Network mechanism of opioids in treating abdominal pain caused by T-cell lymphoma

Abstract

Objective: To investigate the therapeutic mechanism of opioids in abdominal pain caused by T-cell lymphoma with a combination of network pharmacology and bioinformatics analysis. Methods: Initially, we collected T-cell lymphoma, abdominal pain, and opioid-related target genes from the Genecards database. The STRING database was then utilized to construct a protein-protein interaction (PPI) network and drug-disease-hub gene-signal pathway diagram was generated using Cytoscape. Furthermore, GO and KEGG enrichment analyses were performed using the bioinformatics website. To validate the results, the predictive hub genes were validated by download data from GEO database, which had been visualized by heatmap and histogram by using R, SPSS, and GraphPad. Results: There were 857 identified cross-targets. PPI revealed 9 hub targets. GO and KEGG analysis focused on PI3K/AKT, MAPK signaling factors, and their interactions. GEO data analysis using SPSS showed upregulation of SRC, MAPK1, HRAS, and AKT1 in tumor tissue. Additionally, SPSS univariate analysis revealed statistical significance in SRC, STAT3, AKT1, and TP53. Conclusions: This study confirms the effectiveness of opioids in preclinical studies on abdominal pain caused by T-cell lymphoma, which is associated with 10 genes. Besides, the involved function and signal pathway is associated with SRC, STAT3, AKT1, and TP53. These findings may contribute to the mechanism explanation of abdominal pain in T-cell lymphoma treated with opioids.