title: Prediction of signaling cross-talks contributing to acquired drug resistance in breast cancer cells by Bayesian statistical modeling.
abstract: BACKGROUND
  Initial success of inhibitors targeting oncogenes is often followed by tumor relapse due to acquired resistance. In addition to mutations in targeted oncogenes, signaling cross-talks among pathways play a vital role in such drug inefficacy. These include activation of compensatory pathways and altered activities of key effectors in other cell survival and growth-associated pathways.
  
  
  RESULTS
  We propose a computational framework using Bayesian modeling to systematically characterize potential cross-talks among breast cancer signaling pathways. We employed a fully Bayesian approach known as the p 1-model to infer posterior probabilities of gene-pairs in networks derived from the gene expression datasets of ErbB2-positive breast cancer cell-lines (parental, lapatinib-sensitive cell-line SKBR3 and the lapatinib-resistant cell-line SKBR3-R, derived from SKBR3). Using this computational framework, we searched for cross-talks between EGFR/ErbB and other signaling pathways from Reactome, KEGG and WikiPathway databases that contribute to lapatinib resistance. We identified 104, 188 and 299 gene-pairs as putative drug-resistant cross-talks, respectively, each comprised of a gene in the EGFR/ErbB signaling pathway and a gene from another signaling pathway, that appear to be interacting in resistant cells but not in parental cells. In 168 of these (distinct) gene-pairs, both of the interacting partners are up-regulated in resistant conditions relative to parental conditions. These gene-pairs are prime candidates for novel cross-talks contributing to lapatinib resistance. They associate EGFR/ErbB signaling with six other signaling pathways: Notch, Wnt, GPCR, hedgehog, insulin receptor/IGF1R and TGF- β receptor signaling. We conducted a literature survey to validate these cross-talks, and found evidence supporting a role for many of them in contributing to drug resistance. We also analyzed an independent study of lapatinib resistance in the BT474 breast cancer cell-line and found the same signaling pathways making cross-talks with the EGFR/ErbB signaling pathway as in the primary dataset.
  
  
  CONCLUSIONS
  Our results indicate that the activation of compensatory pathways can potentially cause up-regulation of EGFR/ErbB pathway genes (counteracting the inhibiting effect of lapatinib) via signaling cross-talk. Thus, the up-regulated members of these compensatory pathways along with the members of the EGFR/ErbB signaling pathway are interesting as potential targets for designing novel anti-cancer therapeutics.
authors.affiliation: School of Mathematical Science, Monash University, Wellington Road, Clayton, VIC, Australia. aaza7@student.monash.edu.
authors.forename: A K M
authors.initials: AK
authors.lastname: Azad
authors.affiliation: Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Monash University, Wellington Road, Clayton, VIC, Australia. Alfons.Lawen@monash.edu.
authors.forename: Alfons
authors.initials: A
authors.lastname: Lawen
authors.affiliation: School of Mathematical Science, Monash University, Wellington Road, Clayton, VIC, Australia. Jonathan.Keith@monash.edu.
authors.forename: Jonathan M
authors.initials: JM
authors.lastname: Keith
mesh_terms: D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000473:pathology*; D045744:Cell Line, Tumor; D019295:Computational Biology / Q000379:methods*; D019008:Drug Resistance, Neoplasm; D066246:ErbB Receptors / Q000378:metabolism; D006801:Humans; D015233:Models, Statistical; D017526:Receptor, IGF Type 1; D011972:Receptor, Insulin / Q000378:metabolism; D051880:Receptors, Notch / Q000378:metabolism; D017451:Receptors, Somatomedin / Q000378:metabolism; D015398:Signal Transduction / Q000187:drug effects*; D060449:Wnt Signaling Pathway / Q000187:drug effects
chemical_list: C000597236:IGF1R protein, human; D051880:Receptors, Notch; D017451:Receptors, Somatomedin; C512478:EGFR protein, human; D066246:ErbB Receptors; D017526:Receptor, IGF Type 1; D011972:Receptor, Insulin