Characterizing oral dysplasia immune microenvironment (DIME) using imaging mass cytometry

Introduction

Oral squamous cell carcinoma (OSCC) is the most common neoplasm in the oral and maxillofacial region and is commonly preceded by tissue alterations in the form of oral epithelial dysplasia (OED). OEDs are clinically and histologically heterogeneous, with unique cellular, stromal, and signaling components. The dysplasia immune microenvironment (DIME) and the study of this complex interplay of its various cellular and non-cellular components remain a knowledge gap in the field of OSCC immune-oncology. In our study, we propose a high-throughput multi-dimensional analysis to visualize the complex interactions of the tumor microenvironment in progressing and non-progressing oral epithelial dysplasia. This study highlights the vast potential of multiplex single-cell technology to quantify and understand spatial interactions within the microenvironment as a tool to understand dysplasia progression and oral cancer behaviour.

Materials and Methods

In this retrospective study, we used cytometry time-of-flight (CyTOF) imaging mass cytometry (IMC) to simultaneously examine the expression of 21 protein markers in the DIME including cellular and non-cellular components. We analyzed 11 progressing oral epithelial dysplasia, 11 non-progressing oral epithelial dysplasia, and 9 inflamed mucosa and 2 non-inflamed mucosa controls, resulting in 693 high-dimensional pathology images. Deconvolution, t-SNE, UMAP, cytometry analyses were performed using FlowJo, HistoCat, and ImaCyte.

Results

Qualitative, quantitative, and spatial interactions were characterized in both progressing and non-progressing oral epithelial dysplasias. We found that within progressing and carcinoma groups, there is a reduction in the cytotoxic immune response, and upregulation of inflammatory phenotypes, and stromal markers that promote a favorable microenvironment for cell growth and proliferation.

Conclusion

Our study highlights that spatially resolved, single-cell analysis can characterize pre-malignant and malignant OSCC heterogeneity in cellular architecture and cellular composition, which provides a basis for future studies on how better understanding of the microenvironment can influence disease outcomes.