Quantitative Analysis of Proteome in Non-functional Pituitary Adenomas: Clinical Relevance and Potential Benefits for the Patients

Background: Non-functional pituitary adenoma (NFPA) is a common tumor that occurs in the pituitary gland, and generally without any symptoms at its early stage and without clinical elevation of hormones, which is commonly diagnosed when it grows up to compress its surrounding tissues and organs. Currently, the pathogenesis of NFPA has not been clarified yet. It is necessary to investigate molecular alterations in NFPA, and identify reliable biomarkers and drug therapeutic targets for effective treatments. Methods: Tandem mass tags (TMT)-based quantitative proteomics was used to identify and quantify proteins in NFPAs. GO and KEGG enrichment analyses were used to analyze the identified proteins. Differentially expressed genes (DEGs) between NFPA and control tissues were obtained from GEO datasets. These two sets of protein and gene data were analyzed to obtain overlapped molecules (genes; proteins), followed by further GO and KEGG pathway analyses of these overlapped molecules, and molecular network analysis to obtain the hub molecules with Cytoscape. Two hub molecules (SRC and AKT1) were verified with Western blotting. Results: Totally 6076 proteins in NFPA tissues were identified, and 3598 DEGs between NFPA and control tissues were identified from GEO database. Overlapping analysis of 6076 proteins and 3598 DEGs obtained 1088 overlapped molecules (DEGs; proteins). KEGG pathway analysis of 6076 proteins obtained 114 statistically significant pathways, including endocytosis, and spliceosome signaling pathways. KEGG pathway analysis of 1088 overlapped molecules obtained 52 statistically significant pathways, including focal adhesion, cGMP-PKG pathway, and platelet activation signaling pathways. These pathways play important roles in cell energy supply, adhesion, and maintenance of the tumor microenvironment. According to the association degree in Cytoscape, ten hub molecules (DEGs; proteins) were identified, including GAPDH, ALB, ACACA, SRC, ENO2, CALM1, POTEE, HSPA8, DECR1, and AKT1. Western-blotting analysis confirmed the upregulated expressions of SRC and PTMScan experiment confirmed the increased levels of pAKT1, in NFPAs compared to controls. Conclusions: This study established the large-scale quantitative protein profiling of NFPA tissue proteome. It offers a basis for subsequent in-depth proteomics analysis of NFPAs, and insight into the molecular mechanism of NFPAs. It also provided the basic data to discover reliable biomarkers and therapeutic targets for NFPA patients.