In:
BMC Cancer, Springer Science and Business Media LLC, Vol. 22, No. 1 ( 2022-12)
Abstract:
Breast cancer is the most common cancer, and the leading cause of cancer-related deaths, among females world-wide. Recent research suggests that extracellular vesicles (EVs) play a major role in the development of breast cancer metastasis. Axillary lymph node dissection (ALND) is a procedure in patients with known lymph node metastases, and after surgery large amounts of serous fluid are produced from the axilla. The overall aim was to isolate and characterize EVs from axillary serous fluid, and more specifically to determine if potential breast cancer biomarkers could be identified. Methods Lymphatic drain fluid was collected from 7 patients with breast cancer the day after ALND. EVs were isolated using size exclusion chromatography, quantified and detected by nanoparticle tracking analysis, electron microscopy, nano flow cytometry and western blot. The expression of 37 EV surface proteins was evaluated by flow cytometry using the MACSPlex Exosome kit. Results Lymphatic drainage exudate retrieved after surgery from all 7 patients contained EVs. The isolated EVs were positive for the typical EV markers CD9, CD63, CD81 and Flotillin-1 while albumin was absent, indicating low contamination from blood proteins. In total, 24 different EV surface proteins were detected. Eleven of those proteins were detected in all patients, including the common EV markers CD9, CD63 and CD81, cancer-related markers CD24, CD29, CD44 and CD146, platelet markers CD41b, CD42a and CD62p as well as HLA-DR/DP/DQ. Furthermore, CD29 and CD146 were enriched in Her2+ patients compared to patients with Her2- tumors. Conclusions Lymphatic drainage exudate retrieved from breast cancer patients after surgery contains EVs that can be isolated using SEC isolation. The EVs have several cancer-related markers including CD24, CD29, CD44 and CD146, proteins of potential interest as biomarkers as well as to increase the understanding of the mechanisms of cancer biology.
Type of Medium:
Online Resource
ISSN:
1471-2407
DOI:
10.1186/s12885-021-08870-w
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2022
detail.hit.zdb_id:
2041352-X
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