m6A-related lncRNAs are potential biomarkers for predicting prognoses in patients with breast cancer

Background: Breast cancer (BRCA) is a common cancer and major cause of cancer mortality in females around the world. N6-methyladenosine (m 6 A) and m 6 A-associated long non-coding RNAs (lncRNAs) play vital roles in the prognostic value of BRCA. However, how m 6 A-related lncRNAs affect the survival of BRCA patients remains unclear. Methods: : In this study, we obtained m 6 A-related lncRNAs by gene co-expression and used univariate least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to construct a comprehensive m 6 A-related lncRNA model. Based on this model, a risk score was calculated for each patient. Next, Kaplan-Meier analyses, cell type enrichment analysis, and gene ontology (GO) enrichment were used to analyze the risk model. Finally, performance comparison was made between risk model and other common prognostic biomarkers in BRCA using ROC curve and nomogram. Results: : The comprehensive risk model of 39 genes (10 m 6 A-related lncRNAs and 29 other genes) and basic clinical factors showed better performance in BRCA prognosis compared to other common prognostic biomarkers. By regrouping the patients with this model, we found that patients in the high-risk group had higher tumor mutation burden (TMB) and differentially expressed genes between high- and low risk patients were enriched in tumor-related inflammation response pathway and lipid droplet pathway. Conclusions: : These results demonstrate that our comprehensive 39-genes risk model based on the m 6 A-related lncRNAs is promising for clinical prediction and provides a treatment guide for BRCA patients.