Identification of Transcriptional Metabolic Dysregulation in Subtypes of Pituitary Adenoma by Integrated Bioinformatics Analysis

Jintao Hu,1,* Huachun Yin,1,2,* Bo Li,2 Hui Yang1 1Department of Neurosurgery, Xinqiao Hospital, The Army Medical University, Chongqing, People’s Republic of China; 2College of Life Sciences, Chongqing Normal University, Chongqing, People’s Republic of China*These authors contrib...

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Autores principales: Hu J, Yin H, Li B, Yang H
Formato: article
Lenguaje:EN
Publicado: Dove Medical Press 2019
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Acceso en línea:https://doaj.org/article/3812d9d842624581b7358be9c1bffda4
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Sumario:Jintao Hu,1,* Huachun Yin,1,2,* Bo Li,2 Hui Yang1 1Department of Neurosurgery, Xinqiao Hospital, The Army Medical University, Chongqing, People’s Republic of China; 2College of Life Sciences, Chongqing Normal University, Chongqing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bo Li; Hui Yang Email libcell@cqnu.edu.cn; huiyangxinqiao@163.com Background: Pituitary adenoma (PA) is a prevalent intracranial tumor. Metabolites differ between pituitary tumor and healthy tissues or among different tumor subtypes. However, the transcriptional changes in metabolic enzymes, which are usually seemed as targets for metabolic therapy, remain unidentified.Methods: Using microarray data for 160 samples from the Gene Expression Omnibus database, across the four most common tumor subtypes, we present the integrated identification of differentially expressed genes (DEGs) between tumors and controls.Results: Subtype-specific DEGs revealed 1081 prolactin tumor-specific DEGs, 437 nonfunctioning tumor-specific DEGs, and 217 common DEGs among the four subtypes. Functional enrichment showed that a lot of biological functions related to metabolism had changed. Twenty-one prolactin and twenty-three nonfunctioning tumor-specific metabolic-related DEGs are mainly involved in fatty acid and nucleotide metabolism, redox reaction, and gluconeogenesis. Eighteen metabolic-related DEGs enriched in the metabolism of xenobiotics by the cytochrome P450 pathway, sulfur metabolism, retinoid metabolism, and glucose homeostasis were abnormal in all subtypes of PA.Conclusion: Based on a comprehensive bioinformatics analysis of the available PA-related transcriptomics data, we identified specific DEGs related to metabolism, and some of them might be new attractive therapeutic targets. Especially, PDK4 and PCK1 might be new attractive biomarkers and therapeutic targets.Keywords: pituitary adenoma, differentially expressed genes, metabolic dysregulation, microarray data, metabolism pathway