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Biomarkers Associated with Beneficial PD-1 Checkpoint Blockade in Non-Small Cell Lung Cancer (NSCLC) Identified Using
Jon Zugazagoitia1, Swati Gupta2, Yuting Liu2
1Department of Pathology, Yale University School of Medicine, New Haven, Connecticut. jonzuga@gmail.com.
Purpose:
Only a minority of patients with advanced non-small cell lung cancer (NSCLC) truly benefits from single-agent PD-1 checkpoint blockade, and more robust predictive biomarkers are needed.
Experimental Design:
We assessed tumor samples from 67 immunotherapy-treated NSCLC cases represented in a tissue microarray, 53 of whom had pretreatment samples and received monotherapy. Using GeoMx Digital Spatial Profiling System (NanoString Technologies), we quantified 39 immune parameters simultaneously in four tissue compartments defined by fluorescence colocalization [tumor (panCK+), leucocytes (CD45+), macrophages (CD68+), and nonimmune stroma].
Results:
A total of 156 protein variables were generated per case. In the univariate unadjusted analysis, we found 18 markers associated with outcome in spatial context, five of which remained significant after multiplicity adjustment. In the multivariate analysis, high levels of CD56 and CD4 measured in the CD45 compartment were the only markers that were predictive for all clinical outcomes, including progression-free survival (PFS, HR: 0.24, P = 0.006; and HR: 0.31, P = 0.011, respectively), and overall survival (OS, HR: 0.26, P = 0.014; and HR: 0.23, P = 0.007, respectively). Then, using an orthogonal method based on multiplex immunofluorescence and cell counting (inForm), we validated that high CD56+ immune cell counts in the stroma were associated with PFS and OS in the same cohort.
Conclusions:
This pilot scale discovery study shows the potential of the digital spatial profiling technology in the identification of spatially informed biomarkers of response to PD-1 checkpoint blockade in NSCLC. We identified a number of relevant candidate immune predictors in spatial context that deserve validation in larger independent cohorts.
Insights
Predictive biomarkers for PD-1 blockade in non-small cell lung cancer (NSCLC) are needed. High CD56 and CD4 immune cells in the tumor microenvironment predict better progression-free and overall survival in NSCLC patients treated with PD-1 inhibitors.
Area of Science:
- Immunology
- Oncology
- Biomarker Discovery
Background:
- A minority of advanced non-small cell lung cancer (NSCLC) patients benefit from PD-1 checkpoint blockade.
- There is a critical need for robust predictive biomarkers to guide treatment decisions.
Purpose of the Study:
- To identify spatially informed immune biomarkers predictive of response to PD-1 checkpoint blockade in NSCLC.
- To evaluate the utility of digital spatial profiling for biomarker discovery in NSCLC.
Main Methods:
- Assessed tumor samples from 67 NSCLC patients treated with immunotherapy using GeoMx Digital Spatial Profiling.
- Quantified 39 immune parameters across four tissue compartments (tumor, leukocytes, macrophages, stroma).
- Validated candidate biomarkers using multiplex immunofluorescence and cell counting.
Main Results:
- Multivariate analysis identified high CD56 and CD4 levels within the CD45+ compartment as significant predictors of progression-free survival (PFS) and overall survival (OS).
- High CD56+ immune cell counts in the stroma were validated as associated with improved PFS and OS.
- 18 initially identified markers showed association with outcome in spatial context, with five remaining significant after adjustment.
Conclusions:
- Digital spatial profiling shows promise for identifying spatially informed biomarkers for PD-1 blockade response in NSCLC.
- High CD56 and CD4 immune cell levels in specific tumor microenvironment compartments are potential predictive biomarkers for NSCLC immunotherapy.
- Further validation in larger cohorts is warranted for these candidate immune predictors.
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