蛋白组合揭示了前列腺癌患者特异性网络
Justin M Drake1, Evan O Paull2, Nicholas A Graham3
1Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA; Rutgers Cancer Institute of New Jersey and Department of Medicine, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ 08903, USA.
Cell
|August 9, 2016
概括
这项研究使用综合蛋白数据揭示了转移性抵抗割的前列腺癌 (CRPC) 的个性化信号通路. 这些发现为晚期前列腺癌患者的分层和向治疗选择提供了新的方法.
科学领域:
- 癌症学
- 分子生物学
- 生物信息学
背景情况:
- 转移性抵抗割的前列腺癌 (CRPC) 是一种具有复杂信号网络的致命疾病.
- 了解这些网络对于开发有效的向疗法至关重要.
研究的目的:
- 在CRPC中整合多组数据 (基因组,转录组,蛋白组) 用于途径分析.
- 在CRPC中开发一种识别个性化信号通路签名的方法.
- 为个人CRPC患者提供药物优先级的参考.
主要方法:
- 使用临床组织从致命的转移性CRPC患者的快速解剖.
- 通过互动事件 (TieDIE) 进行绑定传播,以整合各种数据集.
- 应用MSigDB标志基因组和蛋白组数据来识别丰富的信号通路.
主要成果:
- 在CRPC中合成了强大的药物酶通路信号网络.
- 在CRPC瘤中发现了六个主要的信号通路.
- 使用集成个性化签名 (pCHIPS) 开发了基于酸化的癌症特征.
结论:
- pCHIPS有效地揭示了转移性CRPC中激活的信号通路的多样性.
- 开发的基于路径的参考可以帮助个别患者确定药物优先级.
- 这种方法有可能对晚期前列腺癌患者进行分层和向治疗.
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