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分子靶标类别可预测体外反应谱。

Molecular target class is predictive of in vitro response profile.

机构信息

Cancer Metabolism Drug Discovery, GlaxoSmithKline, Collegeville, Pennsylvania 19426, USA.

出版信息

Cancer Res. 2010 May 1;70(9):3677-86. doi: 10.1158/0008-5472.CAN-09-3788. Epub 2010 Apr 20.

Abstract

Preclinical cellular response profiling of tumor models has become a cornerstone in the development of novel cancer therapeutics. As efforts to predict clinical efficacy using cohorts of in vitro tumor models have been successful, expansive panels of tumor-derived cell lines can recapitulate an "all comers" efficacy trial, thereby identifying which tumors are most likely to benefit from treatment. The response profile of a therapy is most often studied in isolation; however, drug treatment effect patterns in tumor models across a diverse panel of compounds can help determine the value of unique molecular target classes in specific tumor cohorts. To this end, a panel of 19 compounds was evaluated against a diverse group of cancer cell lines (n = 311). The primary oncogenic targets were a key determinant of concentration-dependent proliferation response, as a total of five of six, four of four, and five of five phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway, insulin-like growth factor-I receptor (IGF-IR), and mitotic inhibitors, respectively, clustered with others of that common target class. In addition, molecular target class was correlated with increased responsiveness in certain histologies. A cohort of PI3K/AKT/mTOR inhibitors was more efficacious in breast cancers compared with other tumor types, whereas IGF-IR inhibitors more selectively inhibited growth in colon cancer lines. Finally, specific phenotypes play an important role in cellular response profiles. For example, luminal breast cancer cells (nine of nine; 100%) segregated from basal cells (six of seven; 86%). The convergence of a common cellular response profile for different molecules targeting the same oncogenic pathway substantiates a rational clinical path for patient populations most likely to benefit from treatment. Cancer Res; 70(9); 3677-86. (c)2010 AACR.

摘要

临床前肿瘤模型的细胞反应分析已成为新型癌症治疗方法开发的基石。由于使用体外肿瘤模型队列预测临床疗效的努力取得了成功,因此广泛的肿瘤衍生细胞系面板可以重现“所有参与者”的疗效试验,从而确定哪些肿瘤最有可能从治疗中受益。治疗的反应谱通常是孤立研究的;然而,在多样化化合物的肿瘤模型中,药物治疗效果模式可以帮助确定特定肿瘤群体中独特分子靶类别的价值。为此,评估了 19 种化合物对一组多样化的癌细胞系(n = 311)的作用。主要致癌靶标是浓度依赖性增殖反应的关键决定因素,总共 6 种中的 5 种、4 种中的 4 种和 5 种中的 5 种磷脂酰肌醇 3-激酶(PI3K)/AKT/雷帕霉素(mTOR)途径、胰岛素样生长因子-I 受体(IGF-IR)和有丝分裂抑制剂分别与其他相同靶类别的药物聚集在一起。此外,分子靶类与某些组织学的更高反应性相关。PI3K/AKT/mTOR 抑制剂在乳腺癌中的疗效优于其他肿瘤类型,而 IGF-IR 抑制剂更选择性地抑制结肠癌系的生长。最后,特定表型在细胞反应谱中起着重要作用。例如,腔腺癌(9/9;100%)与基底细胞(7/7;86%)分离。针对相同致癌途径的不同分子具有共同的细胞反应谱,这为最有可能受益于治疗的患者群体提供了合理的临床途径。癌症研究; 70(9); 3677-86. (c)2010AACR。

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