Track

Clinical Studies

Abstract

Merkel Cell Carcinoma (MCC) is a rare, aggressive skin cancer that can be driven by Merkel Cell polyomavirus or UV light exposure. The introduction of immune checkpoint blockade (ICB) has transformed MCC treatment with response rates of 50–70% in advanced disease. However, significant variability exists in patient responses, with some experiencing durable remissions while others exhibit primary resistance or early progression. Our objective was to identify cellular and molecular correlates of ICB-response. To this end we collected pre-treatment FFPE tissue samples from ten patients with advanced MCC that were treated at the University Medical Center Mainz. Single-nucleus RNA sequencing data (snRNA-seq) were processed with standard normalization and scaling. Expression-based clustering was performed utilizing the Louvain algorithm on principal components to identify transcriptionally similar cell populations. We aimed to identify distinct T cell populations (CD4⁺, CD8⁺, Regulatory T cells, etc.) using canonical T cell markers. We identified 5 distinct T cell populations: Naive CD4⁺ T cells, Memory CD8⁺ T cells, Exhausted CD8⁺ T cells, Regulatory T cells (Tregs), and Effector CD8⁺ T cells. Analysis revealed distinct T cell population patterns between immunotherapy responders and non-responders. Naive CD4⁺ T cells were enriched in responders, while exhausted CD8⁺ T cells and Tregs were enriched in non-responders. However, the small sample size (n=5 per group) limited the statistical power for definitive conclusions. This preliminary analysis identifies specific T cell subpopulations driving immunotherapy response in MCC patients. Validation of this experiment with larger cohorts is needed to confirm these findings and establish clinical significance.