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Abstract：
With the aim to advance the understanding of immune regulation in MCL and to identify targetable T-cell subsets, we set out to combine image analysis and spatial omic technology focused on both early and late differentiation stages of T cells. MCL patient tissue (n = 102) was explored using image analysis and GeoMx spatial omics profiling of 69 proteins and 1812 mRNAs. Tumor cells, T helper (TH) cells and cytotoxic (TC) cells of early (CD57-) and late (CD57+) differentiation stage were analyzed. An image analysis workflow was developed based on fine-tuned Cellpose models for cell segmentation and classification. TC and CD57+ subsets of T cells were enriched in tumor-rich compared to tumor-sparse regions. Tumor-sparse regions had a higher expression of several key immune suppressive proteins, tentatively controlling T-cell expansion in regions close to the tumor. We revealed that T cells in late differentiation stages (CD57+) are enriched among MCL infiltrating T cells and are predictive of an increased expression of immune suppressive markers. CD47, IDO1 and CTLA-4 were identified as potential targets for patients with T-cell-rich MCL TIME, while GITR might be a feasible target for MCL patients with sparse T-cell infiltration. In subgroups of patients with a high degree of CD57+ TC-cell infiltration, several immune checkpoint inhibitors, including TIGIT, PD-L1 and LAG3 were increased, emphasizing the immune-suppressive features of this highly differentiated T-cell subset not previously described in MCL.
摘要：
为了促进对MCL中免疫调节的理解并鉴定可靶向的T细胞亚群，我们着手将图像分析和空间组学技术结合起来，专注于T细胞的早期和晚期分化阶段。使用69种蛋白质和1812种mRNA的图像分析和GeoMx空间组学分析探索MCL患者组织(n=102)。肿瘤细胞,分析了早期（CD57-）和晚期（CD57）分化阶段的T辅助（TH）细胞和细胞毒性（TC）细胞。基于用于细胞分割和分类的微调Cellpose模型开发了图像分析工作流程。与肿瘤稀疏区域相比，富含肿瘤的T细胞的TC和CD57亚群富集。肿瘤稀疏区的几种关键免疫抑制蛋白表达较高，暂时控制肿瘤附近区域的T细胞扩增。我们发现，晚期分化阶段的T细胞（CD57）在MCL浸润T细胞中富集，并预示着免疫抑制标志物的表达增加。CD47、IDO1和CTLA-4被确定为富含T细胞的MCLTIME患者的潜在目标。而GITR可能是T细胞浸润稀疏的MCL患者的可行靶标。在CD57+TC细胞浸润程度高的患者亚组中，几种免疫检查点抑制剂，包括TIGIT,PD-L1和LAG3增加，强调以前在MCL中未描述的这种高度分化的T细胞亚群的免疫抑制特征。
