PO.TB10.06 · 肿瘤生物学

多组学空间分析揭示胃癌中细胞邻域的独特模式

Multi-omic spatial analysis reveals a distinct pattern of cellular neighborhood in gastric cancer

海报缩略图:多组学空间分析揭示胃癌中细胞邻域的独特模式
编号 810 展板 22 时间 4/19 02:00–05:00 区域 Section 32 主讲 Takashi Semba, MD;PhD
分会场 Spatial Protein Profiling and Multi-Modal Mapping of Tumor and Circulating Ecosystems
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作者与单位 Authors & Affiliations

Takashi Semba, Huaitao Wang, Atsuko Yonemura, Yilin Tong, Takatsugu Ishimoto

Japanese Foundation for Cancer Research, Tokyo, Japan

摘要 Abstract

中文摘要
肿瘤微环境(TME)由多种细胞组成,近期研究提示它们的空间关系可能对细胞功能至关重要。然而,胃癌(GC)TME的空间组织仍知之甚少。在本研究中,我们对来自10例晚期胃癌病例的石蜡块,使用多重免疫组化(IHC)和空间转录组学进行了TME的空间分析。从使用我们近期开发的RePROBE方法获得的30余重IHC图像中,我们基于标志物表达水平将每个细胞标注为成纤维细胞、免疫细胞等。随后,我们基于标注的细胞位置信息进行细胞邻域(CN)分析。这产生了八个不同的CN元簇(meta-clusters)的识别。此外,空间转录组学分析揭示了斑点(spots)内发生的细胞间相互作用。例如,基于配体-受体数据库的细胞间通讯分析显示,在主要由成纤维细胞构成的CN内,与胶原和细胞外基质相关的信号高度活跃。我们还识别出转化生长因子beta(TGF-beta)和丝裂原活化蛋白激酶(MAPK)通路为该活性的驱动通路。此外,当我们使用源自每个CN中差异表达基因的基因特征对来自癌症基因组图谱(The Cancer Genome Atlas)队列的胃癌病例进行评分时,我们发现成纤维细胞主导型CN评分高的病例预后显著较差。此外,基于图的细胞网络分析揭示,淋巴细胞网络形成不良与祖细胞样耗竭CD8 T细胞较少相关,且纤维化的TME可能抑制淋巴细胞网络的形成。这些结果突显了纤维化TME的免疫抑制作用及其作为治疗靶点的潜力。
查看英文原文 English abstract
The tumor microenvironment (TME) consists of diverse cells, and recent studies suggest that their spatial relationships may be crucial for cellular function. However, the spatial organization of the gastric cancer (GC) TME remains poorly understood. In this study, we performed spatial analysis of the GC TME using multiplex immunohistochemistry (IHC) and spatial transcriptomics on paraffin blocks from 10 advanced gastric cancer cases. From more than 30-plex IHC images obtained using the RePROBE method, which we recently developed, we annotated each cell as fibroblasts, immune cells, etc., based on marker expression levels. We then performed cellular neighborhood (CN) analysis based on the annotated cell location information. This resulted in the identification of eight distinct CN meta-clusters. Furthermore, spatial transcriptomics analysis revealed the intercellular interactions occurring within spots. For example, an intercellular communication analysis based on a ligand-receptor database showed that within the CN primarily composed of fibroblasts, signals related to collagen and the extracellular matrix were intensely active. We also identified the transforming growth factor beta (TGF-beta) and mitogen-activated protein kinase (MAPK) pathways as the driving pathways for this activity. Moreover, when we scored gastric cancer cases from The Cancer Genome Atlas cohort using gene signatures derived from differentially expressed genes in each CN, we found that cases with high scores for the fibroblast-dominant CN showed significantly poorer prognosis. In addition, graph-based cell network analysis revealed that poor lymphocyte network formation was associated with fewer progenitor-like exhausted CD8 T cells, and fibrotic TME may inhibit the formation of lymphocyte networks. These results highlight the immunosuppressive role of fibrotic TME and its potential as a therapeutic target.
利益披露 Disclosure
T. Semba, None.. H. Wang, None.. A. Yonemura, None.. Y. Tong, None.. T. Ishimoto, None.

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