Abstract
Accumulative evidence confirms that glycolysis and long non-coding RNAs (lncRNAs) are closely associated with tumor development. The aim of this study was to construct a novel prognostic model based on glycolysis-related lncRNAs (GRLs) in breast cancer patients. By performing Pearson correlation analysis and Lasso regression analysis on differentially expressed genes and lncRNAs associated with glycolysis in the Cancer Genome Atlas (TCGA) and Gene Set Enrichment Analysis (GSEA) datasets, we identified nine GRLs and constructed associated prognostic risk signature. Kaplan-Meier survival analysis and univariate and multivariate Cox analysis showed that patients in the low-risk group had a better prognosis. The receiver operator characteristics (ROC) curves showed that the area under the curve (AUC) of the prognostic risk signature predicting patients' overall survival at 1-, 3- and 5- years was 0.78, 0.71, and 0.71, respectively. Moreover, the validation curves also showed that the signature had better diagnostic efficacy and clinical predictive power. Furthermore, clone formation assay, EdU assay, and Transwell assay showed that knockdown of LINC01070 inhibited breast cancer progression. We developed a prognostic risk-associated GRLs signature that can accurately predict the breast cancer patient's prognostic status, and LINC01070 can be used as a potential biomarker for the prognosis of breast cancer patients.