ArticleScientific reports2016
A new avenue for obtaining insight into the functional characteristics of long noncoding RNAs associated with estrogen receptor signaling.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Estrogen Receptor and Vascular Aging.Frontiers in aging · 2021Review
- Identification and characterization of functional long noncoding RNAs in cancer.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2020Review
- Diosgenin protects against alveolar bone loss in ovariectomized rats via regulating long non-coding RNAs.Experimental and therapeutic medicine · 2018Article
- The LncRNA Connectivity Map: Using LncRNA Signatures to Connect Small Molecules, LncRNAs, and Diseases.Scientific reports · 2017Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Estrogen receptor signalling plays important regulatory roles in multiple mammalian physiological processes. Dysregulation of estrogen receptor (ER) expression and/or its associated signalling pathway is strongly associated with the development, progression, transition, and endocrine-resistance of breast cancer. Non-coding transcripts are essential regulators of almost every level of gene regulation. However, few long non-coding transcripts (lncRNAs) associated with the estrogen receptor signalling pathway have been well-described. We used array-based methods to identify 33 estrogen receptor agitation-related (ERAR) lncRNAs. A coding-non-coding gene co-expression network analysis suggested that 15 ERAR lncRNAs were associated with mitosis, DNA damage, and DNA repair. Kaplan-Meier analysis indicated that five ERAR lncRNAs selected using the Random Forest-Recursive Feature Elimination algorithm were significantly correlated with endocrine resistance-free survival and distant metastasis-free survival as well as disease free survival. Our results suggest that ERAR lncRNAs may serve as novel biomarkers for guiding breast cancer treatment and prognosis. Furthermore, our findings reveal a new avenue by which estrogen receptor signalling can be further explored.
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