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Ameloblastoma is a highly aggressive odontogenic tumor, and its pathogenesis is associated with many participating genes. Objective We aimed to identify and validate new critical genes of conventional ameloblastoma using microarray and bioinformatics analysis. Methodology Gene expression microarray and bioinformatic analysis were performed using CHIP H10KA and DAVID software for enrichment. Protein-protein interactions (PPI) were visualized using STRING-Cytoscape with MCODE plugin, followed by Kaplan-Meier and GEPIA analyses that were used for the candidate’s postulation. RT-qPCR and IHC assays were performed to validate the bioinformatic approach. Results 376 upregulated genes were identified. PPI analysis revealed 14 genes that were validated by Kaplan-Meier and GEPIA resulting in PDGFA and IL2RA as candidate genes. The RT-qPCR analysis confirmed their intense expression. Immunohistochemistry analysis showed that PDGFA expression is parenchyma located. Conclusion With bioinformatics methods, we can identify upregulated genes in conventional ameloblastoma, and with RT-qPCR and immunoexpression analysis validate that PDGFA could be a more specific and localized therapeutic target.

Background Periodontal disease is considered one of the most prevalent chronic infectious diseases, often leading to the disruption of tooth-supporting tissues, including alveolar bone, causing tooth mobility and loss. Porphyromonas gingivalis is considered the major etiological agent of this disease, having a plethora of virulence factors, including, lipopolysaccharides (LPS), hemolysins, and proteinases. Antimicrobial peptides are one of the main components of the innate immune response that inhibit the growth of P. gingivalis. The aim of this study was to analyze the antimicrobial activity of cystatin C and to assess the effect on the inflammatory and anti-inflammatory cytokines, the production of reactive oxygen species, and in the release of nitric oxide by human gingival fibroblasts incubated with P. gingivalis in the presence and absence of cystatin C. Methods P. gingivalis ATCC 33277 was exposed to cystatin C for 24h and co-cultured with human gingival fibroblasts (HGFs) ATCC CRL-2014. The effect of cystatin on growth of P. gingivalis and HGFs was evaluated. Pro-inflammatory (TNFα, IL-1β) and anti-inflammatory (IL-10) cytokines were determined by ELISA in the supernatants of HGFs incubated with P. gingivalis exposed to cystatin C. Additionally, nitrites and reactive oxygen species (ROS) production were evaluated. Results Cystatin Cinhibited the growth of P. gingivalis without affecting HGFs. Incubation of HGFs with P. gingivalis led to a significant increase of TNF-α and IL-1β. In contrast, HGFs incubated with P. gingivalis exposed to cystatin C showed a decreased production of both cytokines, whereas IL-10 was enhanced. Incubation of HGFs with P. gingivalis led to an increase of nitric oxide (NO) and ROS production, which was reduced in the presence of the peptide. Conclusions Cystatin C inhibits the growth of P. gingivalis and decreases the inflammatory cytokines, ROS, and NO production during infection of HGFs with P. gingivalis. Knowledge on the antimicrobial and immunomodulatory properties of cystatin C could aid in the design of new therapeutic approaches to facilitate the elimination of this bacterium to improve the treatment of periodontal disease.

Salivary gland neoplasms are a heterogeneous neoplasm group, including mucoepidermoid carcinoma (MECa), adenoid cystic carcinoma (AdCC), and many others. Objective: We aimed to identify new critical genes of MECa and AdCC using bioinformatics analysis. Methods: Gene expression profile of GSE153283 was analyzed by the GEO2R online tool to use the DAVID software for their subsequent enrichment. Protein–protein interactions (PPI) were visualized using String. Cytoscape with MCODE plugin followed by Kaplan–Meier online for overall survival analysis were performed. Results: 97 upregulated genes were identified for MECa and 86 for AdCC. PPI analysis revealed 22 genes for MECa and 63 for AdCC that were validated by Kaplan–Meier that showed FN1 and SPP1 for MECa, and EGF and ERBB2 for AdCC as more significant candidate genes for each neoplasm. Conclusion: With bioinformatics methods, we identify upregulated genes in MECa and AdCC. The resulting candidate genes as possible therapeutic targets were FN1, SPP1, EGF, and ERBB2, and all those genes had been tested as a target in other neoplasm kinds but not salivary gland neoplasm. The bioinformatic evidence is a solid strategy to select them for more extensive research with clinical impact.

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Introduction: Oral epithelial dysplasia (OED) is the presence of cellular and tissue alterations, which may mean a stage prior to the development of cancer. Multiple markers have been considered to estimate its pathogenic potential and evolution to neoplasms, including the p53 molecule, considered as participating in various phenomena of cellular homeostasis. Objective: To determine the relationship between the immunoexpression of p53 DO-7 and PAb 240 with the degree of severity of oral epithelial dysplasia. Material and methods:Nine OED samples were analyzed (three for each degree of severity). The immunoexpression of wild-type p53 (DO-7) and mutated form (PAb 240) was determined through a peroxidase immunohistochemical assay. The mean and standard deviation were obtained, and χ 2 test (p < 0.05) were performed. Results: The mean age was 65.7 ± 11.4 years, with a greater presence of OED in the anatomical area of the lateral side of the tongue. Eight out of nine samples were positive for DO-7 and only two for PAb 240. Conclusions: Our results indicate that, although the expression of p53 DO-7 could be partially related to the pathogenesis of epithelial dysplasia, not all dysplasias presented the mutated form of p53 (PAb 240), which coincides that not all dysplasias have a potential for malignant transformation and that could be related to other oncogenic mechanisms.

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