Bioinformatic Analysis of Gastrointestinal Stromal Tumor: A Comprehensive Report

Abstract

Abstract Background An increasing number of asymptomatic gastrointestinal stromal tumor (GIST) patients are being identified. The objective of this study was to examine the association between necroptosis-related genes and high-risk GIST, providing data to inform the treatment and follow-up guidelines of asymptomatic patients. Methods The GIST dataset was acquired and by analyzing the dataset of GIST patients in high-risk and low-risk groups, we identified differentially expressed genes (DEGs). We constructed a diagnostic model and used it to analyze the screened DEGs in order to identify key genes involved in GIST. We then constructed mRNA-miRNA and mRNA-TF interaction networks to predict the interaction networks of key genes. We employed immune infiltration analysis to examine the correlation between immune cells and key genes. Results A total of 15 necroptosis-related DEGs were identified by analyzing the datasets of high and low-risk GIST patients. A diagnostic model was developed utilizing five essential genes (CAPN1, DNM1L, H2AFZ, MYC, and UCHL1) for discriminating high-risk and low-risk for GIST. The key gene MYC exhibited the highest level of interaction with miRNA, while the key gene CAPN1 displayed the most interactions with TFs. Immune infiltration analysis showed that the key gene MYC has a significant positive correlation with eosinophils and memory B cells. Conclusion The key genes MYC and CAPN1 may play crucial roles in the progression of GIST disease.