BioProject

Recent epidemiological studies revealed a significant association between oral squamous cell carcinoma (OSCC) and Porphyromonas gingivalis, a major pathogen of periodontal disease. More...

Recent epidemiological studies revealed a significant association between oral squamous cell carcinoma (OSCC) and Porphyromonas gingivalis, a major pathogen of periodontal disease. As a keystone pathogen, P. gingivalis is known not only to damage local periodontal tissue, but also to evade from the host immune system and eventually affect systemic health. However, its role in OSCC has yet to be well studied. To explore the underlying effect of chronic P. gingivalis infection on OSCC and to identify relevant biomarkers as promising targets for therapy and prevention, we established a novel model by exposing human immortalized oral epithelial cells (HIOECs) to P. gingivalis at a low MOI for 5 to 23 weeks. The P. gingivalis-infected HIOECs were monitored in tumor biological alteration. Bioinformatics analyses were performed on HIOECs infected for 15 weeks, and some selected data were validated by q-PCR and (or) Western blot on cells infected for 15 and 23 weeks. Accordingly, we found that persistent exposure to P. gingivalis induced tumor biological properties on HIOECs. Tumor-related genes such as NNMT, FLI1, GAS6, lncRNA CCAT1, PDCD1LG2 and CD274 were aberrantly expressed in response to long-term exposure of P. gingivalis. In addition, some clinical biomarkers and novel proteins were presented. In conclusion, chronic P. gingivalis infection may be a potential risk factor of OSCC. The key regulators and biomarkers might be used in monitoring OSCC with chronic periodontal infection. We applied lncRNA Microarray (Affymetrix) which could simultaneously detect coding and non-coding genes to explore the differences of cell gene expression after long-term exposure to P. gingivalis. Overall design: Total RNAs of cells without infection and cells infected with P. gingivalis for 15 weeks were extracted and hybridized on Affymetrix microarrays. Less...