Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1)

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

Julkaisun tekijät: Kontio J, Sonora VR, Pesola V, Lamba R, Dittmann A, Navarro AD, Koivunen J, Pihlajaniemi T, Izzi V

Kustantaja: ELSEVIER

Julkaisuvuosi: 2022

Journal: Matrix Biology

Tietokannassa oleva lehden nimi: MATRIX BIOLOGY

Lehden akronyymi: MATRIX BIOL

Volyymi: 110

Aloitussivu: 141

Lopetussivun numero: 150

Sivujen määrä: 10

ISSN: 0945-053X


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 (cooccur) 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. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (

Last updated on 2022-01-12 at 11:43