https://scholars.lib.ntu.edu.tw/handle/123456789/633536
Title: | Comparing Genetic Risk and Clinical Risk Classification in Luminal-like Breast Cancer Patients Using a 23-Gene Classifier | Authors: | Huang, Chi-Cheng Chen, Ting-Hao Liu, Liang-Chih CHIUN-SHENG HUANG Liang, Ji-An Hsu, Yu-Chen Hsieh, Chia-Ming Huang, Sean-Lin Shih, Kuan-Hui Tseng, Ling-Ming |
Keywords: | Asian; adjuvant! online; gene expression profile; luminal type breast cancer; recurrence | Issue Date: | 19-Dec-2022 | Journal Volume: | 14 | Journal Issue: | 24 | Source: | Cancers | Abstract: | Background: A 23-gene classifier has been developed based on gene expression profiles of Taiwanese luminal-like breast cancer. We aim to stratify risk of relapse and identify patients who may benefit from adjuvant chemotherapy based on genetic model among distinct clinical risk groups. Methods: There were 248 luminal (hormone receptor-positive and human epidermal growth factor receptor II-negative) breast cancer patients with 23-gene classifier results. Using the modified Adjuvant! Online definition, clinical high/low-risk groups were tabulated with the genetic model. The primary endpoint was a recurrence-free interval (RFI) at 5 years. Results: There was a significant difference between the high/low-risk groups defined by the 23-gene classifier for the 5-year prognosis of recurrence (16 recurrences in high-risk and 3 recurrences in low-risk; log-rank test: p < 0.0001). Among the clinically high-risk group, the 5-year RFI of high risk defined by the 23-gene classifier was significantly higher than that of the low-risk group (15 recurrences in high-risk and 2 recurrences in low-risk; log-rank test: p < 0.0001). Conclusion: This study showed that 23-gene classifier can be used to stratify clinically high-risk patients into distinct survival patterns based on genomic risks and displays the potentiality to guide adjuvant chemotherapy. The 23-gene classifier can provide a better estimation of breast cancer prognosis which can help physicians make a better treatment decision. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/633536 | ISSN: | 2072-6694 | DOI: | 10.3390/cancers14246263 |
Appears in Collections: | 醫學系 |
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