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Updated: Jun 27, 2025
Partial Sciatic Nerve Ligation: A Mouse Model of Chronic Neuropathic Pain to Study the Antinociceptive Effect of Novel Therapies
Published on: October 6, 2022
Identification of Key Genes and Pathways in Oxaliplatin-Induced Neuropathic Pain Through Bioinformatic Analysis
Yaling Lou1, Xuting Xu2, Ronghua Wang1
1Department of Clinical Pharmacy, Huzhou Central Hospital (The Fifth School of Clinical Medicine of Zhejiang Chinese Medical University), Huzhou, People's Republic of China.
Background:
The mechanism of Chemotherapy-induced neuropathic pain (NP) remains obscure. This study was aimed to uncover the key genes as well as protein networks that contribute to Oxaliplatin-induced NP.
Material/Methods:
Oxaliplatin frequently results in a type of Chemotherapy-induced NP that is marked by heightened sensitivity to mechanical and cold stimuli, which can lead to intolerance and discontinuation of medication. We investigated whether these different etiologies lead to similar pathological outcomes by targeting shared genetic targets or signaling pathways. Gene expression data were obtained from the Gene Expression Comprehensive Database (GEO) for GSE38038 (representing differential expression in the spinal nerve ligation model rats) and GSE126773 (representing differential expression among the Oxaliplatin-induced NP model rats). Differential gene expression analysis was performed using GEO2R.
Results:
Protein-protein interaction (PPI) analysis identified 260 co-differentially expressed genes (co-DEGs). Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed three shared pathways involved in both models: Kaposi sarcoma-associated herpesvirus (KSHV) infection, Epstein-Barr virus (EBV) infection, and AGE-RAGE signaling pathway in diabetic complications. Further bioinformatics analysis highlighted eight significantly up-regulated genes in the NP group: Mapk14, Icam1, Cd44, IL6, Cxcr4, Stat1, Casp3 and Fgf2. Our results suggest that immune dysfunction, inflammation-related factors or regulating inflammation factors may also be related to Oxaliplatin-induced NP. Additionally, we analyzed a dataset (GSE145222) involving chronic compression of DRGs (CCD) and control groups. CCD model is a classic model for studying NP. We assessed these hub genes' expression levels. In contrast with the control groups, the hub genes were up-regulated in CCD groups, the difference was statistically significant, except Stat1.
Conclusion:
Our research significantly contributes to elucidating the mechanisms underlying the occurrence as well as the progression of Oxaliplatin-induced NP. We have identified crucial genes and signaling pathways associated with this condition.
