Objective:To identify independent prognostic genes for the recurrence of invasive breast cancer and construct a risk prediction model for recurrent invasive breast cancer.Method:Public databases were applied to group samples according to angiogenesis-related gene expression using consistent clustering and performed differen-tial analysis.Differential genes were screened by univariate Cox regression and the least absolute shrinkage and se-lection operator(Lasso)regression,and a recurrence risk prediction model for invasive breast cancer was construc-ted by combining the clinical characteristics of the patients with the recurrence-free survival(RFS)as an observa-tional index.Results:13 angiogenesis-based recurrence-independent prognostic genes(PLS3,IGFBP4,CXCL14,HIST1H2BH,EMC9,H2BFS,S100A9,GJA1,NID2,ID3,PDZD2,GRP,FMO1)were identified.The invasive breast cancer recurrence risk prediction model was established in conjunction with patients'TNM stage.Conclusion:The 13-gene recurrence risk prediction model based on angiogenesis has promising predictive performance and can accurately predict the recurrence risk of invasive breast cancer patients.
Invasive breast cancerRecurrenceAngiogenesisPrediction model
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