Prognostic discrimination using a 70-gene signature among patients with estrogen receptor-positive breast cancer and an intermediate 21-gene recurrence score
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- Prognostic discrimination using a 70-gene signature among patients with estrogen receptor-positive breast cancer and an intermediate 21-gene recurrence score
- S G Ahn; H M Lee; H W Lee; S A Lee; S R Lee; S H Leem; J Jeong; In-Sun Chu
- Bibliographic Citation
- International Journal of Molecular Sciences, vol. 14, no. 12, pp. 23685-23699
- Publication Year
- The Oncotype DX® recurrence score (RS) predictor has been clinically utilized to appropriately select adjuvant chemotherapy for patients with estrogen receptor (ER)-positive early breast cancer. However, the selection of chemotherapy for patients with intermediate RSs remains controversial. We assessed the prognostic value of a 70-gene signature (70GS) among patients with ER-positive breast cancer and intermediate RSs. In addition, we sought to identify genes associated with poor 70GS scores based on gene expression profiling (GEP). GEP was performed using gene expression data from 186 patients with ER-positive breast cancer. The RS and 70GS score were calculated on the basis of GEP. Among 186 patients, 82 ER-positive patients with intermediate RSs were identified. These patients were stratified by 70GS, overall survival (OS) significantly differed according to 70GS (p = 0.013). In a supervised hierarchical analysis according to 70GS, the expression of several representative genes for cell proliferation was significantly higher in the poor 70GS cluster than in the good 70GS cluster. Furthermore, among these patients, FOXM1, AURKA, AURKB, and BIRC5 displayed prognostic significance for OS. In conclusion, 70GS can help to discriminate survival differences among ER-positive patients with intermediate RSs. FOXM1, AURKA, AURKB, and BIRC5, are associated with poor 70GS scores.
- 70-gene signature; AURKA; AURKB; BIRC5; Breast cancer; Estrogen receptor; FOXM1; Recurrence score
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- Division of Biomedical Research > Genome Editing Research Center > 1. Journal Articles
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