RESUMEN
Radicular pain, a common and complex form of neuropathic pain, presents significant challenges in treatment. Acupuncture, a therapy originating from ancient traditional Chinese medicine and widely utilized for various pain types, including radicular pain, has shown promising outcomes in the management of lumbar radicular pain, cervical radicular pain, and radicular pain due to spinal stenosis. Despite its efficacy, the exact mechanisms through which acupuncture achieves analgesia are not fully elucidated and are the subject of ongoing research. This review sheds light on the current understanding of the analgesic mechanisms of acupuncture for radicular pain, offering valuable perspectives for both clinical application and basic scientific research. Acupuncture is postulated to relieve radicular pain by several mechanisms: peripherally, it reduces muscle spasms, lessens mechanical pressure on nerve roots, and improves microcirculation; at the molecular level, it inhibits the HMGB1/RAGE and TLR4/NF-κB signaling pathways, thereby decreasing the release of pro-inflammatory cytokines; within the spinal cord, it influences synaptic plasticity; and centrally, it modulates brain function, particularly affecting the medial prefrontal cortex, anterior cingulate cortex, and thalamus within the default mode network. By acting across these diverse biological domains, acupuncture presents an effective treatment modality for radicular pain, and deepening our understanding of the underlying mechanisms regarding analgesia for radicular pain is crucial for enhancing its clinical efficacy and advancement in pain management.
RESUMEN
BACKGROUND: Gastric cancer (GC) has a high mortality rate worldwide. Despite significant progress in GC diagnosis and treatment, the prognosis for affected patients still remains unfavorable. AIM: To identify important candidate genes related to the development of GC and identify potential pathogenic mechanisms through comprehensive bioinformatics analysis. METHODS: The Gene Expression Omnibus database was used to obtain the GSE183136 dataset, which includes a total of 135 GC samples. The limma package in R software was employed to identify differentially expressed genes (DEGs). Thereafter, enrichment analyses of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed for the gene modules using the clusterProfile package in R software. The protein-protein interaction (PPI) networks of target genes were constructed using STRING and visualized by Cytoscape software. The common hub genes that emerged in the cohort of DEGs that was retrieved from the GEPIA database were then screened using a Venn Diagram. The expression levels of these overlapping genes in stomach adenocarcinoma samples and non-tumor samples and their association with prognosis in GC patients were also obtained from the GEPIA database and Kaplan-Meier curves. Moreover, real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting were performed to determine the mRNA and protein levels of glutamic-pyruvic transaminase (GPT) in GC and normal immortalized cell lines. In addition, cell viability, cell cycle distribution, migration and invasion were evaluated by cell counting kit-8, flow cytometry and transwell assays. Furthermore, we also conducted a retrospective analysis on 70 GC patients diagnosed and surgically treated in Wenzhou Central Hospital, Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University between January 2017 to December 2020. The tumor and adjacent normal samples were collected from the patients to determine the potential association between the expression level of GPT and the clinical as well as pathological features of GC patients. RESULTS: We selected 19214 genes from the GSE183136 dataset, among which there were 250 downregulated genes and 401 upregulated genes in the tumor samples of stage III-IV in comparison to those in tumor samples of stage I-II with a P-value < 0.05. In addition, GO and KEGG results revealed that the various upregulated DEGs were mainly enriched in plasma membrane and neuroactive ligand-receptor interaction, whereas the downregulated DEGs were primarily enriched in cytosol and pancreatic secretion, vascular smooth muscle contraction and biosynthesis of the different cofactors. Furthermore, PPI networks were constructed based on the various upregulated and downregulated genes, and there were a total 15 upregulated and 10 downregulated hub genes. After a comprehensive analysis, several hub genes, including runt-related transcription factor 2 (RUNX2), salmonella pathogenicity island 1 (SPI1), lysyl oxidase (LOX), fibrillin 1 (FBN1) and GPT, displayed prognostic values. Interestingly, it was observed that GPT was downregulated in GC cells and its upregulation could suppress the malignant phenotypes of GC cells. Furthermore, the expression level of GPT was found to be associated with age, lymph node metastasis, pathological staging and distant metastasis (P < 0.05). CONCLUSION: RUNX2, SPI1, LOX, FBN1 and GPT were identified key hub genes in GC by bioinformatics analysis. GPT was significantly associated with the prognosis of GC, and its upregulation can effectively inhibit the proliferative, migrative and invasive capabilities of GC cells.