RESUMO
Background: Oral squamous cell carcinoma (OSCC) is the most common tumor in the oral cavity. Methicillin-resistant Staphylococcus aureus (MRSA) were highly detected in OSCC patients; however, the interactions and mechanisms between drug-resistant bacteria (MRSA) and OSCC are not clear. Aim: The aim of this study was to investigate the promotion of MRSA on the development of OSCC. Methods: MRSA and MSSA (methicillin-susceptible) strains were employed to investigate the effect on the proliferation of OSCC in vitro and vivo. Results: All of the MRSA strains significantly increased the proliferation of OSCC cells and MRSA arrested the cell cycles of OSCC cells in the S phase. MRSA activated the expression of TLR-4, NF-κB and c-fos in OSCC cells. MRSA also promoted the development of squamous cell carcinoma in vivo. The virulence factor fnbpA gene was significantly upregulated in all MRSA strains. By neutralizing FnBPA, the promotions of MRSA on OSCC cell proliferation and development of squamous cell carcinoma were significantly decreased. Meanwhile, the activation of c-fos and NF-κB by MRSA was also significantly decreased by FnBPA antibody. Conclusion: MRSA promoted development of OSCC, and the FnBPA protein was the critical virulence factor. Targeting virulence factors is a new method to block the interaction between a drug-resistant pathogen and development of tumors.
RESUMO
The application of artificial intelligence in medicine has gradually received attention along with its development. Many studies have shown that machine learning has a wide range of applications in stomatology, especially in the clinical diagnosis and treatment of maxillofacial cysts and tumors. This article reviews the application of machine learning in maxillofacial cyst and tumor to provide a new method for the diagnosis of oral and maxillofacial diseases.