Huanhuan Hu, Ziheng Yu, Kongjie Lu, Hui Hu, Lang Deng
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引用次数: 0
Abstract
Background: Hypertrophic Cardiomyopathy (HCM) is a complex cardiac disorder marked by the thickening of the heart muscle.
Methods: HCM and normal control cell lines were cultured in DMEM with 12.5% FBS and 1% penicillin-streptomycin at 37°C and 5% CO2. Differentially expressed genes (DEGs) were identified from GSE32453, GSE53408, and GSE113439 datasets using the limma package in R. Hub genes were determined through protein-protein interaction (PPI) network and Cytoscape analysis and validated via Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) and Western blot analysis. Gene enrichment, miRNA predictions, drug prediction, and molecular docking analyses were conducted for functional enrichment and to explore hub gene-associated drugs.
Results: To identify DEGs and hub genes implicated in HCM, we analyzed three Gene Expression Omnibus (GEO) datasets (GSE32453, GSE53404, and GSE1134439), extracting the top 1000 DEGs. Venn analysis revealed 21 common down-regulated genes. PPI analysis identified these six as key hub genes, including Iron Response Element Binding Protein 2 (IREB2), Protein Tyrosine Phosphatase, Non-Receptor Type 11 (PTPN11), IQ Motif Containing GTPase Activating Protein 1 (IQGAP1), Phosphoglucomutase 2 (PGM2), DIS3 RNA Exonuclease 3' to 5' (DIS3), Glutamine-Fructose-6-Phosphate Transaminase 1 (GFPT1) in HCM patients. Gene enrichment analysis highlighted the involvement of these genes in cellular functions such as energy metabolism and growth factor signaling, suggesting their role in the disease's progression. Validation using an additional dataset (GSE36961) confirmed significant down-regulation of all hub genes in HCM samples, supported by Receiver Operating Characteristic (ROC) curve analysis that demonstrated their diagnostic potential. Furthermore, miRNA analysis identified six up-regulated miRNAs (miR-124, miR-29b, miR-330, miR-34a, miR-375, and miR-451) that likely contribute to the dysregulation of these hub genes. Drug prediction analysis identified various potential therapeutic compounds targeting these hub genes. Molecular docking revealed favorable binding affinities, supporting the therapeutic potential of these drugs in modulating hub gene activity.
Discussion: These findings demonstrate that HCM progression involves coordinated downregulation of hub genes and miRNA-mediated dysregulation of metabolic and signaling pathways. The integration of bioinformatics, validation assays, and drug docking suggests a strong translational potential for biomarker discovery and targeted therapy.
Conclusion: Our findings suggest that IREB2, PTPN11, IQGAP1, PGM2, DIS3, and GFPT1 hub genes and their associated regulatory pathways may serve as biomarkers and therapeutic targets for HCM, potentially improving diagnosis and treatment strategies.
期刊介绍:
Current Genomics is a peer-reviewed journal that provides essential reading about the latest and most important developments in genome science and related fields of research. Systems biology, systems modeling, machine learning, network inference, bioinformatics, computational biology, epigenetics, single cell genomics, extracellular vesicles, quantitative biology, and synthetic biology for the study of evolution, development, maintenance, aging and that of human health, human diseases, clinical genomics and precision medicine are topics of particular interest. The journal covers plant genomics. The journal will not consider articles dealing with breeding and livestock.
Current Genomics publishes three types of articles including:
i) Research papers from internationally-recognized experts reporting on new and original data generated at the genome scale level. Position papers dealing with new or challenging methodological approaches, whether experimental or mathematical, are greatly welcome in this section.
ii) Authoritative and comprehensive full-length or mini reviews from widely recognized experts, covering the latest developments in genome science and related fields of research such as systems biology, statistics and machine learning, quantitative biology, and precision medicine. Proposals for mini-hot topics (2-3 review papers) and full hot topics (6-8 review papers) guest edited by internationally-recognized experts are welcome in this section. Hot topic proposals should not contain original data and they should contain articles originating from at least 2 different countries.
iii) Opinion papers from internationally recognized experts addressing contemporary questions and issues in the field of genome science and systems biology and basic and clinical research practices.