A six-long non-coding RNAs signature as a potential prognostic marker for survival prediction of ER-positive breast cancer patients
نویسندگان
چکیده
Dysregulated expression of lncRNAs has been observed in various human complex diseases (including cancers) by recent transcriptional profiling studies, highlighting potentials of lncRNAs as biomarkers for cancer diagnosis and prognosis. Despite some efforts have been made to search for novel lncRNA signature in breast cancer, the prognostic value of lncRNAs for ER-positive breast cancer patients still needs to be systematically investigated. In this study, we analyzed lncRNA expression profiles in a large of more than 600 breast cancer patients with ER-positive status from The Cancer Genome Atlas (TCGA) and identified six lncRNAs that are significantly associated with survival. Then a linear risk score model comprising six prognostic lncRNAs, termed six-lncRNA signature, was developed to identify high-risk patients from low-risk cases. The results of Kaplan-Meier analysis and ROC curves demonstrated the good sensitivity and specificity in survival prediction both in the training and testing datasets. Multivariate Cox regression analysis and stratified analysis showed that the six-lncRNA signature is an independent prognostic marker in survival prediction for ER-positive breast cancer patients. The GO enrichment analysis suggested that the six-lncRNA might involve with known breast cancer-related biological processes. With further experimental validation, these identified prognostic lncRNAs might have clinical implications for more personalized risk assessment for ER-positive breast cancer patients.
منابع مشابه
A potential prognostic long non-coding RNA signature to predict metastasis-free survival of breast cancer patients
Long non-coding RNAs (lncRNAs) have been implicated in a variety of biological processes, and dysregulated lncRNAs have demonstrated potential roles as biomarkers and therapeutic targets for cancer prognosis and treatment. In this study, by repurposing microarray probes, we analyzed lncRNA expression profiles of 916 breast cancer patients from the Gene Expression Omnibus (GEO). Nine lncRNAs wer...
متن کاملWRAP53 Polymorphism, rs2287498: A Case Study in Northwest of Iran?
Background: Non-coding RNAs apply regulations on expression or function of a gene. A class of non-coding RNAs, natural antisense transcripts, might overlap with their flanking genes and emerge a new complexity upon regulation. WRAP53, is a natural antisense transcript overlapped in a head-to-head manner on the opposite strand of TP53. It has 3 transcripts of which WRAP53β produ...
متن کاملThe Role of Long Non-Coding RNAs in Ovarian Cancer
Background: Ovarian cancer is the most fatal tumor of female's reproductive system, and several genetics and environmental factors are involved in its development. Various studies have already identified suitable biomarkers to facilitate the early detection, prognosis evaluation, and the assessment of treatment response. However, the aim of this review was to investigate the role of long non-co...
متن کاملA potential panel of six-long non-coding RNA signature to improve survival prediction of diffuse large-B-cell lymphoma
Long non-coding RNAs (lncRNAs) represent an emerging layer of cancer biology and have been implicated in the development and progression of cancers. However, the prognostic significance of lncRNAs in diffuse large-B-cell lymphoma (DLBCL) remains unclear and needs to be systematically investigated. In this study, we obtained and analyzed lncRNA expression profiles in three cohorts of 1043 DLBCL ...
متن کاملDiscovery of potential prognostic long non-coding RNA biomarkers for predicting the risk of tumor recurrence of breast cancer patients
Deregulation of long non-coding RNAs (lncRNAs) expression has been proven to be involved in the development and progression of cancer. However, expression pattern and prognostic value of lncRNAs in breast cancer recurrence remain unclear. Here, we analyzed lncRNA expression profiles of breast cancer patients who did or did not develop recurrence by repurposing existing microarray datasets from ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 8 شماره
صفحات -
تاریخ انتشار 2017