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An ex vivo tissue model of cartilage degradation suggests that cartilage state can be determined from secreted key protein patterns

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  • Michael Neidlin
  • Efthymia Chantzi
  • George Macheras
  • Mats G Gustafsson
  • Leonidas G Alexopoulos

Abstract

The pathophysiology of osteoarthritis (OA) involves dysregulation of anabolic and catabolic processes associated with a broad panel of proteins that ultimately lead to cartilage degradation. An increased understanding about these protein interactions with systematic in vitro analyses may give new ideas regarding candidates for treatment of OA related cartilage degradation. Therefore, an ex vivo tissue model of cartilage degradation was established by culturing tissue explants with bacterial collagenase II. Responses of healthy and degrading cartilage were analyzed through protein abundance in tissue supernatant with a 26-multiplex protein profiling assay, after exposing the samples to a panel of 55 protein stimulations present in synovial joints of OA patients. Multivariate data analysis including exhaustive pairwise variable subset selection identified the most outstanding changes in measured protein secretions. MMP9 response to stimulation was outstandingly low in degrading cartilage and there were several protein pairs like IFNG and MMP9 that can be used for successful discrimination between degrading and healthy samples. The discovered changes in protein responses seem promising for accurate detection of degrading cartilage. The ex vivo model seems interesting for drug discovery projects related to cartilage degradation, for example when trying to uncover the unknown interactions between secreted proteins in healthy and degrading tissues.

Suggested Citation

  • Michael Neidlin & Efthymia Chantzi & George Macheras & Mats G Gustafsson & Leonidas G Alexopoulos, 2019. "An ex vivo tissue model of cartilage degradation suggests that cartilage state can be determined from secreted key protein patterns," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-17, October.
    • Handle: RePEc:plo:pone00:0224231
    DOI: 10.1371/journal.pone.0224231
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    References listed on IDEAS

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    1. Rebecca R. Andridge & Roderick J. A. Little, 2010. "A Review of Hot Deck Imputation for Survey Non‐response," International Statistical Review, International Statistical Institute, vol. 78(1), pages 40-64, April.
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    1. Efthymia Chantzi & Michael Neidlin & George A Macheras & Leonidas G Alexopoulos & Mats G Gustafsson, 2020. "COMBSecretomics: A pragmatic methodological framework for higher-order drug combination analysis using secretomics," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-18, May.

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