ArticlePloS one2013
A new algorithm for integrated analysis of miRNA-mRNA interactions based on individual classification reveals insights into bladder cancer.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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
28 citing papers in PubMed, 51 citations in OpenAlex.
- CCDC137 knockdown suppresses bladder cancer progression by downregulating SCD.Journal of translational medicine · 2025Article
- Association of miRNA-17-92 Cluster with Muscle Invasion in Bladder Cancer.International journal of molecular sciences · 2025Article
- Mevalonate pathway inhibition reduces bladder cancer metastasis by modulating RhoB protein stability and integrin β1 localization.Communications biology · 2024Article
- IGF2BP3 prevent HMGB1 mRNA decay in bladder cancer and development.Cellular & molecular biology letters · 2024Article
- CDH1 overexpression predicts bladder cancer from early stage and inversely correlates with immune infiltration.BMC urology · 2022Article
- A review on methods for predicting miRNA-mRNA regulatory modules.Journal of integrative bioinformatics · 2022Review
- Article
- Article
- Article
- miRModuleNet: Detecting miRNA-mRNA Regulatory Modules.Frontiers in genetics · 2022Article
- Fatty Acid Synthase Is the Key Regulator of Fatty Acid Metabolism and Is Related to Immunotherapy in Bladder Cancer.Frontiers in immunology · 2022Article
- Article
- miRGTF-net: Integrative miRNA-gene-TF network analysis reveals key drivers of breast cancer recurrence.PloS one · 2021Article
- Article
- Mechanistic Computational Models of MicroRNA-Mediated Signaling Networks in Human Diseases.International journal of molecular sciences · 2019Review
- Identification of differentially expressed miRNAs and miRNA-targeted genes in bladder cancer.Oncotarget · 2018Article
- Dysregulated genes targeted by microRNAs and metabolic pathways in bladder cancer revealed by bioinformatics methods.Oncology letters · 2018Article
- MiR-411 suppresses the development of bladder cancer by regulating ZnT1.OncoTargets and therapy · 2018Article
- MiR-26a inhibits cell proliferation and induces apoptosis in human bladder cancer through regulating EZH2 bioactivity.International journal of clinical and experimental pathology · 2017Article
- Computational identification of microRNAs associated to both epithelial to mesenchymal transition and NGAL/MMP-9 pathways in bladder cancer.Oncotarget · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression. It has been proposed that miRNAs play an important role in cancer development and progression. Their ability to affect multiple gene pathways by targeting various mRNAs makes them an interesting class of regulators. METHODOLOGY/PRINCIPAL
findingsWe have developed an algorithm, Classification based Analysis of Paired Expression data of RNA (CAPE RNA), which is capable of identifying altered miRNA-mRNA regulation between tissues samples that assigns interaction states to each sample without preexisting stratification of groups. The distribution of the assigned interaction states compared to given experimental groups is used to assess the quality of a predicted interaction. We demonstrate the applicability of our approach by analyzing urothelial carcinoma and normal bladder tissue samples derived from 24 patients. Using our approach, normal and tumor tissue samples as well as different stages of tumor progression were successfully stratified. Also, our results suggest interesting differentially regulated miRNA-mRNA interactions associated with bladder tumor progression. CONCLUSIONS/SIGNIFICANCE: The need for tools that allow an integrative analysis of microRNA and mRNA expression data has been addressed. With this study, we provide an algorithm that emphasizes on the distribution of samples to rank differentially regulated miRNA-mRNA interactions. This is a new point of view compared to current approaches. From bootstrapping analysis, our ranking yields features that build strong classifiers. Further analysis reveals genes identified as differentially regulated by miRNAs to be enriched in cancer pathways, thus suggesting biologically interesting interactions.
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.