Supplementary Tables S1-S36 from Preexisting Skin-Resident CD8 and Γδ T-cell Circuits Mediate Immune Response in Merkel Cell Carcinoma and Predict Immunotherapy Efficacy

Supplementary Table S1. Patient cohort: Clinical data and assays Supplementary Table S2. Sample cohort: Clinical data and assays Supplementary Table S3. Pre-ICB bulk RNA-seq cohort, 63 samples Supplementary Table S4. Pre-Post ICB matched bulk RNA-seq, 28 samples, 14 patient pairs Supplementary Table S5. Number of reads for each bulk RNA-seq sample (85 samples) Supplementary Table S6. Tissue single-cell RNA-seq quality control and sample metadata (54 samples) Supplementary Table S7. Blood single-cell RNA-seq quality control and sample metadata (55 samples) Supplementary Table S8. Multiplex immunofluorescence sample cohort (44 samples) Supplementary Table S9. GeoMx sample cohort (15 samples) Supplementary Table S10. CosMx sample cohort (13 samples) Supplementary Table S11: Genes differentially expressed between MCC that respond to anti-PD-1/PD-L1 therapy (n=31) and MCC that do not respond to anti-PD-1/PD-L1 therapy (n=32) in the pre-ICB cohort (n=63). Supplementary Table S12. Enrichr results of differentially expressed genes (FDR < 0.1) in responders and non-responders prior to immunotherapy in the bulk RNA-seq dataset Supplementary Table S13. Wilcoxon markers of single-cell RNA-seq clusters for all cells in the tissue dataset Supplementary Table S14. Pseudobulk markers of tumor cells comparing immunotherapy responders to non-responders Supplementary Table S15. GSEA results of differentially expressed genes from responders and non-responders in tumor cells pseudobulk dataset. Supplementary Table S16. SCENIC tumor markers of response and non-response to immunotherapy Supplementary Table S17. Genes in single-cell derived gene signatures Supplementary Table S18. Average antibody derived tag expression for cells in CD8 T cell clusters Supplementary Table S19. Wilcoxon markers of Tcirc and Trm CD8 T cells Supplementary Table S20. Wilcoxon markers of CD8 T cell clusters Supplementary Table S21. TCR clonotype linkage of CD8 T cell clusters Supplementary Table S22. Gini index of each CD8 cluster split by sample Supplementary Table S23. Small T and large T antigens peptide pools for TCR epitope screen Supplementary Table S24. GLIPH2 results of CD8 TCRs Supplementary Table S25. CD8 T cells with TCRs that match public databases with known antigens (VDJdb, McPAS-TCR, TRAdb) Supplementary Table S26. Wilcoxon RNA markers of each cell type, split by δ chain, in the γδ/NK cell subset. Supplementary Table S27. Wilcoxon antibody derived tag markers of each cell type, split by δ chain and cellular source, in the γδ/NK cell subset. Supplementary Table S28. Wilcoxon antibody derived tag markers of δ1 versus δ2 T cells from the tissue dataset Supplementary Table S29. Genes with significant non-linear fits along Vδ1 pseudotime Supplementary Table S30. GeoMx: Differentially expressed genes between responders and non-responders in tumor regions of interest Supplementary Table S31. GeoMx: Differentially expressed genes between responders and non-responders in stroma regions of interest Supplementary Table S32. CosMx: Differentially expressed genes among cell types identified by InSituType. Supplementary Table S33. CosMx: SpatialTime matrices of degree of co-localization between cell types Supplementary Table S34. CellChat receptor ligand interaction with CD8 exhausted T cells (Tex) as targets Supplementary Table S35. Differential expressed genes between bulk RNA-seq samples pre/post immunotherapy treatment split between responders (n=7) and non-responders (n=7) Supplementary Table S36. Enrichr results of differentially expressed genes (FDR <0.1) post-immunotherapy responders in the pre/post matched bulk RNA-seq dataset