Identification of novel therapeutic targets for neuropathic pain based on gene expression patterns

Neuropathic pain (NP) caused by nerve injury or dysfunction is one of the most challenging neurological diseases. In‐depth study of disease signatures contributes to the development of novel target treatment for NP. In this study, we analyzed expression profiles of qualified NP datasets (GSE24982 and GSE63442) deposited at Gene Expression Omnibus database by systematic bioinformatics approaches. We analyzed the differentially expressed genes of high and low pain compared with normal control group, and between spinal nerve ligation (SNL) injury model and sham‐operation group. A total of 1,243 upregulated and 1,533 downregulated genes were identified in GSE24982, 380 upregulated and 355 downregulated genes were identified in GSE63442. By comparing low‐pain samples with the corresponding sham‐operation group, we identified 457 upregulated and 409 downregulated genes. Overlapping genes were screened out and signaling pathway and expression regulation model analyses were performed. SCN10A and SST were identified as biomarkers for NP. In conclusion, our study showed the expression pattern of gene about NP. These identified biomarkers could serve as potential therapeutic targets for treating NP. We identified 122 differentially expressed genes related to neuropathic pain (NP) using the limma software, based on the Gene Expression Omnibus (GEO) database, and also found two key genes using the enrichment theory of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, of which SCN10A was associated with sensory pain and ion transport, and SST was associated with neuronal cell body and hormone response, etc. Further, our study will be of great theoretical significance in guiding research on the treatment of NP and may provide new targets for better treatment of NP in the future.