Watters James W, Cheng Chun, Majumder Pradip K, Wang Ruojie, Yalavarthi Sireesha, Meeske Carol, Kong Lingxin, Sun Wenping, Lin Jie, Heyer Joerg, Ware Chris, Winter Christopher, Reilly John F, Demuth Tim, Clark Steve, Chiu M Isabel, Robinson Murray O, Kohl Nancy, Kannan Karuppiah
Department of Molecular Profiling, Merck Research Laboratories, North Wales, Pennsylvania 19454, USA.
Cancer Res. 2009 Dec 1;69(23):8949-57. doi: 10.1158/0008-5472.CAN-09-1544. Epub 2009 Nov 10.
Notch pathway signaling plays a fundamental role in normal biological processes and is frequently deregulated in many cancers. Although several hypotheses regarding cancer subpopulations most likely to respond to therapies targeting the Notch pathway have been proposed, clinical utility of these predictive markers has not been shown. To understand the molecular basis of gamma-secretase inhibitor (GSI) sensitivity in breast cancer, we undertook an unbiased, de novo responder identification study using a novel genetically engineered in vivo breast cancer model. We show that tumors arising from this model are heterogeneous on the levels of gene expression, histopathology, growth rate, expression of Notch pathway markers, and response to GSI treatment. In addition, GSI treatment of this model was associated with inhibition of Hes1 and proliferation markers, indicating that GSI treatment inhibits Notch signaling. We then identified a pretreatment gene expression signature comprising 768 genes that is significantly associated with in vivo GSI efficacy across 99 tumor lines. Pathway analysis showed that the GSI responder signature is enriched for Notch pathway components and inflammation/immune-related genes. These data show the power of this novel in vivo model system for the discovery of biomarkers predictive of response to targeted therapies, and provide a basis for the identification of human breast cancers most likely to be sensitive to GSI treatment.
Notch信号通路在正常生物学过程中发挥着重要作用，且在许多癌症中经常失调。尽管已经提出了几种关于最有可能对靶向Notch通路的疗法产生反应的癌症亚群的假说，但这些预测标志物的临床实用性尚未得到证实。为了了解乳腺癌中γ-分泌酶抑制剂（GSI）敏感性的分子基础，我们使用一种新型的基因工程体内乳腺癌模型进行了一项无偏倚的、从头开始的反应者鉴定研究。我们发现，源自该模型的肿瘤在基因表达水平、组织病理学、生长速率、Notch通路标志物表达以及对GSI治疗的反应方面存在异质性。此外，对该模型进行GSI治疗与抑制Hes1和增殖标志物相关，表明GSI治疗可抑制Notch信号传导。然后，我们鉴定出一个由768个基因组成的预处理基因表达特征，该特征与99个肿瘤系的体内GSI疗效显著相关。通路分析表明，GSI反应者特征富含Notch通路成分以及炎症/免疫相关基因。这些数据显示了这种新型体内模型系统在发现预测靶向治疗反应的生物标志物方面的强大作用，并为鉴定最有可能对GSI治疗敏感的人类乳腺癌提供了依据。
