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Prediction of signaling cross-talks contributing to acquired drug resistance in breast cancer cells by Bayesian statistical modeling

机译:通过贝叶斯统计模型预测导致乳腺癌细胞获得性耐药的信号串扰

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摘要

BackgroundInitial success of inhibitors targeting oncogenes is often followed by tumor relapse due to acquired resistance. In addition to mutations in targeted oncogenes, signaling cross-talks among pathways play a vital role in such drug inefficacy. These include activation of compensatory pathways and altered activities of key effectors in other cell survival and growth-associated pathways.
机译:背景技术针对致癌基因的抑制剂最初的成功通常是由于获得性耐药导致肿瘤复发。除了靶向致癌基因中的突变外,信号通路之间的相互干扰在此类药物无效中也起着至关重要的作用。这些包括补偿性途径的激活和其他细胞存活和生长相关途径中关键效应子的活性改变。

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