title: Development of 95-gene classifier as a powerful predictor of recurrences in node-negative and ER-positive breast cancer patients.
abstract: Our aim was to develop an accurate diagnostic system using gene expression analysis by means of DNA microarray for prognosis of node-negative and estrogen receptor (ER)-positive breast cancer patients in order to identify a subset of patients who can be safely spared adjuvant chemotherapy. A diagnostic system comprising a 95-gene classifier was developed for predicting the prognosis of node-negative and ER-positive breast cancer patients by using already published DNA microarray (gene expression) data (n = 549) as the training set and the DNA microarray data (n = 105) obtained at our institute as the validation set. Performance of the 95-gene classifier was compared with that of conventional prognostic factors as well as of the genomic grade index (GGI) based on the expression of 70 genes. With the 95-gene classifier we could classify the 105 patients in the validation set into a high-risk (n = 44) and a low-risk (n = 61) group with 10-year recurrence-free survival rates of 93 and 53%, respectively (P = 8.6e-7). Multivariate analysis demonstrated that the 95-gene classifier was the most important and significant predictor of recurrence (P = 9.6e-4) independently of tumor size, histological grade, progesterone receptor, HER2, Ki67, or GGI. The 95-gene classifier developed by us can predict the prognosis of node-negative and ER-positive breast cancer patients with high accuracy. The 95-gene classifier seems to perform better than the GGI. As many as 58% of the patients classified into the low-risk group with this classifier could be safely spared adjuvant chemotherapy.
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; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics* / Q000378:metabolism / Q000401:mortality / Q000473:pathology; D016000:Cluster Analysis; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008875:Middle Aged; D011379:Prognosis; D011960:Receptors, Estrogen / Q000378:metabolism*; D012008:Recurrence; D016019:Survival Analysis
chemical_list: D011960:Receptors, Estrogen