Xuanlong Zhang, Xiaoqiong Jiang, Shenjie Song, Kaiyi Du, Hongxin Wang, Zihan Zhang, Yu Wang, Xiangwei Ling, Qingfeng Li
This study demonstrated that the USP4/TNFAIP2 pathway would regulate skin barrier function and ferroptosis via 'M1 macrophages-Tregs axis' in RPSFs. And the skin barrier monitoring technology could serve as reliable method for RPSFs necrosis prediction.
BACKGROUND: Current methods used for assessing random-pattern skin flaps (RPSFs) viability are invasive and subjective. Therefore, this study aimed to establish an accurate and non-invasive method for predicting RPSFs prognosis using skin barrier monitoring technology.
METHODS: Gene ontology (GO) analysis was employed to identify the potential pathways associated with RPSFs necrosis. Skin barrier monitoring technology, immunohistochemistry (IHC), immunofluorescence (IF), and western blotting (WB) were employed to assess skin barrier integrity, quantify ferroptosis level, and evaluate the recruitment of M1 macrophages and regulatory T cells (Tregs). Clinical samples were also included to validate the accuracy and efficacy of skin barrier monitoring technology in predicting RPSFs necrosis.
RESULTS: The necrotic process in RPSFs was characterized by increased infiltration of M1 macrophages and Tregs, accompanied by activated ferroptosis and dysfunction of skin barrier. Notably, Tregs infiltration significantly reduced the necrotic area and restored skin barrier integrity of RPSFs by inhibiting ferroptosis and polarization of M1 macrophages. Mechanistically, USP4 regulated the interaction of M1 macrophages and Tregs (M1 macrophages-Tregs axis) via stabilization of TNFAIP2. Analysis of clinical samples revealed that skin barrier monitoring technology could serve as predictive strategy for RPSFs necrosis.
CONCLUSIONS: This study demonstrated that the USP4/TNFAIP2 pathway would regulate skin barrier function and ferroptosis via 'M1 macrophages-Tregs axis' in RPSFs. And the skin barrier monitoring technology could serve as reliable method for RPSFs necrosis prediction.