Gene expression profiling in prognosis of distant recurrence in HR-positive and HER2-negative breast cancer patients

基因表达谱分析在HR阳性和HER2阴性乳腺癌患者远处复发预后中的应用

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Abstract

There had been several studies using gene-expression profiling in predicting distant recurrence in breast cancer. In this study, we developed an 18-gene classifier (18-GC) to predict distant recurrence of breast cancer and compared it with the 21-gene panel (Oncotype DX(®), ODx) in performance. Included were 224 breast cancer patients with positive hormonal receptor (HR+) and negative human epidermal growth factor receptor 2 (HER2-). We compared the demographic, clinical, and survival information of the patients, and further compared the prediction of recurrence risk obtained by using the 18-GC with that by ODx. To have the best combined sensitivity and specificity, receiver operating characteristics (ROC) curve analysis was performed to determine the cutoff values for several breakpoint scores. For the new 18-GC, a breakpoint score of 21 was adopted to produce a combined highest sensitivity (95%) and specificity (39%) in detecting distant recurrence. At this breakpoint score, 164 of the 224 patients were classified by the 18-GC in the same risk level as by ODx, giving a concordance rate of 73%. Along with patient age and tumor stage, this 18-GC was found to be an independent significant prognostic factor of distant metastasis of breast cancer. We have thus created a new gene panel assay for prediction of distant recurrence in HR+ and HER2- breast cancer patients. With a high concordance rate with ODx, this new assay may serve as a good tool for individual breast cancer patients to make an informed decision on whether adjuvant chemotherapy should be performed post-surgery.

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