title: Autophagy-related prognostic signature for breast cancer.
abstract: Autophagy is a process that degrades intracellular constituents, such as long-lived or damaged proteins and organelles, to buffer metabolic stress under starvation conditions. Deregulation of autophagy is involved in the progression of cancer. However, the predictive value of autophagy for breast cancer prognosis remains unclear. First, based on gene expression profiling, we found that autophagy genes were implicated in breast cancer. Then, using the Cox proportional hazard regression model, we detected autophagy prognostic signature for breast cancer in a training dataset. We identified a set of eight autophagy genes (BCL2, BIRC5, EIF4EBP1, ERO1L, FOS, GAPDH, ITPR1 and VEGFA) that were significantly associated with overall survival in breast cancer. The eight autophagy genes were assigned as a autophagy-related prognostic signature for breast cancer. Based on the autophagy-related signature, the training dataset GSE21653 could be classified into high-risk and low-risk subgroups with significantly different survival times (HR = 2.72, 95% CI = (1.91, 3.87); P = 1.37 × 10(-5)). Inactivation of autophagy was associated with shortened survival of breast cancer patients. The prognostic value of the autophagy-related signature was confirmed in the testing dataset GSE3494 (HR = 2.12, 95% CI = (1.48, 3.03); P = 1.65 × 10(-3)) and GSE7390 (HR = 1.76, 95% CI = (1.22, 2.54); P = 9.95 × 10(-4)). Further analysis revealed that the prognostic value of the autophagy signature was independent of known clinical prognostic factors, including age, tumor size, grade, estrogen receptor status, progesterone receptor status, ERBB2 status, lymph node status and TP53 mutation status. Finally, we demonstrated that the autophagy signature could also predict distant metastasis-free survival for breast cancer.
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Yunyan
authors.initials: Y
authors.lastname: Gu
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Pengfei
authors.initials: P
authors.lastname: Li
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Fuduan
authors.initials: F
authors.lastname: Peng
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Mengmeng
authors.initials: M
authors.lastname: Zhang
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Pharmacology, Harbin Medical University, Harbin, China.
authors.forename: Haihai
authors.initials: H
authors.lastname: Liang
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Wenyuan
authors.initials: W
authors.lastname: Zhao
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Lishuang
authors.initials: L
authors.lastname: Qi
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Hongwei
authors.initials: H
authors.lastname: Wang
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Chenguang
authors.initials: C
authors.lastname: Wang
authors.affiliation: Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.|Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou, China.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Guo
mesh_terms: D001343:Autophagy; D014408:Biomarkers, Tumor / Q000235:genetics; D001940:Breast / Q000378:metabolism / Q000473:pathology*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D018572:Disease-Free Survival; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008875:Middle Aged; D009154:Mutation; D011379:Prognosis; D016016:Proportional Hazards Models; D016019:Survival Analysis; D016159:Tumor Suppressor Protein p53 / Q000235:genetics
chemical_list: D014408:Biomarkers, Tumor; D016159:Tumor Suppressor Protein p53
keywords: autophagy; breast cancer; gene expression; survival analysis