4.7 Article

Integration of Proteomics and Metabolomics Revealed Metabolite-Protein Networks in ACTH-Secreting Pituitary Adenoma

期刊

FRONTIERS IN ENDOCRINOLOGY
卷 9, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fendo.2018.00678

关键词

metabolite-protein networks; proteomics; metabolomics; ACTH; pituitary adenoma

资金

  1. Research Special Fund for Public Welfare Industry of Health [201402008]
  2. National High Technology Research and Development Program of China [2014AA020610]
  3. Beijing Municipal Administration of Hospitals Youth Program [QML20160506]
  4. National Natural Science Foundation of China [81702455]

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An effective treatment for the management of adrenocorticotropic hormone-secreting pituitary adenomas (ACTH-PA) is currently lacking, although surgery is a treatment option. We have integrated information obtained at the metabolomic and proteomic levels to identify critical networks and signaling pathways that may play important roles in the metabolic regulation of ACTH-PA and therefore hopefully represent potential therapeutic targets. Six ACTH-PAs and seven normal pituitary glands were investigated via gas chromatography-mass spectrometry (GC-MS) analysis for metabolomics. Five ACTH-PAs and five normal pituitary glands were subjected to proteomics analysis via nano liquid chromatography tandem-mass spectrometry (nanoLC-MS/MS). The joint pathway analysis and network analysis was performed using MetaboAnalyst 3.0. software. There were significant differences of metabolites and protein expression levels between the ACTH-PAs and normal pituitary glands. A proteomic analysis identified 417 differentially expressed proteins that were significantly enriched in the Myc signaling pathway. The protein-metabolite joint pathway analysis showed that differentially expressed proteins and metabolites were significantly enriched in glycolysis/gluconeogenesis, pyruvate metabolism, citrate cycle (ICA cycle), and the fatty acid metabolism pathway in ACTH-PA. The protein-metabolite molecular interaction network identified from the metabolomics and proteomics investigation resulted in four subnetworks. Ten nodes in subnetwork 1 were the most significantly enriched in cell amino acid metabolism and pyrimidine nucleotide metabolism. Additionally, the metabolite-gene-disease interaction network established nine subnetworks. Ninety-two nodes in subnetwork 1 were the most significantly enriched in carboxylic acid metabolism and organic acid metabolism. The present study clarified the pathway networks that function in ACTH-PA. Our results demonstrated the presence of downregulated glycolysis and fatty acid synthesis in this tumor type. We also revealed that the Myc signaling pathway significantly participated in the metabolic changes and tumorigenesis of ACTH-PA. This data may provide biomarkers for ACTH-PA diagnosis and monitoring, and could also lead to the development of novel strategies for treating pituitary adenomas.

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