Anti-SERPINA1 monoclonal antibody

Background: There exists considerable evidence conforming that autophagy may play an important role in the biological process of breast cancer. This study aimed to construct and evaluate a novel autophagy-related gene signature as a potential prognostic factor and therapeutic target in breast cancer patients based on high-throughput sequencing datasets. Materials & methods: Autophagy-related genes obtained from the Human Autophagy Database and high-sequencing data obtained from The Cancer Genome Atlas (TCGA) were analyzed to identify differential expressed genes (DEGs) between tumor and normal tissues. Then GO and KEGG analysis were performed to explore potential biological and pathological functions of DEGs. Autophagy-related prognostic genes were identified by univariate COX regression analysis. Subsequently stepwise model selection using the Alkaike information criterion (AIC) and multivariate COX regression model was performed to construct autophagy-related gene signature. Then patients were divided into high- and low-risk groups based on the risk score identified by the autophagy-related gene signature. Multivariate COX regression model and stratification analysis were used to specify the prognostic value of this gene signature in whole cohort and various subgroups. T-test and ANOVA analysis were used to compare the expression differences of continuous variables (5 prognostic genes and risk score) in binary and multiple category groups respectively. Kaplan-Meier analysis, log-rank tests and the area under receiver operating characteristic (ROC) curve (AUC) were conducted to validate the accuracy and precise of the autophagy-related gene signature based on GSE20685 and GSE21653 datasets. Results: We profiled autophagy-related DEGs in normal and breast tumor tissues. GO and KEGG analysis indicated that autophagy-related DEGs might participate in breast cancer occurrence, development and drug resistance. Then we identified five autophagy-related genes (EIF4EBP1, ATG4A, BAG1, MAP1LC3A and SERPINA1) that had significantly prognostic values for breast cancer. Autophagy-related gene signature was constructed and patients were divided into highand lowrisk groups based on their risk score. Patients in the high-risk group tended to have shorter overall survival (OS) and relapse-free survival (RFS) times than those in the low-risk group (OS: HR = 1.620, 95%CIs: 1.345-1.950; P < 0.001; RFS: HR = 1.487, 95%CIs: 1.248-1.771, P < 0.001). Autophagy-related gene signature had significant prognostic value in stratified subgroups especially in advanced breast cancer subgroups (T3-4; N2-3; stage III-IV). Its prognostic value was further confirmed in two GEO validation datasets (GSE20685: P = 6.795e-03; GSE21653: P = 1.383e-03). Finally, association analysis between clinicopathological factors and gene signature showed the risk score was higher in patients with ER/PR negative, higher clinical stage or T stage (P < 0.01). Conclusion: We established and confirmed a novel autophagy-related gene signature for patients with breast cancer that had independent survival prognostic value especially in advanced breast cancer subgroups. Our research might promote the molecular mechanism study of autophagy-related genes in breast cancer.