ArticleBMC genomics2012
An integrative analysis of cellular contexts, miRNAs and mRNAs reveals network clusters associated with antiestrogen-resistant breast cancer cells.
Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- The clinicopathological significance of microRNA-155 in breast cancer: a meta-analysis.BioMed research international · 2014Pooled it
- miRNA Expression Profiles in Luminal A Breast Cancer-Implications in Biology, Prognosis, and Prediction of Response to Hormonal Treatment.International journal of molecular sciences · 2020Review
- The Emerging Roles of miR-125b in Cancers.Cancer management and research · 2020Review
- Ovarian Cancer Prognostic Prediction Model Using RNA Sequencing Data.Genomics & informatics · 2018Article
- Differential microRNA expression profiles in tamoxifen-resistant human breast cancer cell lines induced by two methods.Oncology letters · 2018Article
- microRNA Regulation in Estrogen Receptor-Positive Breast Cancer and Endocrine Therapy.Biological procedures online · 2018Review
- Cancer Transcriptome Dataset Analysis: Comparing Methods of Pathway and Gene Regulatory Network-Based Cluster Identification.Omics : a journal of integrative biology · 2017Article
- Review
- miR-378a-3p modulates tamoxifen sensitivity in breast cancer MCF-7 cells through targeting GOLT1A.Scientific reports · 2015Article
- The novel role of miRNAs for tamoxifen resistance in human breast cancer.Cellular and molecular life sciences : CMLS · 2015Review
- MicroRNA-125b upregulation confers aromatase inhibitor resistance and is a novel marker of poor prognosis in breast cancer.Breast cancer research : BCR · 2015Article
- miRNA clusters as therapeutic targets for hormone-resistant breast cancer.Expert review of endocrinology & metabolism · 2015Article
- Identification of temozolomide resistance factors in glioblastoma via integrative miRNA/mRNA regulatory network analysis.Scientific reports · 2014Article
- Mg2+ effect on argonaute and RNA duplex by molecular dynamics and bioinformatics implications.PloS one · 2014Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
Abstract
backgroundA major goal of the field of systems biology is to translate genome-wide profiling data (e.g., mRNAs, miRNAs) into interpretable functional networks. However, employing a systems biology approach to better understand the complexities underlying drug resistance phenotypes in cancer continues to represent a significant challenge to the field. Previously, we derived two drug-resistant breast cancer sublines (tamoxifen- and fulvestrant-resistant cell lines) from the MCF7 breast cancer cell line and performed genome-wide mRNA and microRNA profiling to identify differential molecular pathways underlying acquired resistance to these important antiestrogens. In the current study, to further define molecular characteristics of acquired antiestrogen resistance we constructed an "integrative network". We combined joint miRNA-mRNA expression profiles, cancer contexts, miRNA-target mRNA relationships, and miRNA upstream regulators. In particular, to reduce the probability of false positive connections in the network, experimentally validated, rather than prediction-oriented, databases were utilized to obtain connectivity. Also, to improve biological interpretation, cancer contexts were incorporated into the network connectivity.
resultsBased on the integrative network, we extracted "substructures" (network clusters) representing the drug resistant states (tamoxifen- or fulvestrant-resistance cells) compared to drug sensitive state (parental MCF7 cells). We identified un-described network clusters that contribute to antiestrogen resistance consisting of miR-146a, -27a, -145, -21, -155, -15a, -125b, and let-7s, in addition to the previously described miR-221/222.
conclusionsBy integrating miRNA-related network, gene/miRNA expression and text-mining, the current study provides a computational-based systems biology approach for further investigating the molecular mechanism underlying antiestrogen resistance in breast cancer cells. In addition, new miRNA clusters that contribute to antiestrogen resistance were identified, and they warrant further investigation.
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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.