Immune cell topography predicts response to PD-1 blockade in cutaneous T cell lymphoma
Cutaneous T cell lymphomas (CTCL) are rare but aggressive cancers without effective treatments. While a subset of patients derive benefit from PD-1 blockade, there is a critically unmet need for predictive biomarkers of response. Herein, we perform CODEX multiplexed tissue imaging and RNA sequencing on 70 tumor regions from 14 advanced CTCL patients enrolled in a pembrolizumab clinical trial. We find no differences in the frequencies of immune or tumor cells between responders and non-responders. Instead, we identify topographical differences between effector PD-1+ CD4+ T cells, tumor cells, and immunosuppressive Tregs, from which we derive a spatial biomarker, termed the SpatialScore, that correlates strongly with pembrolizumab response in CTCL. The SpatialScore coincides with differences in the functional immune state of the tumor microenvironment, T cell function, and tumor cell-specific chemokine recruitment and was validated using a simplified, clinically accessible tissue imaging platform. Collectively, these results provide a paradigm for investigating the spatial balance of effector and suppressive T cell activity and broadly leveraging this biomarker approach to inform the clinical use of immunotherapies. All data frames are derived from studies on the FFPE tissue microarray of CTCL skin biopsies from patients treated with pembrolizumab: - Raw_df_CODEX.csv contains marker expression profiles, cell types annotations, X/Y cell coordinates, and cellular neighborhood assignments for all segmented single-cells identified by CODEX. - Raw_df_CODEX_cell_dist.csv contains X/Y cell coordinates and minimal distances between the cell-types obtained with CODEX. - Raw_df_CSx_tumor.txt contains the gene expression of CIBERSORTx-resolved tumor cell genes per tissue microarray spot (reference TMA_key.xlsx). - Raw_df_RNAseq.csv contains the raw counts of aligned transcripts for every gene in the transcriptome per tissue microarray spot (reference TMA_key.xlsx). - TMA_key.xlsx contains the patient ID, tissue microarray spot number, patient treatment group, and corresponding RNAseq label. - Raw_df_Vectra_cell_dist.csv contains X/Y cell coordinates and minimal distances between cell-types obtained with Vectra.
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These data frames were generated from the original CODEX imaging data (ImmunoAtlas, https://immunoatlas.org/NOLN/210920-1) and RNAseq data (GEO database, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE162137). They were processed and analyzed as described in the manuscript.