Objective: Elderly patients are prone to postherpetic neuralgia (PHN), which may cause anxiety, depression, and sleep disorders and reduce quality of life. As a result, the life quality of patients was seriously reduced. However, the pathogenesis of PHN has not been fully elucidated, and current treatments remain inadequate. Therefore, it is important to explore the molecular mechanism of PHN.
Methods: We analyzed the GSE64345 dataset, which includes gene expression from the ipsilateral dorsal root ganglia (DRG) of PHN model rats. Differentially expressed genes (DEGs) were identified and analyzed by Gene Ontology. Protein-protein interaction (PPI) network was constructed. The miRNA associated with neuropathic pain and inflammation was found in miRNet. Hub genes were identified and analyzed in Comparative Toxicogenomics Database (CTD). miRNA-mRNA networks associated with PHN were constructed.
Results: A total of 116 genes were up-regulated in the DRG of PHN rats, and 135 genes were down-regulated. Functional analysis revealed that variations were predominantly enriched for genes involved in neuroactive ligand-receptor interactions, the Jak-STAT signaling pathway, and calcium channel activity. Eleven and thirty-one miRNAs associated with neuropathic pain and inflammation, respectively, were found. Eight hub genes (S1PR1, OPRM1, PDYN, CXCL3, S1PR5, TBX5, TNNI3, MYL7, PTGDR2, and FBXW2) associated with PHN were identified.
Conclusions: Bioinformatics analysis is a useful tool to explore the mechanism and pathogenesis of PHN. The identified hub genes may participate in the onset and development of PHN and serve as therapeutic targets.
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http://dx.doi.org/10.1155/2020/1380504 | DOI Listing |
Curr Res Transl Med
January 2025
Department of Hematology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China. Electronic address:
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View Article and Find Full Text PDFOMICS
January 2025
Department of Biotechnology, Brainware University, Barasat, West Bengal, India.
Next-generation cancer phenomics by deployment of multiple molecular endophenotypes coupled with high-throughput analyses of gene expression offer veritable opportunities for triangulation of discovery findings in non-small cell lung cancer (NSCLC) research. This study reports differentially expressed genes in NSCLC using publicly available datasets (GSE18842 and GSE229253), uncovering 130 common genes that may potentially represent crucial molecular signatures of NSCLC. Additionally, network analyses by GeneMANIA and STRING revealed significant coexpression and interaction patterns among these genes, with four notable hub genes-, , and -identified as pivotal in NSCLC progression.
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December 2024
Department of Pharmacy Practice, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu District, Tamilnadu, 603203, India.
Background: Clopidogrel, an antiplatelet drug commonly used in cardiovascular disease, is metabolized by the liver mainly through CYP2C19. Concomitant use of Proton pump inhibitors along with clopidogrel may affect the potency of clopidogrel by CYP2C19 inhibition. However, a novel PPI, ilaprazole is known to differ in its pharmacokinetic features, given the potential differences between ilaprazole's interactions and their metabolism with clopidogrel.
View Article and Find Full Text PDFHeliyon
July 2024
Cancer Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Background: Breast cancer is a highly malignant disease worldwide, but there are currently no sufficient molecular biomarkers to predict patient prognosis and guide radiotherapy. The tumor microenvironment (TME) is an important factor affecting tumor biological function, and changes in its composition are equally relevant to tumor progression and prognosis during radiotherapy.
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Cureus
December 2024
Community Medicine, Siksha 'O' Anusandhan Deemed to be University Institute of Medical Sciences and SUM Hospital, Bhubaneswar, IND.
Gastric cancer (GC) has become a major challenge in oncology research, primarily due to its detection at advanced stages. In this study, we identified and validated the pharmacological mechanisms involved in treating gastric cancer using an integrated approach combining network pharmacology, molecular docking, and a dynamic approach. Gastric cancer-related genes were obtained from DisGeNET, Genecard, and Malacard databases, while potential targets of bioactive compounds were predicted using SwissTargetPrediction.
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