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.

皮肤T细胞淋巴瘤（CTCL）虽属罕见，但极具侵袭性，且缺乏有效的治疗方案。尽管部分患者从PD-1阻断疗法中获益，但预测性生物标志物的需求极为迫切。本研究对14名参与培美珠单抗临床试验的晚期CTCL患者中的70个肿瘤区域进行了CODEX多路复用组织成像和RNA测序。我们发现，与未应答者相比，应答者之间在免疫细胞或肿瘤细胞频率上并无差异。然而，我们识别出效应PD-1+ CD4+ T细胞、肿瘤细胞和免疫抑制性Treg之间的空间差异，并据此推导出一个空间生物标志物，称为SpatialScore，该标志物与CTCL中对培美珠单抗的反应密切相关。SpatialScore与肿瘤微环境的免疫功能状态、T细胞功能以及肿瘤细胞特异性的趋化因子募集的差异相一致，并通过一种简化且临床可及的组织成像平台进行了验证。总体而言，这些结果为研究效应和抑制性T细胞活动之间的空间平衡提供了范式，并广泛利用这一生物标志物方法，以指导免疫疗法的临床应用。所有数据框架均源自对接受培美珠单抗治疗的CTCL皮肤活检FFPE组织微阵列的研究：
- Raw_df_CODEX.csv包含标记物表达谱、细胞类型注释、X/Y细胞坐标以及由CODEX识别的所有分割单细胞的细胞邻域分配。
- Raw_df_CODEX_cell_dist.csv包含使用CODEX获得的X/Y细胞坐标以及细胞类型之间的最小距离。
- Raw_df_CSx_tumor.txt包含每个组织微阵列点CIBERSORTx解析的肿瘤细胞基因的表达。
- Raw_df_RNAseq.csv包含每个组织微阵列点转录组中每个基因的比对转录本的原生计数。
- TMA_key.xlsx包含患者ID、组织微阵列点编号、患者治疗组和相应的RNA测序标签。
- Raw_df_Vectra_cell_dist.csv包含使用Vectra获得的X/Y细胞坐标以及细胞类型之间的最小距离。