Department of Statistics, Florida State University, Tallahassee, FL, 32306, USA.
Department of Chemistry &Biochemistry, Florida State University, Tallahassee, FL, 32306, USA.
Sci Rep. 2017 Mar 3;7:43294. doi: 10.1038/srep43294.
Choosing the optimal chemotherapy regimen is still an unmet medical need for breast cancer patients. In this study, we reanalyzed data from seven independent data sets with totally 1079 breast cancer patients. The patients were treated with three different types of commonly used neoadjuvant chemotherapies: anthracycline alone, anthracycline plus paclitaxel, and anthracycline plus docetaxel. We developed random forest models with variable selection using both genetic and clinical variables to predict the response of a patient using pCR (pathological complete response) as the measure of response. The models were then used to reassign an optimal regimen to each patient to maximize the chance of pCR. An independent validation was performed where each independent study was left out during model building and later used for validation. The expected pCR rates of our method are significantly higher than the rates of the best treatments for all the seven independent studies. A validation study on 21 breast cancer cell lines showed that our prediction agrees with their drug-sensitivity profiles. In conclusion, the new strategy, called PRES (Personalized REgimen Selection), may significantly increase response rates for breast cancer patients, especially those with HER2 and ER negative tumors, who will receive one of the widely-accepted chemotherapy regimens.
为乳腺癌患者选择最佳化疗方案仍是未满足的医疗需求。在这项研究中，我们重新分析了来自 7 个独立数据集的总共 1079 名乳腺癌患者的数据。这些患者接受了三种不同类型的常用新辅助化疗：单独使用蒽环类药物、蒽环类药物加紫杉醇和蒽环类药物加多西他赛。我们使用遗传和临床变量开发了具有变量选择的随机森林模型，以 pCR（病理完全缓解）作为反应的衡量标准来预测患者的反应。然后，我们使用这些模型重新为每个患者分配最佳方案，以最大程度地提高 pCR 的机会。我们进行了一项独立验证，即在构建模型期间排除每个独立研究，并在之后将其用于验证。与所有 7 项独立研究的最佳治疗方法相比，我们方法的预期 pCR 率明显更高。对 21 种乳腺癌细胞系的验证研究表明，我们的预测与它们的药物敏感性谱一致。总之，这种新策略称为 PRES（个性化方案选择），可能会显著提高乳腺癌患者的反应率，特别是那些接受广泛接受的化疗方案之一的 HER2 和 ER 阴性肿瘤患者。
