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Bioinformatics Analysis Identifies p53 as a Candidate Prognostic Biomarker for Neuropathic Pain.


ABSTRACT: Neuropathic pain (NP) is a type of chronic pain that is different from the common type of pain. The mechanisms of NP are still poorly understood. Exploring the key genes and neurobiological changes in NP could provide important diagnostic and treatment tools for clinicians. GSE24982 is an mRNA-seq dataset that we downloaded from the Gene Expression Omnibus database to identify key genes in NP. Differentially expressed genes (DEGs) were identified using the BRB-ArrayTools software and R. Functional and pathway enrichment analyses of the DEGs were performed using Metascape. A protein-protein interaction network was created and visualized using Cytoscape. A total of 123 upregulated DEGs were obtained. Among these genes, p53 was the node with the highest degree; hence, we validated it experimentally using a chronic constriction injury mouse model. Our results showed that overexpression of the p53 gene, and the subsequent increase in caspase-3 expression, in dorsal root ganglion neurons led to increased apoptotic changes in these neurons. p53 may therefore be partly responsible for the development of chronic constriction injury-induced NP.

SUBMITTER: Gao Y 

PROVIDER: S-EPMC6127677 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Bioinformatics Analysis Identifies p53 as a Candidate Prognostic Biomarker for Neuropathic Pain.

Gao Yibo Y   Sun Na N   Wang Lieju L   Wu Ying Y   Ma Longfei L   Hong Juncong J   Ren Jinxuan J   Zhu Bin B   Yu Lina L   Yan Min M  

Frontiers in genetics 20180831


Neuropathic pain (NP) is a type of chronic pain that is different from the common type of pain. The mechanisms of NP are still poorly understood. Exploring the key genes and neurobiological changes in NP could provide important diagnostic and treatment tools for clinicians. GSE24982 is an mRNA-seq dataset that we downloaded from the Gene Expression Omnibus database to identify key genes in NP. Differentially expressed genes (DEGs) were identified using the BRB-ArrayTools software and R. Function  ...[more]

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