Modeling RAS phenotype in colorectal cancer uncovers novel molecular traits of RAS dependency and improves prediction of response to targeted agents in patients.
Modeling RAS phenotype in colorectal cancer uncovers novel molecular traits of RAS dependency and improves prediction of response to targeted agents in patients.
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DOI：
10.1158/1078-0432.ccr-13-1943
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发表时间：
2014-01-01
期刊：
影响因子：
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通讯作者：
Laurent-Puig P
中科院分区：
文献类型：
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作者：
Guinney J;Ferté C;Dry J;McEwen R;Manceau G;Kao KJ;Chang KM;Bendtsen C;Hudson K;Huang E;Dougherty B;Ducreux M;Soria JC;Friend S;Derry J;Laurent-Puig P
KRAS野生型状态是结直肠癌（CRC）中抗egfr单克隆抗体敏感性的不完美预测因子，这促使人们努力识别驱动RAS的新分子畸变。本研究旨在建立RAS通路活性的定量读数：(1)揭示CRC特异性RAS活性的分子替代物；(2)提高对患者西妥昔单抗反应的预测；(3)提出新的治疗策略。在一个大型CRC数据集中训练RAS通路活性模型，并在三个独立的CRC患者数据集中进行验证。从TCGA CRC数据中推断出新的分子特征。RAS模型预测西妥昔单抗耐药性的能力在小鼠异种移植物和三个独立的患者队列中进行了测试。我们的模型与大细胞系概要之间进行了药物敏感性相关性。RAS模型在3个验证数据集上的性能非常稳健。(1)我们的模型证实了KRAS野生型患者RAS表型的异质性，并提示了驱动其表型的新分子特征（如MED12缺失、GBXW7突变、MAP2K4突变）。(2)与KRAS突变相比，它提高了对西妥昔单抗的反应和无进展生存的预测（HR=2.0; p< 0.01）（异种移植和患者队列）。(3)我们的模型在2个细胞面板筛选中一致预测了对MEK抑制剂的敏感性（p< 0.01）。在CRC中建立RAS表型模型，可以对RAS途径在细胞系、异种移植物和患者群体中的活性进行强有力的调查。它在预测对抗egfr药物和MEK抑制剂的反应方面显示了临床效用。
KRAS wild-type status is an imperfect predictor of sensitivity to anti-EGFR monoclonal antibodies in colorectal cancer (CRC), motivating efforts to identify novel molecular aberrations driving RAS. This study aimed to build a quantitative readout of RAS pathway activity to: (1) uncover molecular surrogates of RAS activity specific to CRC; (2) improve the prediction of cetuximab response in patients; (3) suggest new treatment strategies. A model of RAS pathway activity was trained in a large CRC dataset and validated in three independent CRC patient datasets. Novel molecular traits were inferred from the TCGA CRC data. The ability of the RAS model to predict resistance to cetuximab was tested in mouse xenografts and three independent patient cohorts. Drug sensitivity correlations between our model and large cell line compendiums were performed. The performance of the RAS model was remarkably robust across 3 validation datasets. (1) Our model confirmed the heterogeneity of the RAS phenotype in KRAS wild-type patients, and suggests novel molecular traits driving its phenotype (e.g. MED12 loss, GBXW7 mutation, MAP2K4 mutation). (2) It improved the prediction of response and progression free survival (HR=2.0; p<.01) to cetuximab compared to KRAS mutation (xenograft and patient cohorts). (3) Our model consistently predicted sensitivity to MEK inhibitors (p<.01) in 2 cell panel screens. Modeling the RAS phenotype in CRC allows for the robust interrogation of RAS pathway activity across cell lines, xenografts, and patient cohorts. It demonstrates clinical utility in predicting response to anti-EGFR agents and MEK inhibitors.