University of Oulu

Kontio, Juho, et al. “Analysis of Extracellular Matrix Network Dynamics in Cancer Using the MatriNet Database.” Matrix Biology, vol. 110, June 2022, pp. 141–50. (Crossref),

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

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Author: Kontio, Juho1,2; Soñora, Valeria Rolle3; Pesola, Vilma1;
Organizations: 1Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu FI-90014, Finland
2Faculty of Medicine, University of Oulu, Oulu FI-90014, Finland
3Biostatistics and Epidemiology Platform, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
4Dpto. de Bioquímica y Biología Molecular, IUOPA-Universidad de Oviedo, Oviedo 33006, Spain
5Foundation for the Finnish Cancer Institute, Tukholmankatu 8, Helsinki, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
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Language: English
Published: Elsevier, 2022
Publish Date: 2022-10-03


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 (, 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.

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Series: Matrix biology
ISSN: 0945-053X
ISSN-E: 1569-1802
ISSN-L: 0945-053X
Volume: 110
Pages: 141 - 150
DOI: 10.1016/j.matbio.2022.05.006
Type of Publication: A1 Journal article – refereed
Field of Science: 1182 Biochemistry, cell and molecular biology
Funding: Authors would like to thank Monica Bassignana ( for designing the MatriNet logo and helping with Fig. 1. This research is connected to the DigiHealth-project, a strategic profiling project at the University of Oulu. The project is supported by the Academy of Finland (project number 326291), the University of Oulu, and the Finnish Cancer Institute, K. Albin Johansson Cancer Research Fellowship fund.
Dataset Reference: All pre-processing and analytical procedures are open access and available at
Copyright information: © 2022 The Author(s). This is an open access article under the CC BY license (