Cutaneous squamous cell carcinoma (cSCC), arising from proliferation of malignant epidermal keratinocytes, is the second most common non-melanoma skin cancer. cSCC accounts for 75% of all skin cancer related deaths excluding melanoma, and metastatic and immunotherapy-resistant cases pose an emerging global threat. Tumour development is a gradual process characterized by high mutational burden and an immunosuppressive tumour immune microenvironment (TiME); therefore, identifying the underlying changes across the spatial and temporal landscape of these tumours will be crucial to understanding the key cellular and molecular drivers of disease progression and response.
Methods: In this longitudinal study, we used a single-cell, whole-slide approach to mapping key proteins of immune lineage, tissue architecture, cellular metabolism, and stress to study the spatial landscape of cSCC at baseline (pre-treatment) and multiple time points over the course of immunotherapy with the aim to develop a temporal atlas of the tumor. An ultra-high plex antibody panel encompassing over 50 major determinants in the tumor microenvironment was employed on the PhenoCycler®-Fusion spatial biology platform. Deep bioinformatic analyses was performed to identify cellular phenotypes, spatial neighborhoods, heterogenous functional states and cellular interactions by spatial proximity determinations.
Results: Previous studies in our laboratory have identified unique phenotypes correlating with response and resistance to immunotherapies in pre-treatment cSCC biopsies. Our results expand on these findings with temporal data tracking the dynamic changes in the TiME over the course of immune checkpoint inhibitor therapy. Apart from differences in immune cell composition and spatial localization patterns, we also saw differences in macrophage polarization and expression of metabolic markers in the responder and non-responder cohorts.
Conclusions: Overall, ultrahigh-plex spatio-temporal monitoring of cSCC revealed distinct signatures of response and resistance and identified key features in the TiME that reveal deeper insights into the pathobiology of the tumor. Our discovery-based approach identifies novel biomarkers for patient stratification and therapeutic modulation.