Open AccessIntegrated analysis identifies a novel lncRNA prognostic signature associated with aerobic glycolysis and hub pathways in breast cancer
Author(s) -
Li Zheng,
Zheng Juan,
Feng Yang,
Li Yaming,
Liang Yiran,
Liu Ying,
Wang Xiaolong,
Yang Qifeng
Publication year - 2021
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.4291
Subject(s) - breast cancer , nomogram , cancer , oncology , anaerobic glycolysis , biology , cancer research , tumor progression , medicine , bioinformatics , cancer cell
Abstract Long noncoding RNAs (lncRNAs) play a crucial role in cancer aerobic glycolysis. However, glycolysis‐related lncRNAs are still underexplored in breast cancer. In this study, we identified the five most glycolysis‐related lncRNAs in breast cancer to construct a prognostic signature, which could distinguish between patients with unfavorable and favorable prognoses. To investigate the role of signature lncRNAs in breast cancer, we profiled their expression levels in breast cancer progression cell line model. Real‐time PCR revealed that the five lncRNAs could contribute to breast cancer initiation or progression. Furthermore, we observed that the levels of four lncRNAs expression had a significant trend of gradient upregulation with the addition of glycolysis inhibitor in breast cancer cells. Afterward, random forest and logistic regression were conducted to assess the model's performance in stratifying glycolysis status. Finally, a nomogram including the lncRNA signature and clinical features was developed, and its efficacy in predicting the survival time and clinical utility was evaluated using a calibration curve, concordance index, and decision curve analysis. In this study, gene set enrichment analysis showed that the mTOR pathway, a central pathway in tumor initiation and progression, was significantly enriched in the high‐risk group. In addition, gene set variation analysis was performed to validate our findings in two independent datasets. Subsequent weighted gene co‐expression network analysis, followed by enrichment analysis, indicated that downstream cell growth‐related signaling was strikingly activated in the high‐risk group, and may directly promote tumor progression and escalate mortality risk in patients with high‐risk scores. Overall, our findings may provide novel insight into lncRNA‐related metabolic regulation, and help to develop promising prognostic indicators and therapeutic targets for breast cancer patients.