Ghiringhelli F, Bibeau F, Greillier L, Fumet JD, Ilie A, Monville F, Laugé C, Catteau A, Boquet I, Majdi A, Morgand E, Oulkhouir Y, Brandone N, Adam J, Sbarrato T, Kassambara A, Fieschi J, Garcia S, Lepage AL, Tomasini P, Galon J. 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 cancer. EBioMedicine. 2023. Download the PDF
Summary of the Study
Immune checkpoint inhibitors (ICIs) such as anti-PD-1 and anti-PD-L1 monoclonal antibodies have revolutionized NSCLC treatment, but predictive biomarkers remain limited.
This study applied Immunoscore-IC, a spatially resolved immunohistochemistry-based test combining CD8 and PD-L1 staining quantified by digital pathology. The analysis involved:
- 471 formalin-fixed paraffin-embedded slides
- Two independent validation cohorts (206 patients total)
- CD8+ and PD-L1+ cell densities, spatial relationships, and proximity metrics
Key findings
- A 5-variable risk model using spatial metrics (e.g., clustering, proximity) was significantly associated with Progression-Free Survival (PFS) and Overall Survival (OS) (all P < 0.0001)
- Immunoscore-IC classification outperformed pathologist-assessed PD-L1 scoring
- All Low IS-IC patients progressed within 18 months
- High IS-IC patients had ~34% PFS at 36 months in both training and validation cohorts
Conclusion
Immunoscore-IC is a validated, powerful, and spatially informed prognostic tool for NSCLC patients treated with ICIs.
This work introduces a powerful stratification method for NSCLC using spatial immune profiling and quantitative histology.
In this study, the statistical analysis and survival modeling, including multivariable Cox models and risk stratification, were performed by Alboukadel Kassambara, contributing directly to the development and validation of the Immunoscore-IC prognostic classification.
Citation
Publication: In EBioMedicine
Date: May 25, 2023
Type: Journal Article
PDF: Download the PDF
Scientific Contributions
Here are more scientific abstracts authored or co-authored by Alboukadel Kassambara. These contributions span computational biology, bioinformatics, biostatistics, machine learning, and multi-omics, with a focus on immuno-oncology and translational research.
