Department of Biomedical Engineering, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, Portland, Oregon.
Division of Surgical Oncology, Department of Surgery, Centre Hospitalier de l'Université de Montréal (CHUM), Centre de Recherche du CHUM, l'Université de Montréal, Québec, Canada.
Mol Cancer Ther. 2017 Dec;16(12):2892-2901. doi: 10.1158/1535-7163.MCT-17-0170. Epub 2017 Sep 27.
Effective treatment of patients with triple-negative (ER-negative, PR-negative, HER2-negative) breast cancer remains a challenge. Although PARP inhibitors are being evaluated in clinical trials, biomarkers are needed to identify patients who will most benefit from anti-PARP therapy. We determined the responses of three PARP inhibitors (veliparib, olaparib, and talazoparib) in a panel of eight triple-negative breast cancer cell lines. Therapeutic responses and cellular phenotypes were elucidated using high-content imaging and quantitative immunofluorescence to assess markers of DNA damage (53BP1) and apoptosis (cleaved PARP). We determined the pharmacodynamic changes as percentage of cells positive for 53BP1, mean number of 53BP1 foci per cell, and percentage of cells positive for cleaved PARP. Inspired by traditional dose-response measures of cell viability, an EC value was calculated for each cellular phenotype and each PARP inhibitor. The EC values for both 53BP1 metrics strongly correlated with IC values for each PARP inhibitor. Pathway enrichment analysis identified a set of DNA repair and cell cycle-associated genes that were associated with 53BP1 response following PARP inhibition. The overall accuracy of our 63 gene set in predicting response to olaparib in seven breast cancer patient-derived xenograft tumors was 86%. In triple-negative breast cancer patients who had not received anti-PARP therapy, the predicted response rate of our gene signature was 45%. These results indicate that 53BP1 is a biomarker of response to anti-PARP therapy in the laboratory, and our DNA damage response gene signature may be used to identify patients who are most likely to respond to PARP inhibition. .
有效治疗三阴性(雌激素受体阴性、孕激素受体阴性、HER2 阴性)乳腺癌仍然是一个挑战。虽然 PARP 抑制剂正在临床试验中进行评估,但需要生物标志物来识别最能从抗 PARP 治疗中获益的患者。我们在一个包含八种三阴性乳腺癌细胞系的小组中确定了三种 PARP 抑制剂(veliparib、olaparib 和 talazoparib)的反应。使用高内涵成像和定量免疫荧光来评估 DNA 损伤(53BP1)和细胞凋亡(cleaved PARP)标志物,阐明了治疗反应和细胞表型。我们确定了作为 53BP1 阳性细胞的百分比、每个细胞的 53BP1 焦点的平均数量以及 cleaved PARP 阳性细胞的百分比的药效学变化。受细胞活力传统剂量反应测量的启发,为每个细胞表型和每个 PARP 抑制剂计算了 EC 值。两种 53BP1 指标的 EC 值与每个 PARP 抑制剂的 IC 值强烈相关。通路富集分析确定了一组与 PARP 抑制后 53BP1 反应相关的 DNA 修复和细胞周期相关基因。我们的 63 个基因集在预测 7 个乳腺癌患者来源异种移植肿瘤对 olaparib 的反应中的总体准确性为 86%。在未接受抗 PARP 治疗的三阴性乳腺癌患者中,我们基因特征预测的反应率为 45%。这些结果表明 53BP1 是实验室中抗 PARP 治疗反应的生物标志物,并且我们的 DNA 损伤反应基因特征可用于识别最有可能对 PARP 抑制有反应的患者。