Glucose metabolism and lncRNAs in breast cancer: Sworn friend

BACKGROUND: Glucose metabolism disorder is a common feature in cancer. Cancer cells generate much energy through anaerobic glycolysis, which promote the development of tumors. However, long non‐coding RNA may play an important role in this process. Our aim is to explore a prognostic risk model based on the glucose metabolism‐related lncRNAs which provides clues that lncRNAs predict a clinical outcome through glucose metabolism in breast cancer. METHODS: 1222 RNA‐seq were extracted from the TCGA database, and 74 glucose metabolism‐related genes were loaded from the GSEA website. Then, 7 glucose metabolism‐related lncRNAs risk score model was developed by univariate, Lasso, and multivariate regression analysis. The lncRNA risk model showed that high‐risk patients predict a poor clinical outcome with high reliability (P=2.838×10‐6). Univariate and multivariate independent prognostic analysis and ROC curve analysis proved that the risk score was an independent prognostic factor in breast cancer with an AUC value of 0.652. Finally, Gene set enrichment analysis showed that cell cycle‐related pathways were significantly enriched in a high‐risk group. RESULTS: Our results showed that glucose metabolism‐related lncRNAs can affect breast cancer progression. 7 glucose metabolism‐related lncRNAs prognostic signature was established to evaluate the OS of patients with breast cancer. PICSAR, LINC00839, AP001505.1, LINC00393 were risk factors and expressed highly in the high‐risk group. A Nomogram was made based on this signature to judge patients' living conditions and prognosis. CONCLUSION: 7 glucose metabolism‐related lncRNAs risk score model had a high prognostic value in breast cancer. PICSAR, LINC00839, AP001505.1, LINC00393 were risk factors. AP001505.1 expression was increased in most triple‐negative breast cancer cells treated with high glucose, which may also take part in breast cancer progression and potential therapeutic targets