Grant: Master's Award: Canada Graduate Scholarships

Immune checkpoint blockade therapies have become a first-line treatment for advanced non-small cell lung carcinoma (NSCLC), in which monoclonal antibodies amplify the antitumor immune response through blocking key immunosuppressive signalling molecules like PD-1. However, approximately 40% of patients are resistant to anti-PD-1 treatment. While neoadjuvant administration has improved efficacy, it is difficult to justify this application when resection alone is potentially curative and non-responders risk becoming inoperable should treatment-related surgical delays occur. It is thus imperative that predictive biomarkers for treatment outcome be developed. Tumor expression of PD-1s ligand, PD-L1, is the standard predictive biomarker for outcome of anti-PD-1 monotherapy. However, tumor PD-L1 expression alone has been demonstrated to have little prognostic accuracy in early-stage NSCLC. Approaches that can simultaneously identify immunosuppressive and immune-promoting cell subsets are required to identify new predictive biomarkers.Multiplex immunofluorescence (mIF) allows such nuanced visualization while preserving the spatial relationships between cells in the patient tumor microenvironment (TME). The application of a mIF panel targeted to the PD-1/PD-L1 axis on pre-treatment specimens from a retrospective cohort of patients that had received neoadjuvant anti-PD-1 will relate pathological response to (i) PD-L1 expression on immune cells and its relation to response, (ii) the spatial relationships between PD-1+ and PD-L1+ cells, and (iii) the presence of immunosuppressive cell populations. This analysis of spatial distribution of immune cells and clinical response may identify potential predictive biomarkers and improve treatment selection for resectable NSCLC patients.