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

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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.

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Abbreviations

ER:

Estrogen receptor

PR:

Progesterone receptor

HER2:

Human epidermal growth factor receptor 2

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Acknowledgments

The authors acknowledge Knowledge Cluster Initiative, Scientific Research on Priority Areas programs of the Ministry of Education, Culture, Sports, Science and Technology of Japan and Comprehensive 10-Year Strategy for Cancer Control program of the Ministry of Health, Labour and Welfare, Japan.

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Authors and Affiliations

  1. Department of Breast and Endocrine Surgery, Osaka University Graduate School of Medicine, 2-2-E10 Yamadaoka, Suita-shi, Osaka, 565-0871, Japan

    Yasuto Naoi, Tomonori Tanei, Ryo Tsunashima, Naoomi Tominaga, Seung Jin Kim, Tetsuya Taguchi, Yasuhiro Tamaki & Shinzaburo Noguchi

  2. Central Research Laboratories, Sysmex Corporation, Kobe, Japan

    Kazuki Kishi & Yosuke Baba

Authors
  1. Yasuto Naoi
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  2. Kazuki Kishi
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  3. Tomonori Tanei
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  4. Ryo Tsunashima
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  5. Naoomi Tominaga
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  6. Yosuke Baba
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  7. Seung Jin Kim
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  8. Tetsuya Taguchi
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  9. Yasuhiro Tamaki
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  10. Shinzaburo Noguchi
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Corresponding author

Correspondence to Shinzaburo Noguchi.

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Naoi, Y., Kishi, K., Tanei, T. et al. Development of 95-gene classifier as a powerful predictor of recurrences in node-negative and ER-positive breast cancer patients. Breast Cancer Res Treat 128, 633–641 (2011). https://doi.org/10.1007/s10549-010-1145-z

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  • DOI: https://doi.org/10.1007/s10549-010-1145-z

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