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Featured researches published by Kazuki Kishi.


Cancer | 2011

Prediction of pathologic complete response to sequential paclitaxel and 5-fluorouracil/epirubicin/cyclophosphamide therapy using a 70-gene classifier for breast cancers.

Yasuto Naoi; Kazuki Kishi; Tomonori Tanei; Ryo Tsunashima; Naoomi Tominaga; Yosuke Baba; Seung Jin Kim; Tetsuya Taguchi; Yasuhiro Tamaki; Shinzaburo Noguchi

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.


Cancer Letters | 2011

Gene expression signature of TP53 but not its mutation status predicts response to sequential paclitaxel and 5-FU/epirubicin/cyclophosphamide in human breast cancer

Kazuteru Oshima; Yasuto Naoi; Kazuki Kishi; Yukiko Nakamura; Takashi Iwamoto; Kenzo Shimazu; Takahiro Nakayama; Seung Jin Kim; Yosuke Baba; Yasuhiro Tamaki; Shinzaburo Noguchi

PURPOSE The aim of this study was to determine whether TP53 mutation status (MS) can predict response of breast cancer to paclitaxel followed by 5-FU/epirubicin/cyclophosphamide (P-FEC). TP53 gene expression signature (GES) was also examined for its predictive capability of response to P-FEC since TP53 GES provides a more accurate measure of the functional configuration of TP53. METHODS Tumor samples were obtained from 72 primary breast cancer patients (stage II/III) before neoadjuvant chemotherapy (P-FEC) and analyzed for identification of TP53 MS (genomic sequencing), TP53 GES (DNA microarray), and p53 protein expression (immunohistochemistry). RESULTS Of 72 breast tumors, 16 were TP53 mutant-type (TP53 mt) and 56 were wild-type (TP53 wt). 29 tumors (40%) were positive for p53 protein by immunohistochemistry. DNA microarray analysis showed that 27 were TP53 mt-like tumors and 45 were TP53 wt-like tumors, depending on the expression signature of the TP53-related 31-genes. There was no statistically significant difference in pathological complete response (pCR) rates between TP53 mt and wt tumors (19% vs 23%) and between p53 positive and negative tumors (24% vs 21%) but TP53 mt-like tumors showed a significantly (P=0.019) higher pCR rate (37%) than TP53 wt-like tumors (13%) (Hazard ratio, 3.82; 95% C.I., 1.20-12.21). CONCLUSIONS TP53 GES, but not TP53 MS and p53 protein expression, is predictive of response to neoadjuvant P-FEC, suggesting that TP53 GES more correctly reflects the functionality of TP53.


Annals of Oncology | 2014

Construction of novel immune-related signature for prediction of pathological complete response to neoadjuvant chemotherapy in human breast cancer

Yoshiaki Sota; Yasuto Naoi; Ryo Tsunashima; Naofumi Kagara; Kenzo Shimazu; Naomi Maruyama; Atsushi Shimomura; Masashi Shimoda; Kazuki Kishi; Yosuke Baba; Seung Jin Kim; Shinzaburo Noguchi

BACKGROUND The aim of this study was to construct a novel prediction model for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) using immune-related gene expression data. PATIENTS AND METHODS DNA microarray data were used to perform a gene expression analysis of tumor samples obtained before NAC from 117 primary breast cancer patients. The samples were randomly divided into the training (n = 58) and the internal validation (n = 59) sets that were used to construct the prediction model for pCR. The model was further validated using an external validation set consisting of 901 patients treated with NAC from six public datasets. RESULTS The training set was used to construct an immune-related 23-gene signature for NAC (IRSN-23) that is capable of classifying the patients as either genomically predicted responders (Gp-R) or non-responders (Gp-NR). IRSN-23 was first validated using an internal validation set, and the results showed that the pCR rate for Gp-R was significantly higher than that obtained for Gp-NR (38 versus 0%, P = 1.04E-04). The model was then tested using an external validation set, and this analysis showed that the pCR rate for Gp-R was also significantly higher (40 versus 11%, P = 4.98E-23). IRSN-23 predicted pCR regardless of the intrinsic subtypes (PAM50) and chemotherapeutic regimens, and a multivariate analysis showed that IRSN-23 was the most important predictor of pCR (odds ratio = 4.6; 95% confidence interval = 2.7-7.7; P = 8.25E-09). CONCLUSION The novel prediction model (IRSN-23) constructed with immune-related genes can predict pCR independently of the intrinsic subtypes and chemotherapeutic regimens.


European Journal of Cancer | 2011

Association between c-myc amplification and pathological complete response to neoadjuvant chemotherapy in breast cancer

Hiroyuki Yasojima; Atsushi Shimomura; Yasuto Naoi; Kazuki Kishi; Yousuke Baba; Kenzo Shimazu; Takahiro Nakayama; Seung Jin Kim; Yasuhiro Tamaki; Shinzaburo Noguchi

BACKGROUND The aim of this study was to investigate whether c-myc amplification in human breast cancer is associated with response to neoadjuvant chemotherapy comprising paclitaxel followed by 5-FU/epirubicin/cyclophosphamide (P-FEC). METHODS Tumour tissue samples were obtained before neoadjuvant chemotherapy (P-FEC) from 100 primary breast cancer patients (stage II/III). C-myc and HER2 amplification were examined by FISH, and oestrogen receptor (ER), progesterone receptor (PR), Ki67, and topoisomerase 2α (TOP2A) expression were examined immunohistochemically. Pathological complete response (pCR) was defined by a complete loss of tumour cells in the breast without any lymph node metastasis. RESULTS C-myc amplification was observed in 40% (40/100) of breast tumours, and was significantly associated with ER-negative tumours (23/40 for ER(-) versus 17/60 for ER(+), P=0.004), high histological grade tumours (11/18 for grade 3 versus 29/82 for grades 1+2, P=0.043) and TOP2A-positive tumours (28/51 for TOP2A(+) versus 12/49 for TOP2A(-), P=0.002). pCR rate was 20% for total patients (10.0% for ER(+) and 35.0% for ER(-)). Further, breast tumours with c-myc amplification (c-myc(+)) showed a significantly (P=0.041) higher pCR rate (12/40) than those without such amplification (c-myc(-)) (8/60). This association between pCR and c-myc amplification was observed in ER-positive tumours (4/17 for c-myc(+) versus 2/43 for c-myc(-), P=0.048) but not in ER-negative tumours (8/23 for c-myc(+) versus 6/17 for c-myc(-), P=0.973). CONCLUSION Our results suggest that c-myc amplification is significantly associated with a high pCR rate to P-FEC in breast tumours, especially in ER-positive tumours.


Cancer | 2011

High genomic grade index associated with poor prognosis for lymph node‐negative and estrogen receptor‐positive breast cancers and with good response to chemotherapy

Yasuto Naoi; Kazuki Kishi; Tomonori Tanei; Ryo Tsunashima; Naoomi Tominaga; Yosuke Baba; Seung Jin Kim; Tetsuya Taguchi; Yasuhiro Tamaki; Shinzaburo Noguchi

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.


Cancer Letters | 2012

Estrogen receptor positive breast cancer identified by 95-gene classifier as at high risk for relapse shows better response to neoadjuvant chemotherapy

Ryo Tsunashima; Yasuto Naoi; Kazuki Kishi; Yosuke Baba; Atsushi Shimomura; Naomi Maruyama; Takahiro Nakayama; Kenzo Shimazu; Seung Jin Kim; Yasuhiro Tamaki; Shinzaburo Noguchi

A 95-gene classifier (95-GC) recently developed by us can predict the risk of relapse for ER-positive and node-negative breast cancer patients with high accuracy. This study investigated association of risk classification by 95-GC with response to neoadjuvant chemotherapy (NAC). Tumor biopsy samples obtained preoperatively from 72 patients with ER-positive breast cancer were classified by 95-GC into high-risk and low-risk for relapse. Pathological complete response (pCR) rate was numerically higher for high-risk (15.8%) than low-risk patients (8.8%) although the difference was not statistically significant. Pathological response evaluated in terms of the pathological partial response (pPR) rate (loss of tumor cells in more than two-thirds of the primary tumor) showed a significant association (P=0.005) between the high-risk patients and a high pPR rate. Besides, external validation study using the public data base (GSE25066) showed that the pCR rate (16.4%) for high-risk patients (n=128) was significantly (P=0.003) higher than for low-risk patients (5.7%) (n=159). These results demonstrate that the high-risk patients for relapse show a higher sensitivity to chemotherapy and thus are likely to benefit more from adjuvant chemotherapy.


Cancer Letters | 2012

70-Gene classifier for differentiation between paclitaxel- and docetaxel-sensitive breast cancers

Yasuto Naoi; Tomonori Tanei; Kazuki Kishi; Ryo Tsunashima; Naoomi Tominaga; Yosuke Baba; Takahiro Nakayama; Kenzo Shimazu; Seung Jin Kim; Yasuhiro Tamaki; Shinzaburo Noguchi

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.


Breast Cancer Research and Treatment | 2011

Development of 95-gene classifier as a powerful predictor of recurrences in node-negative and ER-positive breast cancer patients

Yasuto Naoi; Kazuki Kishi; Tomonori Tanei; Ryo Tsunashima; Naoomi Tominaga; Yosuke Baba; Seung Jin Kim; Tetsuya Taguchi; Yasuhiro Tamaki; Shinzaburo Noguchi


Archive | 2006

Method of discriminating cancer and atypical cells and cell analyzer

Masaki Ishisaka; Yasuyuki Imura; Kazuki Kishi


Archive | 2007

Methods of discriminating cancer/atypical cell and particle agglomerate, and cytoanalyzer

Masaki Ishisaka; Yasuyuki Imura; Kazuki Kishi

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