Naoomi Tominaga

Osaka City University, Ōsaka-shi, Osaka-fu, Japan

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Publications (5)27.12 Total impact

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    ABSTRACT: Background The aim of this study was to investigate the clinicopathological characteristics of GATA binding protein 3 (GATA3)-positive breast cancers as well as the association of GATA3 expression with response to chemotherapy.Patients and methodsTumor specimens obtained before neoadjuvant chemotherapy [paclitaxel followed by 5-fluorouracil/epirubicin/cyclophosphamide)] from breast cancer patients (n = 130) were subjected to immunohistochemical and mutational analysis of GATA3 and DNA microarray gene expression analysis for intrinsic subtyping.ResultsSeventy-four tumors (57%) were immunohistochemically positive for GATA3. GATA3-positive tumors were significantly more likely to be lobular cancer, estrogen receptor (ER)-positive, progesterone receptor (PgR)-positive, Ki67-negative, and luminal A tumors. Somatic mutations were found in only three tumors. Pathological complete response (pCR) was observed in 8 (11%) GATA3-positive tumors and in 22 (39%) GATA3-negative tumors. Multivariate analysis showed that tumor size, human epidermal growth factor receptor 2 (HER2), and GATA3 were independent predictors of pCR.ConclusionsGATA3-positive breast cancers showed luminal differentiation characterized by high ER expression and were mostly classified as luminal-type tumors following intrinsic subtyping. Interestingly, GATA3 was an independent predictor of response to chemotherapy, suggesting that GATA3 might be clinically useful as a predictor of a poor response to chemotherapy.
    Annals of Oncology 07/2012; · 7.38 Impact Factor
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    ABSTRACT: Association of estrogen receptor (ER), progesterone receptor (PR), HER2, Ki67 and 70-gene classifier (70-GC) with a response to paclitaxel (PAC) (n=79) or docetaxel (DOC) (n=55) was investigated in the neoadjuvant setting for breast cancer patients. Sensitivity of breast tumors to PAC, but not to DOC, was found to be significantly associated with ER negativity (P=0.003), PR negativity (P=0.007), and Ki67 positivity (P=0.007). Breast tumors classified into the responders by 70-GC showed a significantly (P=0.005) higher reduction rate to PAC and interestingly a significantly (P=0.009) lower reduction rate to DOC than those classified into the non-responders by 70-GC, suggesting that 70-GC might be useful for the differentiation of PAC-sensitive and DOC-sensitive breast tumors.
    Cancer letters 01/2012; 314(2):206-12. · 4.86 Impact Factor
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    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.
    Breast Cancer Research and Treatment 08/2011; 128(3):633-41. · 4.47 Impact Factor
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    ABSTRACT: 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. 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. 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. 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.
    Cancer 02/2011; 117(16):3682-90. · 5.20 Impact Factor
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    ABSTRACT: BACKGROUND:The aim of the present study was to investigate the prognostic value of the genomic grade index for lymph node-negative and estrogen receptor (ER)-positive breast cancers of Japanese women treated with adjuvant hormonal therapy alone, as well as the relation between genomic grade index and pathological complete response (CR) to neoadjuvant chemotherapy.METHODS:Genomic grade index was determined by DNA microarray (U133plus2.0; Affymetrix, Santa Clara, Calif) in tumor tissues obtained from lymph node-negative and ER-positive breast cancers (n = 105) treated with adjuvant hormonal therapy alone or in breast tumor biopsy specimens (n = 84, Mammotome) obtained before neoadjuvant chemotherapy (paclitaxel followed by 5-fluorouracil/epirubicin/cyclophosphomide) to investigate the prognostic and predictive values of genomic grade index.RESULTS:Recurrence-free survival of patients with high genomic grade index tumors was significantly (P < .001) lower than that of patients with low genomic grade index tumors (55% vs 88%, 10 years after surgery). Multivariate analysis demonstrated that genomic grade index was the most important and significant predictive factor for disease recurrence (P = .013) independently of other prognostic factors, including tumor size, histological grade, progesterone receptor, human epidermal growth receptor 2, and Ki67. High genomic grade index tumors showed a significantly (P = .022) higher pathological CR rate for neoadjuvant chemotherapy than low genomic grade index tumors (31.9% [15 of 47] vs 10.8% [4 of 37]).CONCLUSIONS:Genomic grade index is a powerful prognostic factor for lymph node-negative and ER-positive tumors treated with adjuvant hormonal therapy alone, and high genomic grade index tumors are more likely to respond to chemotherapy. Genomic grade index also appears to be very useful for decision making regarding the need for adjuvant chemotherapy for lymph node-negative and ER-positive breast cancers. Cancer 2011. © 2010 American Cancer Society.
    Cancer 01/2011; 117(3):472 - 479. · 5.20 Impact Factor