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空间转录组学揭示了不同且保守的肿瘤核心和边缘结构,这些结构可预测患者的生存和靶向治疗反应。

Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response.

机构信息

Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.

出版信息

Nat Commun. 2023 Aug 18;14(1):5029. doi: 10.1038/s41467-023-40271-4.

Abstract

The spatial organization of the tumor microenvironment has a profound impact on biology and therapy response. Here, we perform an integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize malignant cells in tumor core (TC) and leading edge (LE) transcriptional architectures. We show that the TC and LE are characterized by unique transcriptional profiles, neighboring cellular compositions, and ligand-receptor interactions. We demonstrate that the gene expression profile associated with the LE is conserved across different cancers while the TC is tissue specific, highlighting common mechanisms underlying tumor progression and invasion. Additionally, we find our LE gene signature is associated with worse clinical outcomes while TC gene signature is associated with improved prognosis across multiple cancer types. Finally, using an in silico modeling approach, we describe spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response. Our work provides pan-cancer insights into TC and LE biology and interactive spatial atlases ( http://www.pboselab.ca/spatial_OSCC/ ; http://www.pboselab.ca/dynamo_OSCC/ ) that can be foundational for developing novel targeted therapies.

摘要

肿瘤微环境的空间组织对生物学和治疗反应有深远的影响。在这里,我们对 HPV 阴性口腔鳞状细胞癌(OSCC)进行了综合的单细胞和空间转录组学分析,全面描述了肿瘤核心(TC)和前沿(LE)中恶性细胞的转录结构。我们表明,TC 和 LE 具有独特的转录谱、相邻的细胞组成和配体-受体相互作用。我们证明,与 LE 相关的基因表达谱在不同癌症中是保守的,而 TC 则是组织特异性的,突出了肿瘤进展和侵袭的共同机制。此外,我们发现我们的 LE 基因特征与更差的临床结果相关,而 TC 基因特征与多种癌症类型的改善预后相关。最后,我们使用一种计算建模方法,描述了 OSCC 中细胞发育的空间调节模式,这些模式与药物反应有可预测的关联。我们的工作为 TC 和 LE 生物学以及交互式空间图谱(http://www.pboselab.ca/spatial_OSCC/; http://www.pboselab.ca/dynamo_OSCC/)提供了泛癌症的见解,可为开发新的靶向治疗方法奠定基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a54/10439131/3414fc3915d8/41467_2023_40271_Fig1_HTML.jpg

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