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计算免疫突触分析揭示了不同肿瘤微环境中的T细胞相互作用。

Computational immune synapse analysis reveals T-cell interactions in distinct tumor microenvironments.

作者信息

Wang Victor, Liu Zichao, Martinek Jan, Zhou Jie, Boruchov Hannah, Ray Kelly, Palucka Karolina, Chuang Jeffrey

机构信息

National Institutes of Health.

1The Jackson Laboratory for Genomic Medicine.

出版信息

Res Sq. 2023 Jun 1:rs.3.rs-2968528. doi: 10.21203/rs.3.rs-2968528/v1.

Abstract

The tumor microenvironment (TME) and the cellular interactions within it can be critical to tumor progression and treatment response. Although technologies to generate multiplex images of the TME are advancing, the many ways in which TME imaging data can be mined to elucidate cellular interactions are only beginning to be realized. Here, we present a novel approach for multipronged computational immune synapse analysis (CISA) that reveals T-cell synaptic interactions from multiplex images. CISA enables automated discovery and quantification of immune synapse interactions based on the localization of proteins on cell membranes. We first demonstrate the ability of CISA to detect T-cell:APC (antigen presenting cell) synaptic interactions in two independent human melanoma imaging mass cytometry (IMC) tissue microarray datasets. We then generate melanoma histocytometry whole slide images and verify that CISA can detect similar interactions across data modalities. Interestingly, CISA histoctyometry analysis also reveals that T-cell:macrophage synapse formation is associated with T-cell proliferation. We next show the generality of CISA by extending it to breast cancer IMC images, finding that CISA quantifications of T-cell:B-cell synapses are predictive of improved patient survival. Our work demonstrates the biological and clinical significance of spatially resolving cell-cell synaptic interactions in the TME and provides a robust method to do so across imaging modalities and cancer types.

摘要

肿瘤微环境(TME)及其内部的细胞相互作用对肿瘤进展和治疗反应可能至关重要。尽管生成TME多重图像的技术不断进步,但挖掘TME成像数据以阐明细胞相互作用的多种方式才刚刚开始被认识到。在这里,我们提出了一种新的多管齐下的计算免疫突触分析(CISA)方法,该方法可从多重图像中揭示T细胞突触相互作用。CISA能够基于细胞膜上蛋白质的定位自动发现和量化免疫突触相互作用。我们首先展示了CISA在两个独立的人类黑色素瘤成像质谱细胞术(IMC)组织微阵列数据集中检测T细胞与抗原呈递细胞(APC)突触相互作用的能力。然后,我们生成黑色素瘤组织细胞计数全玻片图像,并验证CISA可以跨数据模式检测类似的相互作用。有趣的是,CISA组织细胞计数分析还表明,T细胞与巨噬细胞突触的形成与T细胞增殖有关。接下来,我们通过将CISA扩展到乳腺癌IMC图像来展示其通用性,发现CISA对T细胞与B细胞突触的量化可预测患者生存率的提高。我们的工作证明了在TME中空间解析细胞间突触相互作用的生物学和临床意义,并提供了一种跨成像模式和癌症类型进行此操作的强大方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/912a/10312981/db6e306e9b64/nihpp-rs2968528v1-f0001.jpg

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