Abstract
The objective of this study was to construct a competitive endogenous RNA (ceRNA) regulatory network using differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with triple-negative breast cancer (TNBC) and to construct a prognostic model for predicting overall survival (OS) in patients with TNBC. Differentially expressed lncRNAs, miRNAs, and mRNAs in TNBC patients from the TCGA and Metabric databases were examined. A prognostic model based on prognostic scores (PSs) was established for predicting OS in TNBC patients, and the performance of the model was assessed by a recipient that operated on a distinctive curve. A total of 874 differentially expressed RNAs (DERs) were screened, among which 6 lncRNAs, 295 miRNAs and 573 mRNAs were utilized to construct targeted and coexpression ceRNA regulatory networks. Eight differentially expressed genes (DEGs) associated with survival prognosis, DBX2, MYH7, TARDBP, POU4F1, ABCB11, LHFPL5, TRHDE and TIMP4, were identified by multivariate Cox regression and then used to establish a prognostic model. Our study shows that the ceRNA network has a critical role in maintaining the aggressiveness of TNBC and provides comprehensive molecular-level insight for predicting individual mortality hazards for TNBC patients. Our data suggest that these prognostic mRNAs from the ceRNA network are promising therapeutic targets for clinical intervention.
Highlights
Breast cancer is the most frequently diagnosed cancer and the second most common cause of cancer mortality in women worldwide [1]
According to the platform annotation information provided in the downloaded data, 14,000 mRNAs, 1778 long noncoding RNAs (lncRNAs) and 2222 miRNAs were annotated in the data set
The above differentially expressed RNAs (DERs) were identified as candidate prognosis factors
Summary
Breast cancer is the most frequently diagnosed cancer and the second most common cause of cancer mortality in women worldwide [1]. TNBC, as an aggressive subtype, accounts for 12-18% of all breast cancers [2]. Targeted therapies cannot significantly improve the survival rate of TNBC patients, and chemotherapy is still the standard treatment. Exploring the molecular biological mechanism affecting the ceRNA Reveals OS in TNBC prognosis of patients with TNBC and identifying reliable prognostic markers are very valuable for accelerating individual therapies and improving clinical prognoses. Substantial efforts have been made to classify TNBC into distinct clinical and molecular subtypes to guide treatment decisions. High levels of somatic mutations, frequent TP53 mutations (83%) and complex aneuploidy rearrangement (80%) have been found in TNBC patients via deep sequencing studies [3], multiregion sequencing analyses [4] and single-cell sequencing research [5], revealing extensive intratumoural heterogeneity (ITH). The molecular mechanism driving TNBC relapse has not been fully elucidated
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