ArticleOncotarget2016
Network-based identification of microRNAs as potential pharmacogenomic biomarkers for anticancer drugs.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
What it found
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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.
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.
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Who cites it
44 citing papers in PubMed, 85 citations in OpenAlex.
- Heterogeneous dual-channel and interpretable graph representation learning with global virtual nodes for microRNA-mediated drug sensitivity prediction.Molecular diversity · 2026Article
- Leveraging quantum chemical properties in transfer learning for predicting blood-brain barrier permeability of drugs.Drug delivery and translational research · 2026Article
- JNJ-26366821 Attenuates Radiation-Induced Pro-Inflammatory Cytokines and miRNAs and Triggers TR/RXR Signaling Pathway.International journal of molecular sciences · 2026Article
- Machine learning approaches for predicting the small molecule-miRNA associations: a comprehensive review.Molecular diversity · 2025Review
- MDFGNN-SMMA: prediction of potential small molecule-miRNA associations based on multi-source data fusion and graph neural networks.BMC bioinformatics · 2025Article
- The neurodevelopmental regulatory role and clinical value of hsa-circ-CORO1C-hsa-miR-708-3p-JARID2 + LNPEP axis in early-onset schizophrenia.Schizophrenia (Heidelberg, Germany) · 2024Article
- Drug repurposing for cancer therapy.Signal transduction and targeted therapy · 2024Review
- Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications.European journal of medicinal chemistry · 2023Review
- AMCSMMA: Predicting Small Molecule-miRNA Potential Associations Based on Accurate Matrix Completion.Cells · 2023Article
- Bioinformatics analysis of miRNA and its associated genes to identify potential biomarkers of oral submucous fibrosis and oral malignancy.Cancer reports (Hoboken, N.J.) · 2023Article
- Article
- Combining non-negative matrix factorization with graph Laplacian regularization for predicting drug-miRNA associations based on multi-source information fusion.Frontiers in pharmacology · 2023Article
- Article
- Review
- Prediction of small molecule drug-miRNA associations based on GNNs and CNNs.Frontiers in genetics · 2023Article
- CDX-301 prevents radiation-induced dysregulation of miRNA expression and biogenesis.Molecular therapy. Nucleic acids · 2022Article
- A message passing framework with multiple data integration for miRNA-disease association prediction.Scientific reports · 2022Article
- PSRR: A Web Server for Predicting the Regulation of miRNAs Expression by Small Molecules.Frontiers in molecular biosciences · 2022Article
- VDA-RWLRLS: An anti-SARS-CoV-2 drug prioritizing framework combining an unbalanced bi-random walk and Laplacian regularized least squares.Computers in biology and medicine · 2022Article
- Prediction of potential small molecule-miRNA associations based on heterogeneous network representation learning.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
As the recent development of high-throughput technologies in cancer pharmacogenomics, there is an urgent need to develop new computational approaches for comprehensive identification of new pharmacogenomic biomarkers, such as microRNAs (miRNAs). In this study, a network-based framework, namely the SMiR-NBI model, was developed to prioritize miRNAs as potential biomarkers characterizing treatment responses of anticancer drugs on the basis of a heterogeneous network connecting drugs, miRNAs and genes. A high area under the receiver operating characteristic curve of 0.820 ± 0.013 was yielded during 10-fold cross validation. In addition, high performance was further validated in identifying new anticancer mechanism-of-action for natural products and non-steroidal anti-inflammatory drugs. Finally, the newly predicted miRNAs for tamoxifen and metformin were experimentally validated in MCF-7 and MDA-MB-231 breast cancer cell lines via qRT-PCR assays. High success rates of 60% and 65% were yielded for tamoxifen and metformin, respectively. Specifically, 11 oncomiRNAs (e.g. miR-20a-5p, miR-27a-3p, miR-29a-3p, and miR-146a-5p) from the top 20 predicted miRNAs were experimentally verified as new pharmacogenomic biomarkers for metformin in MCF-7 or MDA-MB-231 cell lines. In summary, the SMiR-NBI model would provide a powerful tool to identify potential pharmacogenomic biomarkers characterized by miRNAs in the emerging field of precision cancer medicine, which is available at http://lmmd.ecust.edu.cn/database/smir-nbi/.
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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.