title: The needle in the haystack: application of breast fine-needle aspirate samples to quantitative protein microarray technology.
abstract: BACKGROUND
  There is an unmet clinical need for economic, minimally invasive procedures that use a limited number of cells for the molecular profiling of tumors in individual patients. Reverse-phase protein microarray (RPPM) technology has been applied successfully to the quantitative analysis of breast, ovarian, prostate, and colorectal cancers using frozen surgical specimens.
  
  
  METHODS
  For this report, the authors investigated the novel use of RPPM technology for the analysis of both archival cytology aspirate smears and frozen fine-needle aspiration (FNA) samples. RPPMs were printed with 63 breast FNA samples that were obtained before, during, and after treatment from 21 patients who were enrolled in a Phase II trial of neoadjuvant capecitabine and docetaxel therapy for breast cancer.
  
  
  RESULTS
  Based on an MCF7 cell line model of breast adenocarcinoma, the sensitivity of the RPPM detection method was in the femtomolar range with a coefficient of variance <13.5% for the most dilute sample. Assay linearity was noted from 1.0 microg/microL to 7.8 ng/microL total protein/array spot (R(2) = 0.9887) for a membrane receptor protein (epidermal growth factor receptor; R(2) = 0.9935).
  
  
  CONCLUSIONS
  The results from this study indicated that low-abundance analytes and phosphorylated and nonphosphorylated proteins in specimens that consist of a few thousand cells obtained through FNA can be quantified with RPPM technology. The ability to monitor the in vivo state of cell-signaling proteins before and after treatment potentially will augment the ability to design individualized therapy regimens through the mapping of aberrant cell-signaling phenotypes. The mapping of these protein pathways will further the development of rational drug targets.
authors.affiliation: Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. rapkia01@med.nyu.edu
authors.forename: Amy
authors.initials: A
authors.lastname: Rapkiewicz
authors.forename: Virginia
authors.initials: V
authors.lastname: Espina
authors.forename: Jo Anne
authors.initials: JA
authors.lastname: Zujewski
authors.forename: Peter F
authors.initials: PF
authors.lastname: Lebowitz
authors.forename: Armando
authors.initials: A
authors.lastname: Filie
authors.forename: Julia
authors.initials: J
authors.lastname: Wulfkuhle
authors.forename: Kevin
authors.initials: K
authors.lastname: Camphausen
authors.forename: Emanuel F
authors.initials: EF
authors.lastname: Petricoin
authors.forename: Lance A
authors.initials: LA
authors.lastname: Liotta
authors.forename: Andrea
authors.initials: A
authors.lastname: Abati
mesh_terms: D001499:Bayes Theorem; D044963:Biopsy, Fine-Needle / Q000379:methods; D001940:Breast / Q000378:metabolism / Q000473:pathology; D001943:Breast Neoplasms / Q000378:metabolism* / Q000473:pathology; D045744:Cell Line, Tumor; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D046228:Microarray Analysis / Q000379:methods*; D010750:Phosphoproteins / Q000032:analysis; D011494:Protein Kinases / Q000032:analysis; D020543:Proteome / Q000032:analysis*; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results
chemical_list: D010750:Phosphoproteins; D020543:Proteome; D011494:Protein Kinases