文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

通过高多重化成像的视角来描绘实体瘤微环境中的空间细胞-细胞相互作用。

Delineating spatial cell-cell interactions in the solid tumour microenvironment through the lens of highly multiplexed imaging.

机构信息

Department of Integrative Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada.

Department of Biochemistry and Molecular Pharmacology, New York University (NYU) Langone Medical Center, New York, NY, United States.

出版信息

Front Immunol. 2023 Oct 23;14:1275890. doi: 10.3389/fimmu.2023.1275890. eCollection 2023.


DOI:10.3389/fimmu.2023.1275890
PMID:37936700
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10627006/
Abstract

The growth and metastasis of solid tumours is known to be facilitated by the tumour microenvironment (TME), which is composed of a highly diverse collection of cell types that interact and communicate with one another extensively. Many of these interactions involve the immune cell population within the TME, referred to as the tumour immune microenvironment (TIME). These non-cell autonomous interactions exert substantial influence over cell behaviour and contribute to the reprogramming of immune and stromal cells into numerous pro-tumourigenic phenotypes. The study of some of these interactions, such as the PD-1/PD-L1 axis that induces CD8 T cell exhaustion, has led to the development of breakthrough therapeutic advances. Yet many common analyses of the TME either do not retain the spatial data necessary to assess cell-cell interactions, or interrogate few (<10) markers, limiting the capacity for cell phenotyping. Recently developed digital pathology technologies, together with sophisticated bioimage analysis programs, now enable the high-resolution, highly-multiplexed analysis of diverse immune and stromal cell markers within the TME of clinical specimens. In this article, we review the tumour-promoting non-cell autonomous interactions in the TME and their impact on tumour behaviour. We additionally survey commonly used image analysis programs and highly-multiplexed spatial imaging technologies, and we discuss their relative advantages and limitations. The spatial organization of the TME varies enormously between patients, and so leveraging these technologies in future studies to further characterize how non-cell autonomous interactions impact tumour behaviour may inform the personalization of cancer treatment.​.

摘要

肿瘤的生长和转移被认为是由肿瘤微环境(TME)促进的,TME 由高度多样化的细胞类型组成,这些细胞类型之间广泛地相互作用和交流。这些相互作用中的许多涉及到 TME 中的免疫细胞群体,称为肿瘤免疫微环境(TIME)。这些非细胞自主的相互作用对细胞行为产生了巨大的影响,并促使免疫细胞和基质细胞重新编程为许多促进肿瘤发生的表型。对这些相互作用中的一些的研究,例如诱导 CD8 T 细胞耗竭的 PD-1/PD-L1 轴,已经导致了突破性的治疗进展。然而,TME 的许多常见分析要么没有保留评估细胞-细胞相互作用所必需的空间数据,要么只检测很少的(<10)标志物,限制了细胞表型分析的能力。最近开发的数字病理学技术,加上复杂的生物图像分析程序,现在可以在临床标本的 TME 中对多样化的免疫和基质细胞标志物进行高分辨率、高度多重化的分析。在本文中,我们回顾了 TME 中促进肿瘤的非细胞自主相互作用及其对肿瘤行为的影响。我们还调查了常用的图像分析程序和高度多重化的空间成像技术,并讨论了它们的相对优势和局限性。TME 的空间组织在患者之间差异巨大,因此在未来的研究中利用这些技术来进一步描述非细胞自主相互作用如何影响肿瘤行为,可能有助于癌症治疗的个体化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af20/10627006/129c80d2d419/fimmu-14-1275890-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af20/10627006/3a961367a6a0/fimmu-14-1275890-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af20/10627006/32c9759495c1/fimmu-14-1275890-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af20/10627006/e71639eadd51/fimmu-14-1275890-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af20/10627006/129c80d2d419/fimmu-14-1275890-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af20/10627006/3a961367a6a0/fimmu-14-1275890-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af20/10627006/32c9759495c1/fimmu-14-1275890-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af20/10627006/e71639eadd51/fimmu-14-1275890-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af20/10627006/129c80d2d419/fimmu-14-1275890-g004.jpg

相似文献

[1]
Delineating spatial cell-cell interactions in the solid tumour microenvironment through the lens of highly multiplexed imaging.

Front Immunol. 2023

[2]
Tumor microenvironment signaling and therapeutics in cancer progression.

Cancer Commun (Lond). 2023-5

[3]
Identification of a tumour immune barrier in the HCC microenvironment that determines the efficacy of immunotherapy.

J Hepatol. 2023-4

[4]
Mapping the single cell spatial immune landscapes of the melanoma microenvironment.

Clin Exp Metastasis. 2024-8

[5]
Mesenchymal stromal cells (MSCs) and colorectal cancer: a troublesome twosome for the anti-tumour immune response?

Oncotarget. 2016-9-13

[6]
[Characterization of the tumor microenvironment by highly multiplexed microscopy].

Pathologie (Heidelb). 2022-8

[7]
Pro-inflammatory chemokine-chemokine receptor interactions within the Ewing sarcoma microenvironment determine CD8(+) T-lymphocyte infiltration and affect tumour progression.

J Pathol. 2010-12-10

[8]
Nutrient deprivation and hypoxia alter T cell immune checkpoint expression: potential impact for immunotherapy.

J Cancer Res Clin Oncol. 2023-7

[9]
Prognostic impact of CD8-positive tumour-infiltrating lymphocytes and PD-L1 expression in salivary gland cancer.

Oral Oncol. 2020-12

[10]
Identification of distinct immune landscapes using an automated nine-color multiplex immunofluorescence staining panel and image analysis in paraffin tumor tissues.

Sci Rep. 2021-2-25

引用本文的文献

[1]
Towards Post-Genomic Oncology: Embracing Cancer Complexity via Artificial Intelligence, Multi-Targeted Therapeutics, Drug Repurposing, and Innovative Study Designs.

Int J Mol Sci. 2025-8-10

[2]
Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology.

Brief Bioinform. 2024-7-25

本文引用的文献

[1]
Tertiary lymphoid structures predict the prognosis and immunotherapy response of cholangiocarcinoma.

Front Immunol. 2023

[2]
Spatial analysis with SPIAT and spaSim to characterize and simulate tissue microenvironments.

Nat Commun. 2023-5-15

[3]
Different approaches to Imaging Mass Cytometry data analysis.

Bioinform Adv. 2023-4-3

[4]
Dissecting the immune suppressive human prostate tumor microenvironment via integrated single-cell and spatial transcriptomic analyses.

Nat Commun. 2023-2-7

[5]
Single-cell spatial immune landscapes of primary and metastatic brain tumours.

Nature. 2023-2

[6]
Single-cell spatial landscapes of the lung tumour immune microenvironment.

Nature. 2023-2

[7]
Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment.

Nat Genet. 2022-8

[8]
Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell-Cell Interactions That Predict Immunotherapy Response.

Cancer Res. 2022-9-16

[9]
Spatiotemporal co-dependency between macrophages and exhausted CD8 T cells in cancer.

Cancer Cell. 2022-6-13

[10]
Spatial analysis and CD25-expression identify regulatory T cells as predictors of a poor prognosis in colorectal cancer.

Mod Pathol. 2022-9

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索