Abstract
BackgroundAutophagy is a “self-feeding” phenomenon of cells, which is crucial in mammalian development. Long non-coding RNA (lncRNA) is a new regulatory factor for cell autophagy, which can regulate the process of autophagy to affect tumor progression. However, poor attention has been paid to the roles of autophagy-related lncRNAs in breast cancer.ObjectiveThis study aimed to construct an autophagy-related lncRNA signature that can effectively predict the prognosis of breast cancer patients and explore the potential functions of these lncRNAs.MethodsThe RNA sequencing (RNA-Seq) data of breast cancer patients was collected from The Cancer Genome Atlas (TCGA) database and the GSE20685 database. Multivariate Cox analysis was implemented to produce an autophagy-related lncRNA signature in the TCGA cohort. The signature was then validated in the GSE20685 cohort. The receiver operator characteristic (ROC) curve was performed to evaluate the predictive ability of the signature. Gene set enrichment analysis (GSEA) was used to explore the potential functions based on the signature. Finally, the study developed a nomogram and internal verification based on the autophagy-related lncRNAs.ResultsA signature composed of 9 autophagy-related lncRNAs was determined as a prognostic model, and 1,109 breast cancer patients were divided into high-risk group and low-risk group based on median risk score of the signature. Further analysis demonstrated that the over survival (OS) of breast cancer patients in the high-risk group was poorer than that in the low-risk group based on the prognostic signature. The area under the curve (AUC) of ROC curve verified the sensitivity and specificity of this signature. Additionally, we confirmed the signature is an independent factor and found it may be correlated to the progression of breast cancer. GSEA showed gene sets were notably enriched in carcinogenic activation pathways and autophagy-related pathways. The qRT-PCR identified 5 lncRNAs with significantly differential expression in breast cancer cells based on the 9 lncRNAs of the prognostic model, and the results were consistent with the tissues.ConclusionIn summary, our signature has potential predictive value in the prognosis of breast cancer and these autophagy-related lncRNAs may play significant roles in the diagnosis and treatment of breast cancer.
Highlights
Breast cancer is the most common malignant tumor and the leading cause of cancer-related deaths in women worldwide, with an incidence and mortality of 24.2% and 15.0%, respectively [1, 2]
We developed autophagy-related Long non-coding RNA (lncRNA) coexpression networks based on the 9 genes (Table 2, Figure 3A)
Breast cancer is characterized by the accumulation of abnormal cells, which may be attributed to the imbalance of cell proliferation, apoptosis, and autophagy regulation disorder
Summary
Breast cancer is the most common malignant tumor and the leading cause of cancer-related deaths in women worldwide, with an incidence and mortality of 24.2% and 15.0%, respectively [1, 2]. Most patients respond to initial treatment within a certain period of time, but there are still some breast cancers, especially triple negative breast cancer, that will develop into a more invasive tumor form, resulting in a poor prognosis [9,10,11]. Multiple studies have reported that autophagy may play especially important roles in supporting cell growth and drug resistance to targeted therapy in BRAF-mutant melanoma [15,16,17]. Recent findings have revealed the autophagy drugs such as sirolimus and arsenic trioxide can induce autophagy of tumor cells and improve the outcome of certain cancer patients. Poor attention has been paid to the roles of autophagy-related lncRNAs in breast cancer
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
