Abstract
Capsular contracture (CC) is one of the most common postoperative complications associated with breast implant-associated infections. The mechanisms that lead to CC remain poorly understood. Plasma is an ideal biospecimen for early proteomics biomarker discovery. However, as high-abundance proteins mask signals from low-abundance proteins, identifying novel or specific proteins as biomarkers for a particular disease has been hampered. Here, we employed depletion of high-abundance plasma proteins followed by Tandem Mass Tag (TMT)-based quantitative proteomics to compare 10 healthy control patients against 10 breast implant CC patients. A total of 450 proteins were identified from these samples. Among them, 16 proteins were significantly differentially expressed in which 5 proteins were upregulated and 11 downregulated in breast implant CC patients compared to healthy controls. Gene Ontology enrichment analysis revealed that proteins related to cell, cellular processes and catalytic activity were highest in the cellular component, biological process, and molecular function categories, respectively. Further, pathway analysis revealed that inflammatory responses, focal adhesion, platelet activation, and complement and coagulation cascades were enriched pathways. The differentially abundant proteins from TMT-based quantitative proteomics have the potential to provide important information for future mechanistic studies and in the development of breast implant CC biomarkers.
| Original language | English |
|---|---|
| Article number | 22 |
| Pages (from-to) | 1-17 |
| Number of pages | 17 |
| Journal | Proteomes |
| Volume | 12 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 6 Aug 2024 |
Bibliographical note
Copyright the Author(s) 2024. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- breast implants
- capsular contracture
- human plasma
- Tandem Mass Tags
- mass spectrometry
- proteomics
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