Dapeng Cui, Ming Li*, Runjia Fu, Wei Guo, Jiandong Fei
Gastrointestinal Stromal Tumors (GIST) has the potential for malignant transformation during recurrence and distant metastasis, but the mechanism of metastasis and related gene targets are unknown. In this study, a bioinformatics approach was used to identify potential therapeutic targets for GIST transfer inhibition. Firstly, 761 differentially expressed genes were identified based on the GSE136755 dataset and GSE21315 dataset. Enrichment analysis, protein-protein interaction network, and key gene identification were carried out successively. In addition, tissue specific expression analysis and prediction model construction of key genes were carried out. The results showed that the tissue-specific expression of five key genes (ALB, VEGFA, CDH1, JUN, CXCL8) increased significantly, and the prediction model constructed had a good prediction effect. In conclusion, the identified key genes (ALB, VEGFA, CDH1, JUN, CXCL8) may be used as therapeutic targets to inhibit the malignant progression of GIST.