title: Subtype classification for prediction of prognosis of breast cancer from a biomarker panel: correlations and indications.
abstract: BACKGROUND
  Hormone receptors, including the estrogen receptor and progesterone receptor, human epidermal growth factor receptor 2 (HER2), and other biomarkers like Ki67, epidermal growth factor receptor (EGFR, also known as HER1), the androgen receptor, and p53, are key molecules in breast cancer. This study evaluated the relationship between HER2 and hormone receptors and explored the additional prognostic value of Ki67, EGFR, the androgen receptor, and p53.
  
  
  METHODS
  Quantitative determination of HER2 and EGFR was performed in 240 invasive breast cancer tissue microarray specimens using quantum dot (QD)-based nanotechnology. We identified two subtypes of HER2, ie, high total HER2 load (HTH2) and low total HER2 load (LTH2), and three subtypes of hormone receptor, ie, high hormone receptor (HHR), low hormone receptor (LHR), and no hormone receptor (NHR). Therefore, breast cancer patients could be divided into five subtypes according to HER2 and hormone receptor status. Ki67, p53, and the androgen receptor were determined by traditional immunohistochemistry techniques. The relationship between hormone receptors and HER2 was investigated and the additional value of Ki67, EGFR, the androgen receptor, and p53 for prediction of 5-year disease-free survival was assessed.
  
  
  RESULTS
  In all patients, quantitative determination showed a statistically significant (P<0.001) negative correlation between HER2 and the hormone receptors and a significant positive correlation (P<0.001) between the estrogen receptor and the progesterone receptor (r=0.588), but a significant negative correlation (P<0.001, r=-0.618) with the HHR subtype. There were significant differences between the estrogen receptor, progesterone receptor, and HER2 subtypes with regard to total HER2 load and hormone receptor subtypes. The rates of androgen receptor and p53 positivity were 46.3% and 57.0%, respectively. Other than the androgen receptor, differences in expression of Ki67, EGFR, and p53 did not achieve statistical significance (P>0.05) between the five subtypes. EGFR and Ki67 had prognostic significance for 5-year disease-free survival in univariate analysis, but the androgen receptor and p53 did not. Multivariate analysis identified that EGFR expression had predictive significance for 5-year disease-free survival in hormone-receptor positive patients and in those with the lymph node-positive breast cancer subtype.
  
  
  CONCLUSIONS
  Hormone receptor expression was indeed one of the molecular profiles in the subtypes identified by quantitative HER2 and vice versa. EGFR status may provide discriminative prognostic information in addition to HER2 and hormone receptor status, and should be integrated into routine practice to help formulate more specific prediction of the prognosis and appropriate individualized treatment.
authors.affiliation: Department of Breast and Thyroid Surgery, Wuhan University, Renmin Hospital, Wuhan, People's Republic of China.
authors.forename: Chuang
authors.initials: C
authors.lastname: Chen
authors.affiliation: Department of Oncology, Zhongnan Hospital of Wuhan University and Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, Wuhan, People's Republic of China ; Department of Pathology, The Central Hospital of Wuhan, Wuhan, People's Republic of China.
authors.forename: Jing-Ping
authors.initials: JP
authors.lastname: Yuan
authors.affiliation: Department of Breast and Thyroid Surgery, Wuhan University, Renmin Hospital, Wuhan, People's Republic of China.
authors.forename: Wen
authors.initials: W
authors.lastname: Wei
authors.affiliation: Department of Breast and Thyroid Surgery, Wuhan University, Renmin Hospital, Wuhan, People's Republic of China.
authors.forename: Yi
authors.initials: Y
authors.lastname: Tu
authors.affiliation: Department of Breast and Thyroid Surgery, Wuhan University, Renmin Hospital, Wuhan, People's Republic of China.
authors.forename: Feng
authors.initials: F
authors.lastname: Yao
authors.affiliation: Medical School of Jingchu University of Technology, Jingmen, People's Republic of China.
authors.forename: Xue-Qin
authors.initials: XQ
authors.lastname: Yang
authors.affiliation: Department of Breast and Thyroid Surgery, Wuhan University, Renmin Hospital, Wuhan, People's Republic of China.
authors.forename: Jin-Zhong
authors.initials: JZ
authors.lastname: Sun
authors.affiliation: Department of Breast and Thyroid Surgery, Wuhan University, Renmin Hospital, Wuhan, People's Republic of China.
authors.forename: Sheng-Rong
authors.initials: SR
authors.lastname: Sun
authors.affiliation: Department of Oncology, Zhongnan Hospital of Wuhan University and Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, Wuhan, People's Republic of China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Li
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism*; D001943:Breast Neoplasms / Q000145:classification* / Q000378:metabolism*; D066246:ErbB Receptors / Q000378:metabolism; D005260:Female; D006801:Humans; D019394:Ki-67 Antigen / Q000378:metabolism; D050997:Nanomedicine; D036103:Nanotechnology; D011379:Prognosis; D045663:Quantum Dots; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D011944:Receptors, Androgen / Q000378:metabolism; D011960:Receptors, Estrogen / Q000378:metabolism; D011980:Receptors, Progesterone / Q000378:metabolism; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism
chemical_list: D014408:Biomarkers, Tumor; D066246:ErbB Receptors; D019394:Ki-67 Antigen; D018719:Erb-b2 Receptor Tyrosine Kinases; D011944:Receptors, Androgen; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone; D016159:Tumor Suppressor Protein p53; C410798:AR protein, human; C495901:TP53 protein, human; C512478:EGFR protein, human; C508053:ERBB2 protein, human
keywords: breast cancer; molecular classification; prediction; prognosis; quantum dots