定义癌症依赖地图
Aviad Tsherniak1, Francisca Vazquez2, Phil G Montgomery1
1Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
Cell
|July 29, 2017
概括
研究人员通过基因组尺度选, 在多种癌细胞系中发现了769个必需基因. 预测模型揭示了大多数癌症依赖性的基于表达的生物标志物,有助于治疗目标优先.
科学领域:
- 癌症研究
- 基因组学
- 分子生物学
背景情况:
- 人类上皮瘤具有众多的遗传变异,使瘤生存必需基因的识别复杂化.
- 系统地确定癌症依赖性对于开发有效的癌症疗法至关重要.
研究的目的:
- 系统地识别人类癌症细胞系的生存所必需的基因.
- 使用分子特征开发癌症依赖性的预测模型.
- 建立一个癌症依赖地图的基础, 以优先考虑治疗目标.
主要方法:
- 在人类癌细胞系中对501个基因组尺度功能丧失查进行分析.
- 开发DEMETER分析框架,以区分目标和非目标RNAi效应.
- 使用66646个分子特征进行非线性回归建模的应用,以构建基因依赖性的预测模型.
主要成果:
- 在癌症细胞系中差异性要求的769个基因的识别.
- 对426个 (55%) 已确定依赖性的预测模型的开发.
- 发现基于表达的生物标志物在82%的模型中是主要的预测因素.
- 一个预测模型的演示,将UBB基因高甲基化与UBC依赖性联系起来.
结论:
- 这项研究对大量细胞系的癌症依赖性进行了全面分析.
- 基于表达的生物标志物是癌症依赖性的关键预测因素,为治疗策略提供了洞察力.
- 这些发现为制定癌症依赖地图奠定了基础,
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