Abstract
The early clinical symptoms of gastric cancer are not obvious, and metastasis may have occurred at the time of treatment. Poor prognosis is one of the important reasons for the high mortality of gastric cancer. Therefore, the identification of gastric cancer-related genes can be used as relevant markers for diagnosis and treatment to improve diagnosis precision and guide personalized treatment. In order to further reveal the pathogenesis of gastric cancer at the gene level, we proposed a method based on Gradient Boosting Decision Tree (GBDT) to identify the susceptible genes of gastric cancer through gene interaction network. Based on the known genes related to gastric cancer, we collected more genes which can interact with them and constructed a gene interaction network. Random Walk was used to extract network association of each gene and we used GBDT to identify the gastric cancer-related genes. To verify the AUC and AUPR of our algorithm, we implemented 10-fold cross-validation. GBDT achieved AUC as 0.89 and AUPR as 0.81. We selected four other methods to compare with GBDT and found GBDT performed best.
Highlights
There are about 950,000 new cases of gastric cancer worldwide each year, and nearly 700,000 deaths
We compared our method with other methods, such as Support Vector Machine (SVM), Xgboost, Adaboost, and Deep Neural Network (DNN)
Inhibitors targeting vascular endothelial growth factor (VEGF), epidermal growth factor (EGF), and tyrosine kinase have been successfully developed, showing significant curative effects on gastric cancer. This greatly encourages us to study the characteristic markers of recurrence or metastasis of gastric cancer from the perspective of genes
Summary
There are about 950,000 new cases of gastric cancer worldwide each year, and nearly 700,000 deaths. It is one of the most serious tumors (Rawla and Barsouk, 2019). The early clinical symptoms of gastric cancer are not obvious, and metastasis may have occurred at the time of treatment (Axon, 2006). Poor prognosis is one of the important reasons for the high mortality of gastric cancer (Eguchi et al, 2003). Using animal models to screen gastric cancer metastasis-related genes (Wang and Chen, 2002), fully mimic the process of tumor metastasis in vivo, with high metastasis efficiency, clear
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