The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients.
The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients.
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DOI：
10.1186/s12885-017-3297-2
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发表时间：
2017-05-02
期刊：
影响因子：
3.8
通讯作者：
Cheng C
中科院分区：
文献类型：
--
作者：
Mark KMK;Varn FS;Ung MH;Qian F;Cheng C
新辅助化疗是乳腺癌治疗方案的关键组成部分，患者对该疗法的病理完全反应各不相同。这可能是由于每种肿瘤疾病病理学的分子机制存在差异。开发基因组临床检测来准确区分有反应者和无反应者可以为患者提供针对其个体疾病的最有效的治疗。我们应用之前开发的 E2F4 基因组特征来预测乳腺癌的新辅助化疗反应。针对 5 个独立的乳腺癌新辅助化疗数据集的 1129 名患者样本计算了 E2F4 个体调节活动评分。将 E2F4 特征预测新辅助化疗反应的准确性与 Oncotype DX 和 MammaPrint 预测特征进行比较。在所有数据集中，E2F4 活性水平是新辅助化疗反应的准确预测因子，高 E2F4 分数预测实现病理完全缓解，低分数预测残留病灶。即使根据雌激素受体 (ER) 状态、肿瘤分期和乳腺癌分子亚型对患者进行分层，这些结果仍然显着。与 Oncotype DX 和 MammaPrint 特征相比，我们的 E2F4 特征在预测新辅助化疗反应方面取得了相似的性能，尽管与 ER- 肿瘤相比，所有特征在 ER+ 肿瘤中表现更好。我们的签名的准确性在各个数据集上是可重复的，并且当从 199 个基因签名细化为临床友好的 33 个基因组时，其准确性得以保持。总的来说，我们表明我们的 E2F4 特征在预测患者对新辅助化疗的反应方面是准确的。由于该特征在预测新辅助化疗反应方面与其他临床可用的基因表达测定相比更加完善且具有可比性，因此在评估潜在的治疗方案时应考虑这一点。本文的在线版本 (doi:10.1186/s12885-017-3297-2) 包含补充材料，可供授权用户使用。
Neoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. This is presumably due to differences in the molecular mechanisms that underlie each tumor’s disease pathology. Developing genomic clinical assays that accurately categorize responders from non-responders can provide patients with the most effective therapy for their individual disease. We applied our previously developed E2F4 genomic signature to predict neoadjuvant chemotherapy response in breast cancer. E2F4 individual regulatory activity scores were calculated for 1129 patient samples across 5 independent breast cancer neoadjuvant chemotherapy datasets. Accuracy of the E2F4 signature in predicting neoadjuvant chemotherapy response was compared to that of the Oncotype DX and MammaPrint predictive signatures. In all datasets, E2F4 activity level was an accurate predictor of neoadjuvant chemotherapy response, with high E2F4 scores predictive of achieving pathologic complete response and low scores predictive of residual disease. These results remained significant even after stratifying patients by estrogen receptor (ER) status, tumor stage, and breast cancer molecular subtypes. Compared to the Oncotype DX and MammaPrint signatures, our E2F4 signature achieved similar performance in predicting neoadjuvant chemotherapy response, though all signatures performed better in ER+ tumors compared to ER- ones. The accuracy of our signature was reproducible across datasets and was maintained when refined from a 199-gene signature down to a clinic-friendly 33-gene panel. Overall, we show that our E2F4 signature is accurate in predicting patient response to neoadjuvant chemotherapy. As this signature is more refined and comparable in performance to other clinically available gene expression assays in the prediction of neoadjuvant chemotherapy response, it should be considered when evaluating potential treatment options. The online version of this article (doi:10.1186/s12885-017-3297-2) contains supplementary material, which is available to authorized users.