Research Paper Advance Articles
A glycolysis-related gene expression signature in predicting recurrence of breast cancer
- 1 Department of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- 2 Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China
Received: May 7, 2020 Accepted: July 9, 2020 Published: November 16, 2020https://doi.org/10.18632/aging.103806
How to Cite
Copyright: © 2020 Tang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Metabolic change is the hallmark of cancer. In the present study, we aimed to develop a glycolysis-related gene signature to predict the prognosis of breast cancer patients. Gene expression profiles and clinical data of breast cancer patients were obtained from the GEO database. A four-gene based signature (ALDH2, PRKACB, STMN1 and ZNF292) was developed to separate patients into high-risk and low-risk groups. Patients in the low-risk group had significantly better prognosis than those in the high-risk group. Time-dependent ROC analysis demonstrated that the glycolysis-related gene signature had excellent prognostic accuracy. We further confirmed the expression of the four prognostic genes in breast cancer and paracancerous tissue samples using qRT-PCR analysis. Expression level of PRKACB was higher in paracancerous tissues, while STMN1 and ZNF292 were overexpressed in tumor samples, no significant difference was observed in ALDH2 expression level. Global proteome data of 105 TCGA breast cancer samples obtained from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) were used to evaluate the prognostic value in protein levels. Consistently, high expression level of PRKACB protein was associated with favorable prognosis, while high ZNF292 and STMN1 protein expression levels indicated poor prognosis. The glycolysis-related gene signature might provide an effective prognostic predictor and a new insight for individualize management of breast cancer patients.
TCGA: The Cancer Genome Atlas; GEO: Gene Expression Omnibus; ROC: Receiver operating characteristic; RMA: Robust Multi-array Average; RFS: Relapse-free survival; NSCLC: Non-small cell lung cancer.