title: Inferring predominant pathways in cellular models of breast cancer using limited sample proteomic profiling.
abstract: BACKGROUND
  Molecularly targeted drugs inhibit aberrant signaling within oncogenic pathways. Identifying the predominant pathways at work within a tumor is a key step towards tailoring therapies to the patient. Clinical samples pose significant challenges for proteomic profiling, an attractive approach for identifying predominant pathways. The objective of this study was to determine if information obtained from a limited sample (i.e., a single gel replicate) can provide insight into the predominant pathways in two well-characterized breast cancer models.
  
  
  METHODS
  A comparative proteomic analysis of total cell lysates was obtained from two cellular models of breast cancer, BT474 (HER2+/ER+) and SKBR3 (HER2+/ER-), using two-dimensional electrophoresis and MALDI-TOF mass spectrometry. Protein interaction networks and canonical pathways were extracted from the Ingenuity Pathway Knowledgebase (IPK) based on association with the observed pattern of differentially expressed proteins.
  
  
  RESULTS
  Of the 304 spots that were picked, 167 protein spots were identified. A threshold of 1.5-fold was used to select 62 proteins used in the analysis. IPK analysis suggested that metabolic pathways were highly associated with protein expression in SKBR3 cells while cell motility pathways were highly associated with BT474 cells. Inferred protein networks were confirmed by observing an up-regulation of IGF-1R and profilin in BT474 and up-regulation of Ras and enolase in SKBR3 using western blot.
  
  
  CONCLUSIONS
  When interpreted in the context of prior information, our results suggest that the overall patterns of differential protein expression obtained from limited samples can still aid in clinical decision making by providing an estimate of the predominant pathways that underpin cellular phenotype.
authors.affiliation: Department of Chemical Engineering, West Virginia University College of Engineering and Mineral Resources, West Virginia University, Morgantown, WV 26506, USA.
authors.forename: Yogesh M
authors.initials: YM
authors.lastname: Kulkarni
authors.forename: Vivian
authors.initials: V
authors.lastname: Suarez
authors.forename: David J
authors.initials: DJ
authors.lastname: Klinke
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism*; D015153:Blotting, Western; D001943:Breast Neoplasms / Q000188:drug therapy / Q000378:metabolism*; D045744:Cell Line, Tumor; D030562:Databases, Protein; D015180:Electrophoresis, Gel, Two-Dimensional; D005260:Female; D006801:Humans; D018579:Patient Selection; D010449:Peptide Mapping; D010641:Phenotype; D057285:Precision Medicine; D040901:Proteomics / Q000379:methods; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism*; D011960:Receptors, Estrogen / Q000378:metabolism*; D015203:Reproducibility of Results; D015398:Signal Transduction / Q000187:drug effects; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D014408:Biomarkers, Tumor; D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; C508053:ERBB2 protein, human