Open AccessDevelopment of a novel five‐lncRNA prognostic signature for predicting overall survival in elderly patients with breast cancer
Author(s) -
Luo Yang,
Zhang Yue,
Wu YuXin,
Li HanBing,
Shen Di,
Che YiQun
Publication year - 2022
Publication title -
journal of clinical laboratory analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.536
H-Index - 50
eISSN - 1098-2825
pISSN - 0887-8013
DOI - 10.1002/jcla.24172
Subject(s) - nomogram , proportional hazards model , oncology , receiver operating characteristic , univariate , breast cancer , carcinogenesis , long non coding rna , survival analysis , medicine , lasso (programming language) , multivariate analysis , cancer , multivariate statistics , biology , gene , computer science , rna , machine learning , genetics , world wide web
Background Breast 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. Methods The 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. Results We 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. Conclusions The 5‐lncRNA signature and nomogram are reliable in predicting elderly BC patients’ prognosis and provide clues for clinical decision‐making.