ArticleBMC medical genomics2022
Identification and validation of an epigenetically regulated long noncoding RNA model for breast cancer metabolism and prognosis.
Article in BMC medical genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Expression of MIR155HG, LOC283856, KIAA0125, and LOC100190986 as potential prognostic and predictive biomarkers for breast cancer.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas · 2026Article
- Clinical significance of LINC01158 in breast cancer and inhibition of proliferation and metastasis of breast cancer cells by regulating miR-711.Hereditas · 2025Article
- Development of a novel forensic age estimation strategy for aged blood samples by combining piRNA and miRNA markers.International journal of legal medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBreast cancer (BC) is the leading cause of death among women, and epigenetic alterations that can dysregulate long noncoding RNAs (lncRNAs) are thought to be associated with cancer metabolism, development, and progression. This study investigated the epigenetic regulation of lncRNAs and its relationship with clinical outcomes and treatment responses in BC in order to identify novel and effective targets for BC treatment.
methodsWe comprehensively analysed DNA methylation and transcriptome data for BC and identified epigenetically regulated lncRNAs as potential prognostic biomarkers using machine learning and multivariate Cox regression analysis. Additionally, we applied multivariate Cox regression analysis adjusted for clinical characteristics and treatment responses to identify a set of survival-predictive lncRNAs, which were subsequently used for functional analysis of protein-encoding genes to identify downstream biological pathways.
resultsWe identified a set of 1350 potential epigenetically regulated lncRNAs and generated a methylated lncRNA dataset for BC, MylnBrna, comprising 14 lncRNAs from a list of 20 epigenetically regulated lncRNAs significantly associated with tumour survival. MylnBrna stratifies patients into high-risk and low-risk groups with significantly different survival rates. These lncRNAs were found to be closely related to the biological pathways of amino acid metabolism and tumour metabolism, revealing a potential tumour-regulation function.
conclusionThis study established a potential prognostic biomarker model (MylnBrna) for BC survival and offered an insight into the epigenetic regulatory mechanisms of lncRNAs in BC in the context of tumour metabolism.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.