Identification of a Six-lncRNA Signature With Prognostic Value for Breast Cancer Patients

Abstract

Breast cancer (BRCA) is the most common cancer and a major cause of death in women. Long non-coding RNAs (lncRNAs) are emerging as key regulators and have been implicated in carcinogenesis and prognosis. In this study, we aimed to develop a lncRNA signature of BRCA patients to improve risk stratification. In the training cohort (GSE21653, n = 232), 17 lncRNAs were identified by univariate Cox proportional hazards regression, which were significantly associated with patients’ survival. The least absolute shrinkage and selection operator-penalized Cox proportional hazards regression analysis was used to identify a six-lncRNA signature. According to the median of the signature risk score, patients were divided into a high-risk group and a low-risk group with significant disease-free survival differences in the training cohort. A similar phenomenon was observed in validation cohorts (GSE42568, n = 101; GSE20711, n = 87). The six-lncRNA signature remained as independent prognostic factors after adjusting for clinical factors in these two cohorts. Furthermore, this signature significantly predicted the survival of grade III patients and estrogen receptor-positive patients. Furthermore, in another cohort (GSE19615, n = 115), the low-risk patients that were treated with tamoxifen therapy had longer disease-free survival than those who underwent no therapy. Overall, the six-lncRNA signature can be a potential prognostic tool used to predict disease-free survival of patients and to predict the benefits of tamoxifen treatment in BRCA, which will be helpful in guiding individualized treatments for BRCA patients.

Postpartum breast cancer has a distinct molecular profile that predicts poor outcomes

“…To determine whether this PPBC gene expression signature could predict outcomes in an ER+ YWBC cohort. We assembled a YWBC cohort (≤45 years old) with outcomes data by compiling gene expression data across seven previously published studies [72][73][74][75][76][77][78] . Although no parity history was available on these publicly available cases, upon applying our PPBC gene signature to this YWBC cohort (n = 311 patients with both ER+ and ER− disease) we observed a highly significant decrease in 15-year overall survival in breast cancer patients with a PPBC Hi signature score (HR 2.134, p = 0.0011) compared with those with a low score (PPBC Lo, Fig.…”

“…Compilation and analysis of YWBC cohort. In this study, YWBC data sets were collected from 8 studies and downloaded from the Gene Expression Omnibus (GEO) with the following accession number: GSE1992 72 , GSE20624 73 , GSE21653 74 , GSE6532 75 , GSE2990 79 , GSE4922 76 , GSE7390 77 , and GSE19615 78 . The GEOquery and biomaRt R packages 117 were used to download the raw expression and meta data.…”

A Novel Risk Model Based on Lipid Metabolism-Associated Genes Predicts Prognosis and Indicates Immune Microenvironment in Breast Cancer

“…Epidemiological studies have revealed that at least 268,000 patients are newly diagnosed with BRCA each year and 41,760 patients die. The incidence of BRCA has been steadily increasing ( Siegel et al, 2019 ; Britt et al, 2020 ; Zhao et al, 2020 ). Currently, the therapeutic strategies for BRCA mainly include surgical resection, endocrine therapy, and combining surgery with various types of adjuvant therapies, including radiotherapy, chemotherapy, and immunotherapy ( Waks and Winer, 2019 ; Zhao et al, 2020 ).…”

Genetic instability-related lncRNAs predict prognosis and influence the immune microenvironment in breast cancer

“…We next compared the predictive performance of GILncRNASig to two recently published lncRNA signatures: the 6-lncRNA signature derived from Erjie's study (hereafter referred to as ErjielncRNAsig) (Zhao et al, 2020) and the 8-lncRNA signature derived from Zhenbin's study (hereafter referred to as ZhenbinlncRNAsig) (Liu et al, 2019). Using the same TCGA patient cohort, the AUC of GILncRNASig we constructed was 0.686 for 1-year OS, which was significantly higher than those of ErjielncRNASig (AUC = 0.583) and ZhenbinlncRNASig (AUC = 0.661) (Figure 5A).…”