Materials Today BioBiophysicsPeer-reviewed journal article
Breast cancer cell-derived extracellular vesicles accelerate collagen fibrillogenesis and integrate into the matrix
Abstract
Extracellular vesicles (EVs) within the extracellular matrix (ECM) are often studied as passive elements whose diffusion and behaviour are subject to the composition and structure of the ECM. While EV diffusion and distribution in tissues are indeed governed by matrix interactions, accumulating evidence suggests that EVs contain much of the cellular machinery required for actively remodeling ECM. Using rheology and confocal reflectance microscopy, we investigate the gelation of collagen I hydrogels formed in the presence of EVs, and show that EVs can play an active role in ECM formation. EVs appear to nucleate new fibrils, recruiting collagen molecules from solution and accelerating their polymerization. Trypsinization of EVs shows that collagen-EV interactions are primarily mediated by surface proteins. The use of extruded plasma membrane vesicles shows that membrane composition determines final fibril length and matrix structure. EVs also become integrated into the fibril structures that they help form, reminiscent of matrix vesicles found in situ within tissues. This represents a plausible way by which EVs are deposited into the ECM, becoming signaling cues for resident cells. Our data show that EV-matrix interactions are dynamic and can contribute to the remodeling of tissue microenvironments. SignificanceExtracellular vesicles (EVs) are nanoscale membrane structures known for their role in facilitating cellto-cell trafficking of proteins, lipids, RNA, and other signaling molecules. In this report, we show that EVs derived from breast cancer cells are not merely passive messengers, but also direct active effectors of extracellular matrix (ECM) remodeling processes. Bulk rheology and confocal microscopy show that these EVs have the ability to nucleate new collagen fibrils and accelerate the formation of dense fibrillar collagenous networks. This has important implications in cancer pathology, where matrix density is often associated with worse disease outcomes, but could also potentially be exploitable in future tissue engineering applications.
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- 2
- FWCI
- 1.48
- Field percentile
- top 27%
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