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Predictive outcome assessment for chemotherapy with neoadjuvant bevacizumab

机译:新型贝伐单抗新辅助化疗的预测结果评估

摘要

In a predictive outcome assessment test for predicting whether a patient undergoing a breast cancer treatment regimen will achieve pathological complete response (pCR), differential gene expression level information are generated for an input set of genes belonging to the TGF-β signaling pathway. The differential gene expression level information compares baseline gene expression level information from a baseline sample (70) of a breast tumor of a patient acquired before initiating (71) a breast cancer therapy regimen to the patient and response gene expression level information from a response sample (72) of the breast tumor acquired after initiating the breast cancer therapy regimen by administering a first dose of bevacizumab to the patient. A pCR prediction for the patient is computed based on the differential gene expression level information for the input set of genes belonging to the TGF-β signaling pathway. Related predictive outcome assessment test development methods are also disclosed.
机译:在用于预测接受乳腺癌治疗方案的患者是否将实现病理完全缓解(pCR)的预测结果评估测试中,针对属于TGF-β信号通路的一组输入基因生成了差异基因表达水平信息。差异基因表达水平信息比较了开始( 71 )乳腺癌治疗之前获得的患者乳腺肿瘤基线样品( 70 )的基线基因表达水平信息方案和通过向患者施用第一剂贝伐单抗开始乳腺癌治疗方案后获得的乳腺癌反应样品( 72 )的反应基因表达水平信息。基于属于TGF-β信号通路的基因输入集的差异基因表达水平信息,为患者计算pCR预测。还公开了相关的预测结果评估测试开发方法。

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