Quantitative peripheral live single T-cell dynamic polyfunctionality profiling predicts lung cancer checkpoint immunotherapy treatment response and clinical outcomes.

Background: Predictive biomarkers for immune checkpoint inhibitors (ICIs), e.g., programmed death ligand-1 (PD-L1) tumor proportional score (TPS), remain limited in clinical applications. Predictive biomarkers that require invasive tumor biopsy procedures are practically challenging especially when longitudinal follow-up is required. Clinical utility of tissue-based PD-L1 TPS also becomes diluted when ICI is combined with chemotherapies. Peripheral single T-cell dynamic polyfunctionality profiling offers the opportunity to reveal rare T-cell subpopulations that are polyfunctional and responsible for the underlying ICI treatment molecular response that bulk biological assays cannot achieve. Here, we evaluated a novel live single-cell functional liquid biopsy cytokine profiling platform, IsoLight, as a potential predictive biomarker to track ICI treatment response and clinical outcomes in non-small cell lung cancer (NSCLC).

Methods: Peripheral blood mononuclear cell samples of 10 healthy donors and 10 NSCLC patients undergoing ICI-based therapies were collected longitudinally pre-/post-ICI treatment after ≥2 cycles under institutional review board (IRB)-approved protocols. Cancer blood samples were collected from unresectable advanced stage (III-IV) NSCLC patients. Clinical course and treatment response and survival outcomes were extracted from electronic health records, with treatment response assessed by treating oncologists based on RECIST. CD4 and CD8 T-cells were enriched magnetically and analyzed on the IsoLight platform. Single T-cells were captured in microchambers on IsoCode chips for proteomic immune cytokines profiling. Functional polyfunctionality data from 55,775 single cells were analyzed with IsoSpeak software, 2D- and 3D-t-distributed stochastic neighbor embedding (t-SNE) analysis, kappa coefficient, and Kaplan-Meier survival plots. P values ≤0.05 is considered statistically significant.

Results: Pre-treatment baseline polyfunctionality profiles could not differentiate NSCLC patients from healthy subjects, and could not differentiate ICI responders from non-responders. We found a statistically significant difference between responders and non-responders in CD8 T-cells' changes in overall polyfunctionality (ΔPolyFx) (P=0.01) and polyfunctional strength index (ΔPSI) (P=0.006) in our dynamic pre-/post-treatment single cell measurements, both performing better than PD-L1 TPS alone (P=0.08). In the 3D-t-SNE analysis, subpopulations of post-treatment CD8 T-cells in ICI responders displayed distinct immune cytokine profiles from those in pre-treatment cells. CD8 T-cells ΔPolyFx and ΔPSI scores performed better than PD-L1 TPS in ICI response correlation. Moreover, combined PD-L1 strong TPS and ΔPSI >15 scores strongly correlated with early ICI response with a robust kappa coefficient of 1.0 (P=0.003), which was previously statistically established to indicate a perfect agreement between the prediction and actual response status. Interestingly, high CD4 T-cells ΔPSI >5 was found to correlate with a strong trend of improved progression-free survival (3.9-fold) (10.8 2.8 months; P=0.07) and overall survival (3-fold) (34.5 11.5 months; P=0.09) in ICI-treated patients.

Conclusions: Our study nominates single peripheral T-cell polyfunctionality dynamics analysis to be a promising liquid biopsy platform to determine potential ICI predictive biomarker in NSCLC. It warrants further studies in larger prospective cohorts to validate the clinical utilities and to further optimize cancer immunotherapy.