Transcription Factor Forkhead Box P (Foxp) 1 Reduces Brain Damage During Cerebral Ischemia-Reperfusion Injury in Mice Through FUN14 Domain-containing Protein 1.

Mitophagy plays a significant role in modulating the activation of pyrin domain-containing protein 3 (NLRP3) inflammasome, which is a major contributor to the inflammatory response that exacerbates cerebral ischemia-reperfusion (I/R) injury. Despite this, the transcriptional regulation mechanism that governs mitophagy remains unclear. This study sought to explore the potential mechanism of Forkhead Box P1 (Foxp1) and its impact on cerebral I/R injury. We investigated the potential neuroprotective role of Foxp1 in cerebral I/R injury by the middle cerebral artery occlusion (MCAO) mouse model. Additionally, we assessed whether FUN14 domain-containing protein 1 (FUNDC1) could rescue the protective effect of Foxp1. Our results showed that overexpression of Foxp1 prevented brain damage during cerebral I/R injury and promoted NLRP3 inflammasome activation, whereas knockdown of Foxp1 had the opposite effect. Notably, Foxp1 overexpression directly promotes FUNDC1 expression, enhanced mitophagy activation, and inhibited the inflammatory response mediated by the NLRP3 inflammasome. Furthermore, we confirmed through chromatin immunoprecipitation (ChIP) and luciferase reporter assays that FUNDC1 is a direct target gene of Foxp1 downstream. Furthermore, the knockdown of FUNDC1 reversed the increased activation of mitophagy and suppressed NLRP3 inflammasome activation induced by Foxp1 overexpression. Collectively, our findings suggest that Foxp1 inhibits NLRP3 inflammasome activation through FUNDC1 to reduce cerebral I/R injury.

Identification of 9-Gene Epithelial-Mesenchymal Transition Related Signature of Osteosarcoma by Integrating Multi Cohorts.

BACKGROUND: The prognosis of patients with osteosarcoma is still poor due to the lack of effective prognostic markers. The EMT (epithelial-mesenchymal transition) serves as a promoter in the progression of osteosarcoma. This study systematically analyzed EMT-related genes to explore new markers for predicting the prognosis of osteosarcoma. METHODS: RNA-Seq data and clinical information were obtained from the GEO database; GSVA and GSEA analysis were used to enrich pathways related to osteosarcoma progression; LASSO method analysis was used to construct the prognosis risk signature. The "Nomogram" package generated the risk prediction nomogram, and its clinical applicability was evaluated by decision curve analysis (DCA). RESULTS: GSVA and GSEA analysis showed that the EMT signaling pathway was closely related to osteosarcoma progression. A 9-genes signature (LAMA3, LGALS1, SGCG, VEGFA, WNT5A, MATN3, ANPEP, FUCA1, and FLNA) was constructed. The overall survival (OS) of the high-risk scores group was significantly lower than the low-risk scores group. The 9-gene signature demonstrated good predictive accuracy. Cox regression analysis showed that the 9-gene signature provided independent prognostic factors for osteosarcoma patients. In addition, the predictive nomogram model could effectively predict the prognosis of osteosarcoma patients. CONCLUSION: This study constructed a 9-gene signature as a new prognostic marker to predict osteosarcoma patients' survival.