Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.
Genome Innovation Hub, The University of Queensland, Brisbane, QLD, Australia.
Front Immunol. 2022 Jul 29;13:911873. doi: 10.3389/fimmu.2022.911873. eCollection 2022.
The ability to study cancer-immune cell communication across the whole tumor section without tissue dissociation is needed, especially for cancer immunotherapy development, which requires understanding of molecular mechanisms and discovery of more druggable targets. In this work, we assembled and evaluated an integrated experimental framework and analytical process to enable genome-wide scale discovery of ligand-receptors potentially used for cellular crosstalks, followed by targeted validation. We assessed the complementarity of four different technologies: single-cell RNA sequencing and Spatial transcriptomic (measuring over >20,000 genes), RNA Hybridization (RNAscope, measuring 4-12 genes) and Opal Polaris multiplex protein staining (4-9 proteins). To utilize the multimodal data, we implemented existing methods and also developed STRISH (Spatial TRanscriptomic Hybridization), a computational method that can automatically scan across the whole tissue section for local expression of gene (e.g. RNAscope data) and/or protein markers (e.g. Polaris data) to recapitulate an interaction landscape across the whole tissue. We evaluated the approach to discover and validate cell-cell interaction through in-depth analysis of two types of cancer, basal cell carcinoma and squamous cell carcinoma, which account for over 70% of cancer cases. We showed that inference of cell-cell interactions using scRNA-seq data can misdetect or detect false positive interactions. Spatial transcriptomics still suffers from misdetecting lowly expressed ligand-receptor interactions, but reduces false discovery. RNAscope and Polaris are sensitive methods for defining the location of potential ligand receptor interactions, and the STRISH program can determine the probability that local gene co-expression reflects true cell-cell interaction. We expect that the approach described here will be widely applied to discover and validate ligand receptor interaction in different types of solid cancer tumors.
需要能够在不进行组织解离的情况下研究整个肿瘤切片中的癌症-免疫细胞通讯,特别是对于癌症免疫疗法的发展,这需要了解分子机制并发现更多可成药的靶点。在这项工作中,我们组装并评估了一个集成的实验框架和分析流程,以实现配体-受体的全基因组规模发现,用于细胞串扰,随后进行靶向验证。我们评估了四种不同技术的互补性:单细胞 RNA 测序和空间转录组学(测量超过 >20,000 个基因)、RNA 杂交(RNAscope,测量 4-12 个基因)和 Opal Polaris 多聚蛋白染色(4-9 个蛋白)。为了利用多模态数据,我们实施了现有的方法,并且还开发了 STRISH(空间转录组杂交),这是一种计算方法,可以自动扫描整个组织切片,以局部表达基因(例如 RNAscope 数据)和/或蛋白质标记物(例如 Polaris 数据),从而在整个组织中重现相互作用图谱。我们通过深入分析两种类型的癌症(基底细胞癌和鳞状细胞癌)来评估该方法,这两种癌症占癌症病例的 70%以上,来发现和验证细胞-细胞相互作用。我们表明,使用 scRNA-seq 数据推断细胞-细胞相互作用可能会错误检测或检测到假阳性相互作用。空间转录组学仍然存在错误检测低表达配体-受体相互作用的问题,但可以减少假发现。RNAscope 和 Polaris 是定义潜在配体受体相互作用位置的敏感方法,而 STRISH 程序可以确定局部基因共表达反映真实细胞-细胞相互作用的概率。我们预计这里描述的方法将广泛应用于不同类型的实体癌肿瘤中发现和验证配体受体相互作用。