Abstract

BackgroundBreast cancer (BC) is an age‐related disease. Long noncoding RNAs (lncRNAs) have been proven to be crucial contributors in tumorigenesis. This study aims to develop a novel lncRNA‐based signature to predict elderly BC patients’ prognosis.MethodsThe RNA expression profiles and corresponding clinical information of 182 elderly BC patients were retrieved from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs (DElncRNAs) between BC and adjacent normal samples were used to construct the signature in the training set through univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis. Kaplan–Meier analysis and time‐dependent receiver operating characteristic (ROC) analysis were used to evaluate the predictive performance. Besides, we developed the nomogram. Gene set enrichment analysis (GSEA) was performed to reveal the underlying molecular mechanisms.ResultsWe constructed the five‐lncRNA signature (including LEF1‐AS1, MEF2C‐AS1, ST8SIA6‐AS1, LINC01224, and LINC02408) in the training set, which successfully divided the patients into low‐ and high‐risk groups with significantly different prognosis (p = 0.000049), and the AUC at 3 and 5 years of the signature was 0.779 and 0.788, respectively. The predictive performance of this signature was validated in the test and entire set. The 5‐lncRNA signature was an independent prognostic factor of OS (p = 0.007) and the nomogram constructed by independent prognostic factors was an accurate predictor of predicting overall survival probability. Besides, several pathways associated with tumorigenesis have been identified by GSEA.ConclusionsThe 5‐lncRNA signature and nomogram are reliable in predicting elderly BC patients’ prognosis and provide clues for clinical decision‐making.

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 call

Disclaimer: 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.