Autophagy related long non-coding RNA and breast cancer prognosis analysis and prognostic risk model establishment

BACKGROUND: The role of autophagy-related long-stranded non-coding RNA (lncRNA) in breast cancer (BRCA) is unclear. We proposed to screen autophagy-related lncRNAs in BRCA and construct a prognostic risk assessment model to explore prognostic correlates. METHODS: We extracted BRCA lncRNAs from The Cancer Genome Atlas (TCGA) database and autophagy-related genes from the Human Autophagy Database (HADb), to screen for autophagy-related lncRNA pairs (ARLP) in BRCA. Single-factor Cox regression analysis and multi-factor Cox regression analysis were used to screen lncRNAs associated with BRCA prognosis, and risk models were established. We divided BRCA patients into high-risk and low-risk groups based on median risk scores. The single-sample gene set enrichment analysis (ssGSEA) algorithm was used to calculate the abundance of 28 immune cells in the TCGA-BRCA cohort and to analyze the relationship between the risk score and the level of immune cell infiltration by ARLP characteristics. RESULTS: Univariate Cox regression results showed that 42 ARLPs were significantly associated with overall survival (OS) in BRCA patients. Further multifactorial analysis showed that a total of 11 lncRNAs, including SEMA3B-AS1, ST7-AS1, AL136295.7, AC090912.1, LINC01871, AL136531.1, AC024361.1, OTUD6B-AS1, LINC01786, AL122010.1, and MAPT-AS1, were prognostically independent influencers of BRCA. The risk model developed was further validated as a new independent prognostic factor for BRCA patients by Kaplan-Meier (KM) analysis, univariate and multivariate Cox regression analysis to calculate the risk score. In addition, the results of the relationship between risk score and immune infiltration showed that low risk score was associated with T-lymphocyte subpopulation. CONCLUSIONS: Our study suggested that a risk model consisting of 11 autophagy-related lncRNAs can be used to assess the prognosis of BRCA patients.