A bioinformatics-based approach and expression assay for identification of dysregulated genes in pituitary adenoma.

ABSTRACT

Non-functioning pituitary adenomas (NFPAs) are a group of pituitary neuroendocrine tumors that are associated with morbidity. The exact pathophysiological process leading to this pathology is not known. Nerve growth factor (NGF) is a neurotropic factor that might be involved in this process. We used bioinformatics tools to analyze expression of genes in NFPA samples. Our analyses led to identification of NGF-related genes, namely ARC, ID1, and SH3GL3 - as well as one long non-coding RNA (lncRNA) called myocardial infarction associated transcript (MIAT). Then, we assessed their expression in NFPAs and their adjacent non-cancerous samples. While expression levels of SH3GL3 and MIAT were different between NFPA samples and control samples, expressions of ARC and ID1 were not meaningfully different between these two groups of specimens. SH3GL3 was over-expressed in NFPA samples compared with control samples (expression ratio (95% CI)= 8.22 (1.51-44.6), P value= 0.03). Similarly, expression of MIAT was higher in NFPAs compared with controls (expression ratio (95% CI)= 7.7 (1.7-33.6), P value= 0.009). Taken together, we validated the bioinformatics results regarding the expression of SH3GL3 and MIAT. This study provides a deeper understanding of the involvement of these genes in the pituitary tumorigenesis.