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MTFR2, A Potential Biomarker for Prognosis and Immune Infiltrates, Promotes Progression of Gastric Cancer Based on Bioinformatics Analysis and Experiments

Background: Mitochondrial fission regulator 2 (MTFR2) which can promote mitochondrial fission, has recently been reported to be involved in tumorigenesis. However, little is known about its expression levels and function in gastric cancer (GC). This study aims to clarify the role of MTFR2 in GC. Met...

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Detalles Bibliográficos
Autores principales: Zhu, Hai, Wang, Gang, Zhu, Haixing, Xu, Aman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120185/
https://www.ncbi.nlm.nih.gov/pubmed/33995638
http://dx.doi.org/10.7150/jca.58158
Descripción
Sumario:Background: Mitochondrial fission regulator 2 (MTFR2) which can promote mitochondrial fission, has recently been reported to be involved in tumorigenesis. However, little is known about its expression levels and function in gastric cancer (GC). This study aims to clarify the role of MTFR2 in GC. Methods:We firstly determined the expression level and prognostic value of MTFR2 in GC by integrated bioinformatics (Oncomine, GEPIA, Kaplan-Meier Plotter database) and experimental approaches (RT-qPCR, western blot, immunohistochemistry). After constructing stable down-regulated GC cells, the biological functions of MTFR2 in vitro and in vivo were studied through cell clone formation, wound healing, transwell and tumor formation experiments.To understand the reason for the high expression of MTFR2 in GC, copy number alternation, promoter methylation and mutation of MTFR2 were detected by UALCAN and cBioPortal. TargetScanHuman and PROMO databases were also used to explore the miRNAs and transcription factors of MTFR2, and the regulatory network was visualized by Cytoscape. LinkedOmics was used to detect the co-expression profile, and then these co-expressed genes were used for gene oncology function and pathway enrichment analysis to deepen the understanding of MTFR2 mechanism. The protein interaction network of MTFR2 was constructed by the GeneMANIA platform. Docking study of the binding mode was conducted by H DOCK webserver, and PYMOL is used for visualization, and analysis. TIMER database was used to explore the correlation between MTFR2 expression level and immune cells infiltration and gene markers of tumor infiltrating immune cells. Results: We demonstrated that MTFR2 was up-regulated in GC, and its overexpression led to poorer prognosis. MTFR2 downregulation inhibited the proliferation, migration, and invasion of GC cells in vitro and in vivo. By bioinformatics analysis, we identified the possible factors in MTFR2 overexpression. Moreover, function and pathway enrichment analyses found that MTFR2 was involved in chromosome segregation, catalytic activity, cell cycle, and ribonucleic acid transport. A MTFR2-protein interaction network revealed a potential direct protein interaction between MTFR2 and protein kinase adenosine-monophosphate-activated catalytic subunit alpha 1 (PRKAA1), and their potential binding site was predicted in a molecular docking model. In addition, we also found that MTFR2 may be correlated with immune infiltration in GC. Conclusions: Our study has effectively revealed the expression, prognostic value, potential functional networks, protein interactions and immune infiltration of MTFR2 in GC. Altogether, our data identify the possible underlying mechanisms of MTFR2 and suggest that MTFR2 may be a prognostic biomarker and therapeutic target in GC.