Abstract
Objectives: A minority of NSCLC patients benefit from anti-PD1 immune checkpoint inhibitors. A rational combination of biomarkers is needed. The objective was to determine the predictive value of tumor mutational load (TML), CD8+ T cell infiltration, HLA class-I and PD-L1 expression in the tumor. Materials and methods: Metastatic NSCLC patients were prospectively included in an immune-monitoring trial (NTR7015) between April 2016-August 2017, retrospectively analyzed in FFPE tissue for TML (NGS: 409 cancer-related-genes) and by IHC staining to score PD-L1, CD8+ T cell infiltration, HLA class-I. PFS (RECISTv1.1) and OS were analyzed by Kaplan–Meier methodology. Results: 30 patients with adenocarcinoma (67%) or squamous cell carcinoma (33%) were included. High TML was associated with better PFS (p = 0.004) and OS (p = 0.025). Interaction analyses revealed that patients with both high TML and high total CD8+ T cell infiltrate (p = 0.023) or no loss of HLA class-I (p = 0.026), patients with high total CD8+ T cell infiltrate and no loss of HLA class-I (p = 0.041) or patients with both high PD-L1 and high TML (p = 0.003) or no loss of HLA class-I (p = 0.032) were significantly associated with better PFS. Unsupervised cluster analysis based on these markers revealed three sub-clusters, of which cluster-1A was overrepresented by patients with progressive disease (15 out of 16), with significant effect on PFS (p = 0.007). Conclusion: This proof-of-concept study suggests that a combination of PD-L1 expression, TML, CD8+ T cell infiltration and HLA class-I functions as a better predictive biomarker for response to anti-PD-1 immunotherapy. Consequently, refinement of this set of biomarkers and validation in a larger set of patients is warranted.
| Original language | English |
|---|---|
| Pages (from-to) | 771-777 |
| Number of pages | 7 |
| Journal | Cancer Immunology, Immunotherapy |
| Volume | 69 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 1 May 2020 |
Bibliographical note
Funding Information:The authors thank Annemarie van Schadewijk (Leiden University Medical Center, Leiden, The Netherlands) for help with the IHC analysis and Wesley van de Geer (Erasmus University Medical Center, Rotterdam, The Netherlands) for support with the cluster analysis.
Funding Information:
This study was supported by an unrestricted grant from the Zabawas Foundation (J. Smit and P.S. Hiemstra) and an investigator-initiated study grant from Bristol-Myers Squibb (J.H. von der Thüsen, study identification number: OT123-361). Acknowledgements
Publisher Copyright:
© 2020, The Author(s).