Immune checkpoint inhibition (ICI) has transformed the possibilities of cancer treatment by boosting anti-cancer immunity. Its clinical use has been particularly successful in metastatic Merkel Cell Carcinoma (MCC), one of the rarest but deadliest skin cancers. Nevertheless, only half of patients respond to treatment, and many develop resistance. MCC, often caused by viral integration into the host genome, is highly immunogenic and, thus, a good model for studying cancer-immune interactions. Furthermore, the specificity of anti-tumor T and B cells is often directed against these tumor-expressed viral antigens. Identifying cells reactive to these antigens thus allows us to clearly identify tumor-specific T and B cells, which is much more difficult in other cancer types. In order to characterize the tumor-reactive cells and their spatial context within tumors, we are employing the Spatial VDJ method. This method enables the sequence analysis of the variable regions of TCR and Ig genes in the spatial context of 10x Visium spatial transcriptomics. We will thus be able to predict which regions on MCC tumor sections are enriched for T and B cells specific to viral antigens and the transcriptomic patterns characterizing these regions. We will also investigate the differences between samples from ICI-responding and ICI-resistant patients. We will support this analysis with published single-cell and bulk TCR-seq and RNA-seq data from MCC patients. By identifying the tumor-reactive immune cells in their spatial context, we hope to elucidate the conditions in which these cells are active and propose determinants for ICI response and resistance in MCC.