ArticleMolecular oncology2018
miRNA-mediated 'tug-of-war' model reveals ceRNA propensity of genes in cancers.
Article in Molecular oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Circular circRANGAP1 Contributes to Non-small Cell Lung Cancer Progression by Increasing COL11A1 Expression Through Sponging miR-653-5p.Biochemical genetics · 2023Article
- Replication Study: Coding-independent regulation of the tumor suppressor PTEN by competing endogenous mRNAs.eLife · 2020Article
- Analysis of circular RNA-associated competing endogenous RNA network in breast cancer.Oncology letters · 2020Article
- NORAD accelerates chemo-resistance of non-small-cell lung cancer via targeting at miR-129-1-3p/SOX4 axis.Bioscience reports · 2020Article
- LncRNA NNT-AS1 contributes to the cisplatin resistance of cervical cancer through NNT-AS1/miR-186/HMGB1 axis.Cancer cell international · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Competing endogenous RNA (ceRNA) are transcripts that cross-regulate each other at the post-transcriptional level by competing for shared microRNA response elements (MREs). These have been implicated in various biological processes impacting cell-fate decisions and diseases including cancer. There are several studies that predict possible ceRNA pairs by adopting various machine-learning and mathematical approaches; however, there is no method that enables us to gauge as well as compare the propensity of the ceRNA of a gene and precisely envisages which among a pair exerts a stronger pull on the shared miRNA pool. In this study, we developed a method that uses the 'tug of war of genes' concept to predict and quantify ceRNA potential of a gene for the shared miRNA pool in cancers based on a score represented by SoCeR (score of competing endogenous RNA). The method was executed on the RNA-Seq transcriptional profiles of genes and miRNA available at TCGA along with CLIP-supported miRNA-target sites to predict ceRNA in 32 cancer types which were validated with already reported cases. The proposed method can be used to determine the sequestering capability of the gene of interest as well as in ranking the probable ceRNA candidates of a gene. Finally, we developed standalone applications (SoCeR tool) to aid researchers in easier implementation of the method in analysing different data sets or diseases.
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.