title: An integrative analysis of cellular contexts, miRNAs and mRNAs reveals network clusters associated with antiestrogen-resistant breast cancer cells.
abstract: BACKGROUND
  A 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.
  
  
  RESULTS
  Based 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.
  
  
  CONCLUSIONS
  By 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.
authors.affiliation: Cancer Genomics Branch, National Cancer Center, Goyang-si, Gyeonggi-do, 410-769, Korea. seungyoon.nam@ncc.re.kr
authors.forename: Seungyoon
authors.initials: S
authors.lastname: Nam
authors.forename: Xinghua
authors.initials: X
authors.lastname: Long
authors.forename: Changhyuk
authors.initials: C
authors.lastname: Kwon
authors.forename: Sun
authors.initials: S
authors.lastname: Kim
authors.forename: Kenneth P
authors.initials: KP
authors.lastname: Nephew
mesh_terms: D001943:Breast Neoplasms / Q000188:drug therapy / Q000235:genetics / Q000473:pathology*; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D019008:Drug Resistance, Neoplasm / Q000235:genetics*; D004967:Estrogens / Q000378:metabolism*; D006801:Humans; D061986:MCF-7 Cells; D035683:MicroRNAs / Q000235:genetics*; D058990:Molecular Targeted Therapy; D012333:RNA, Messenger / Q000235:genetics
chemical_list: D004967:Estrogens; D035683:MicroRNAs; D012333:RNA, Messenger