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在非小细胞肺癌中瘤子集的蛋白质组模式
Kiyoshi Yanagisawa1, Yu Shyr, Baogang J Xu
1Vanderbilt-Ingram Cancer Center, Nashville, Tennessee 37232-6838, USA.
Lancet (London, England)
|August 21, 2003
概括
来自肺瘤组织的蛋白质组学可以准确地分类癌症类型,并预测患者的生存率. 这种质谱方法有助于理解肺癌生物学和预后.
科学领域:
- 生物化学 生物化学
- 在瘤学瘤学.
- 蛋白质组学是指蛋白质组学.
背景情况:
- 蛋白质组学为了解癌症生物学提供了一个对基因组学的补充方法.
- 矩阵辅助激光脱/电离质谱法 (MALDI-MS) 可以直接从组织段中对蛋白质表达进行分析.
- 这种技术可以用于分类肺瘤.
研究的目的:
- 使用蛋白质组学来分类肺瘤.
- 开发肺癌组织学,转移和结节参与的预测模型.
- 为了确定与非小细胞肺癌预后相关的蛋白质组模式.
主要方法:
- 使用MALDI-MS.从79个肺癌和14个正常肺组织中获得了蛋白质谱.
- 使用训练队列 (42个瘤,8个正常样本) 构建了一个类预测模型.
- 该模型在一个独立的盲测试队列 (37个瘤,6个正常样本) 上得到验证.
主要成果:
- 从1毫米的组织区域确定了1600多个蛋白质峰值.
- 该模型实现了肺癌组织学和原发性与转移性瘤的完美分类.
- 节点参与被分类的准确率为85%,该模型在测试队列中表现良好.
- 在非小细胞肺癌患者 (p<0.0001) 中,15个峰值的蛋白质组特征区分出良好和差的预后 (p<0.0001).
结论:
- 来自少量肺瘤组织的蛋白质组模式可以准确地分类组织学群.
- 该方法预测了切除非小细胞肺癌的节点参与和存活率.
- 这种方法为肺癌生物学和患者的结果提供了宝贵的见解.
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