint (Immunoscore-IC), an in vitro diagnostic test, was used on 471 routine single FFPE-slides, and the duplex-immunohistochemistry CD8 and PD-L1 staining was quantified using digital-pathology. Analytical validation was performed on two independent cohorts of 206 NSCLC patients. Quantitative parameters related to cell location, number, proximity and clustering were analysed. The Immunoscore-IC was applied on a first cohort of metastatic NSCLC patients (n = 133), treated with anti-PD1 or anti-PD-L1 mAbs. Another independent cohort (n = 132) served as validation. Findings: Anti-PDL1 clone (HDX3) has similar characteristics as anti-PD-L1 clones (22C3, SP263). Densities of PD-L1+ cells, CD8+ cells and distances between CD8+ and PD-L1+ cells were quantified and the Immunoscore-IC classification was computed. Using univariate Cox model, 5 histological dichotomised variables (CD8 free of PD-L1+ cells, CD8 clusters, CD8 cells in proximity of PD-L1 cells, CD8 density and PD-L1 cells in proximity of CD8 cells) were significantly associated with Progression-Free Survival (PFS) (all P < 0.0001). Immunoscore-IC classification improved the discriminating power of prognostic model, which included clinical variables and pathologist PD-L1 assessment. In two categories, the Immunoscore-IC risk-score was significantly associated with patients’ PFS (HR = 0.39, 95% CI (0.26–0.59), P < 0.0001) and Overall Survival (OS) (HR = 0.42, 95% CI (0.27–0.65), P < 0.0001) in the training-set. Further increased hazard ratios (HR) were found when stratifying patients into three-category Immunoscore-IC (IS-IC). All patients with Low-IS-IC progressed in less than 18 months, whereas PFS at 36 months were 34% and 33% of High-IS-IC patients in the training and validation sets, respectively. Interpretation: Immunoscore-IC is a powerful tool to predict the efficacy of immune-checkpoint inhibitors (ICIs) in patients with NSCLC. Funding: Veracyte, INSERM, Labex Immuno-Oncology, Transcan ERAnet European project, ARC, SIRIC, CARPEM, Ligue Contre le Cancer, ANR, QNRF, INCa France, Louis Jeantet Prize Foundation.

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