In pituitary adenoma (PA), invasiveness is the main cause of recurrence and poor prognosis. Thus, identifying specific biomarkers for diagnosis and effective treatment of invasive PAs is of great clinical significance. In this study, from the Gene Expression Omnibus database, we obtained and combined several microarrays of PA by the "sva" R package. Weighted gene co-expression network analysis was performed to construct a scale-free topology model and analyze the relationships between the modules and clinical traits. Our analysis results indicated that three key modules (dark turquoise, saddle brown, and steel blue) were associated with the invasiveness of PA. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and Gene Ontology analysis were performed for the functional annotation of the key modules. In addition, the hub genes in the three modules were identified and screened by differential expression analysis between normal samples and PA samples. Three upregulated differentially expressed genes (DGAT2, PIGZ, and DHRS2) were identified. The Fisher's exact test and receiver operating characteristic curve were used to validate the capability of these genes to distinguish invasive traits, and transcription factor interaction networks were used to further explore the underlying mechanisms of the three genes. Moreover, a lower expression level of DGAT2 in invasive PA tissue than in noninvasive PA tissue was validated by quantitative reverse transcription-polymerase chain reaction. In general, this study contributes to potential molecular biomarkers of invasive PAs and provides a broader perspective for diagnosis and new therapeutic targets for the invasive PAs.
Keywords: Hub genes; Invasiveness; Pituitary adenoma; Weighted gene co-expression network analysis.