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利用 MatriNet 数据库分析癌症细胞外基质网络动力学。

Analysis of extracellular matrix network dynamics in cancer using the MatriNet database.

机构信息

Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu FI-90014, Finland; Faculty of Medicine, University of Oulu, Oulu FI-90014, Finland.

Biostatistics and Epidemiology Platform, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain.

出版信息

Matrix Biol. 2022 Jun;110:141-150. doi: 10.1016/j.matbio.2022.05.006. Epub 2022 May 12.

DOI:10.1016/j.matbio.2022.05.006
PMID:35569692
Abstract

The extracellular matrix (ECM) is a three-dimensional network of proteins of diverse nature, whose interactions are essential to provide tissues with the correct mechanical and biochemical cues they need for proper development and homeostasis. Changes in the quantity of extracellular matrix (ECM) components and their balance within the tumor microenvironment (TME) accompany and fuel all steps of tumor development, growth and metastasis, and a deeper and more systematic understanding of these processes is fundamental for the development of future therapeutic approaches. The wealth of "big data" from numerous sources has enabled gigantic steps forward in the comprehension of the oncogenic process, also impacting on our understanding of ECM changes in the TME. Most of the available studies, however, have not considered the network nature of ECM and the possibility that changes in the quantity of components might be regulated (co-occur) in cancer and significantly "rebound" on the whole network through its connections, fundamentally altering the matrix interactome. To facilitate the exploration of these network-scale effects we have implemented MatriNet (www.matrinet.org), a database enabling the study of structural changes in ECM network architectures as a function of their protein-protein interaction strengths across 20 different tumor types. The use of MatriNet is intuitive and offers new insights into tumor-specific as well as pan-cancer features of ECM networks, facilitating the identification of similarities and differences between cancers as well as the visualization of single-tumor events and the prioritization of ECM targets for further experimental investigations.

摘要

细胞外基质 (ECM) 是一种具有多种性质的蛋白质三维网络,其相互作用对于为组织提供正确的机械和生化线索至关重要,这些线索是组织正常发育和维持所必需的。细胞外基质 (ECM) 成分的数量变化及其在肿瘤微环境 (TME) 中的平衡伴随着并推动了肿瘤发展、生长和转移的所有步骤,对这些过程进行更深入和更系统的理解对于开发未来的治疗方法至关重要。大量来自不同来源的“大数据”使我们在理解致癌过程方面取得了巨大的进展,也影响了我们对 TME 中 ECM 变化的理解。然而,大多数可用的研究并没有考虑 ECM 的网络性质,也没有考虑到数量变化的组件可能在癌症中受到调节(共同发生),并通过其连接对整个网络产生显著的“反弹”,从而从根本上改变基质相互作用组。为了促进对这些网络规模效应的探索,我们实现了 MatriNet(www.matrinet.org),这是一个数据库,能够研究 20 种不同肿瘤类型中 ECM 网络架构的结构变化作为其蛋白质-蛋白质相互作用强度的函数。MatriNet 的使用直观,并为 ECM 网络的肿瘤特异性和泛癌特征提供了新的见解,有助于识别癌症之间的相似性和差异性,以及可视化单个肿瘤事件,并为进一步的实验研究确定 ECM 靶标。

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