Protein-Protein Interaction Network: The Identification of Key Genes and Pathways Involved in Nonfunctioning Pituitary Adenoma Tumorigenesis

Nahid  Safari-Alighiarloo; Seyyed Mohammad  Tabatabaei; Nasibeh  Khayer; Nahid Hashemi  Madani; Mohammad Ebrahim  Khamseh

doi:10.18502/ijdl.v25i6.20858

Nahid Safari-Alighiarloo Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran
Seyyed Mohammad Tabatabaei Medical Informatics Department, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
Nasibeh Khayer Skull Base Research Center, the Five Senses Health Institute, Iran University of Medical Sciences, Tehran, Iran
Nahid Hashemi Madani Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran
Mohammad Ebrahim Khamseh Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran

DOI: https://doi.org/10.18502/ijdl.v25i6.20858

Keywords: Nonfunctioning pituitary adenomas (NFPAs), Transcriptome, Protein-protein interaction (PPI) network, Topology, Clustering

Abstract

Background: Nonfunctioning pituitary adenomas (NFPAs) are among the most prevalent subtypes of pituitaryadenomas, 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 identifykey 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) datacollected from the IntAct database. Cytoscape software, igraph, and MCL packages were used to construct the PPInetwork, analyze its topology, and cluster it.

Results: 1,135 differential genes were identified between NFPAs and normal pituitary samples based on |log2FC|>2 andFDR < 0.05. Of these, 323 were up-regulated and 812 were down-regulated. The constructed PPI network consisted of6,960 nodes and 15,691 edges. According to network clustering, cell cycle regulation, chromatin organization andassembly 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 hubnodes 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 proteininteraction data, can effectively identify pathways and biomarkers in NFPAs tumorigenesis