title: Prediction of pathologic complete response to sequential paclitaxel and 5-fluorouracil/epirubicin/cyclophosphamide therapy using a 70-gene classifier for breast cancers.
abstract: BACKGROUND
  Sequential administration of paclitaxel plus combined fluorouracil, epirubicin, and cyclophosphamide (P-FEC) is 1 of the most common neoadjuvant chemotherapies for patients with primary breast cancer and produces pathologic complete response (pCR) rates of 20% to 30%. However, a predictor of pCR to this chemotherapy has yet to be developed. The authors developed such a predictor by using a proprietary DNA microarray for gene expression analysis of breast tumor tissues.
  
  
  METHODS
  Tumor samples were obtained from 84 patients with breast cancer by core-needle biopsy before the patients received P-FEC, and the gene expression profile was analyzed in those samples to construct a classifier for predicting pCR to P-FEC. In addition, the authors analyzed the gene expression profile of tumor tissues that were obtained at surgery from 105 patients with lymph node-negative and estrogen receptor-positive breast cancer who received adjuvant hormone therapy alone to determine the prognostic significance of the classifier.
  
  
  RESULTS
  The 70-gene classifier for predicting pCR to P-FEC was constructed by using the training set (n = 50) and subsequently was validated successfully in the validation set (n = 34), revealing high sensitivity (88%; 95% confidence interval [CI], 47%-100%) and high negative predictive value (93%; 95% CI, 68%-100%). Specificity and positive predictive value were 54% (95% CI, 33%-73%) and 37% (95% CI, 16%-62%), respectively. Among the various parameters (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and Ki-67 status, etc), the 70-gene classifier had the strongest association with pCR (P = .015). In an additional study, genetically assumed complete responders were associated significantly (P = .047) with a poor prognosis.
  
  
  CONCLUSIONS
  The 70-gene classifier that was constructed for predicting pCR to P-FEC for breast tumors was successful, with high sensitivity and high negative predictive value. The classifier also appeared to be useful for predicting the prognosis of patients with lymph node-negative and estrogen receptor-positive breast cancer who receive adjuvant hormone therapy alone.
authors.affiliation: Department of Breast and Endocrine Surgery, Osaka University Graduate School of Medicine, Osaka, Japan.
authors.forename: Yasuto
authors.initials: Y
authors.lastname: Naoi
authors.forename: Kazuki
authors.initials: K
authors.lastname: Kishi
authors.forename: Tomonori
authors.initials: T
authors.lastname: Tanei
authors.forename: Ryo
authors.initials: R
authors.lastname: Tsunashima
authors.forename: Naoomi
authors.initials: N
authors.lastname: Tominaga
authors.forename: Yosuke
authors.initials: Y
authors.lastname: Baba
authors.forename: Seung Jin
authors.initials: SJ
authors.lastname: Kim
authors.forename: Tetsuya
authors.initials: T
authors.lastname: Taguchi
authors.forename: Yasuhiro
authors.initials: Y
authors.lastname: Tamaki
authors.forename: Shinzaburo
authors.initials: S
authors.lastname: Noguchi
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use*; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000235:genetics* / Q000473:pathology; D003520:Cyclophosphamide / Q000008:administration & dosage*; D015251:Epirubicin / Q000008:administration & dosage*; D005260:Female; D005472:Fluorouracil / Q000008:administration & dosage*; D020869:Gene Expression Profiling; D006801:Humans; D008875:Middle Aged; D020360:Neoadjuvant Therapy; D017239:Paclitaxel / Q000008:administration & dosage*; D011237:Predictive Value of Tests; D011379:Prognosis; D011960:Receptors, Estrogen / Q000032:analysis; D012680:Sensitivity and Specificity
chemical_list: D011960:Receptors, Estrogen; D015251:Epirubicin; D003520:Cyclophosphamide; D017239:Paclitaxel; D005472:Fluorouracil