Volume 25, Issue 6 (1-2026)
ijdld 2026, 25(6): 535-543 |
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Safari-Alighiarloo N, Tabatabaei S M, Khayer N, Hashemi Madani N, Khamseh M E. Protein-Protein Interaction Network: The Identification of Key Genes and Pathways Involved in Nonfunctioning Pituitary Adenoma Tumorigenesis. ijdld 2026; 25 (6) :535-543
URL: http://ijdld.tums.ac.ir/article-1-6481-en.html
URL: http://ijdld.tums.ac.ir/article-1-6481-en.html
Nahid Safari-Alighiarloo *1 
, Seyyed Mohammad Tabatabaei2 , Nasibeh Khayer3 , Nahid Hashemi Madani4 , Mohammad E. Khamseh4
, Seyyed Mohammad Tabatabaei2 , Nasibeh Khayer3 , Nahid Hashemi Madani4 , Mohammad E. Khamseh4
1- Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran , safari.n@iums.ac.ir
2- Medical Informatics Department, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
3- Skull Base Research Center, The Five Senses Health Institute, Iran University of Medical Sciences, Tehran, Iran
4- Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran
2- Medical Informatics Department, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
3- Skull Base Research Center, The Five Senses Health Institute, Iran University of Medical Sciences, Tehran, Iran
4- Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran
Abstract: (373 Views)
Background: Nonfunctioning pituitary adenomas (NFPAs) are among the most prevalent subtypes of pituitary adenomas, presenting no clinical hormone elevation. The lack of definitive biomarkers for prognosis and treatment, combined with a significant risk of recurrence, poses substantial challenges to management. This study aims to identify key genes and biological pathways involved in NFPAs tumorigenesis using a systems biology approach.
Methods: The dataset with accession number GSE26966 was analyzed to identify differentially expressed genes (DEGs) in NFPAs. Interactions between DEGs at the protein level were constructed using protein-protein interaction (PPI) data collected from the IntAct database. Cytoscape software, igraph, and MCL packages were used to construct the PPI network, analyze its topology, and cluster it.
Results: 1,135 differential genes were identified between NFPAs and normal pituitary samples based on |log2FC|>2 and FDR < 0.05. Of these, 323 were up-regulated and 812 were down-regulated. The constructed PPI network consisted of 6,960 nodes and 15,691 edges. According to network clustering, cell cycle regulation, chromatin organization and assembly regulation, transcription regulation, and actin cytoskeleton regulation were the most significant pathways. Using topological analysis, CDKN1A, BHLHE40, FHL2, H1-2, H2BC21, and FGFR3 were identified as central hub nodes in the PPI network. These genes were also involved in the biological pathways mentioned above.
Conclusion: This study demonstrated that a systems biology approach, integrating gene transcriptome data with protein interaction data, can effectively identify pathways and biomarkers in NFPAs tumorigenesis.
Methods: The dataset with accession number GSE26966 was analyzed to identify differentially expressed genes (DEGs) in NFPAs. Interactions between DEGs at the protein level were constructed using protein-protein interaction (PPI) data collected from the IntAct database. Cytoscape software, igraph, and MCL packages were used to construct the PPI network, analyze its topology, and cluster it.
Results: 1,135 differential genes were identified between NFPAs and normal pituitary samples based on |log2FC|>2 and FDR < 0.05. Of these, 323 were up-regulated and 812 were down-regulated. The constructed PPI network consisted of 6,960 nodes and 15,691 edges. According to network clustering, cell cycle regulation, chromatin organization and assembly regulation, transcription regulation, and actin cytoskeleton regulation were the most significant pathways. Using topological analysis, CDKN1A, BHLHE40, FHL2, H1-2, H2BC21, and FGFR3 were identified as central hub nodes in the PPI network. These genes were also involved in the biological pathways mentioned above.
Conclusion: This study demonstrated that a systems biology approach, integrating gene transcriptome data with protein interaction data, can effectively identify pathways and biomarkers in NFPAs tumorigenesis.
Keywords: Nonfunctioning pituitary adenomas (NFPAs), Transcriptome, Protein-protein interaction (PPI) network, Topology, Clustering
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