Microarray and bioinformatic analysis of conventional ameloblastoma

• Autor(a) principal: Jacinto-Alemán, Luis Fernando
• Data de Publicação: 2022
• Outros Autores: Portilla-Robertson, Javier, Leyva-Huerta, Elba Rosa, Ramírez-Jarquín, Josué Orlando, Villanueva-Sánchez, Francisco Germán
• Tipo de documento: Conjunto de dados
• Título da fonte: SciELO Data
• Texto Completo: https://doi.org/10.48331/scielodata.Z2S8X9
• topic: Medicine, Health and Life Sciences; Ameloblastoma; Computational Biology; Platelet-Derived Growth Factor; Interleukin-2 Receptor alpha Subunit

Ameloblastoma is a highly aggressive odontogenic tumor, and its pathogenesis is associated with multiple participating genes. Objective: Our aim was to identify and validate new critical genes of conventional ameloblastoma using microarray and bioinformatics analysis. Methods: Gene expression microarray and bioinformatic analysis were performed to use 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 analysis that were employed 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.