Proteome of Personalized Tissue-Engineered Veins
收藏NIAID Data Ecosystem2026-05-01 收录
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https://figshare.com/articles/dataset/Proteome_of_Personalized_Tissue-Engineered_Veins/25439415
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资源简介:
Vascular diseases are the largest cause of death globally
and impose
a major global burden on healthcare. The gold standard for treating
vascular diseases is the transplantation of autologous veins, if applicable.
Alternative treatments still suffer from shortcomings, including low
patency, lack of growth potential, the need for repeated intervention,
and a substantial risk of developing infections. The use of a vascular
ECM scaffold reconditioned with the patient’s own cells has
shown successful results in preclinical and clinical studies. In this
study, we have compared the proteomes of personalized tissue-engineered
veins of humans and pigs. By applying tandem mass tag (TMT) labeling
LC/MS-MS, we have investigated the proteome of decellularized (DC)
veins from humans and pigs and reconditioned (RC) DC veins produced
through perfusion with the patient’s whole blood in STEEN solution,
applying the same technology as used in the preclinical studies. The
results revealed high similarity between the proteomes of human and
pig DC and RC veins, including the ECM texture after decellularization
and reconditioning. In addition, functional enrichment analysis showed
similarities in signaling pathways and biological processes involved
in the immune system response. Furthermore, the classification of
proteins involved in immune response activity that were detected in
human and pig RC veins revealed proteins that evoke immunogenic responses,
which may lead to graft rejection, thrombosis, and inflammation. However,
the results from this study imply the initiation of wound healing
rather than an immunogenic response, as both systems share the same
processes, and no immunogenic response was reported in the preclinical
and clinical studies. Finally, our study assessed the application
of STEEN solution in tissue engineering and identified proteins that
may be useful for the prediction of successful transplantations.
创建时间:
2024-03-19



