通过结合质谱和外基因组测序来预测免疫性瘤突变
Mahesh Yadav1, Suchit Jhunjhunwala1, Qui T Phung1
1Genentech, South San Francisco, California 94080, USA.
Nature
|November 28, 2014
概括
科学家们开发了一种新方法来发现瘤中的免疫原突变. 这种方法简化了针对个性化癌症疫苗的新抗原的识别和监测T细胞反应.
科学领域:
- 免疫学 免疫学 免疫学
- 在瘤学瘤学.
- 生物信息学是一种生物信息学.
背景情况:
- 人类瘤积累了许多体质突变.
- 在主要基因相容性复合物I类 (MHCI) 分子上呈现的突变可以作为新抗原,可能引起抗瘤T细胞反应.
- 发现这些新抗原是具有挑战性的,因为艰苦的选方法.
研究的目的:
- 为了简化免疫原突变的发现.
- 描述免疫原突变的一般性质.
- 开发一种用于识别新抗原的预测算法.
主要方法:
- 结合全外体和转录组测序与质谱学,以识别小鼠瘤模型中的新上位素.
- 结合MHCI的突变的结构建模.
- 通过预测T细胞受体可访问的溶剂暴露突变来评估免疫性.
- 接种了预测免疫性的疫苗的小鼠.
主要成果:
- 确定了超过1300个氨基酸变化,预计约13%的氨基酸会结合MHCI.
- 通过质谱测量证实了预测的子集.
- 结构模拟的与MHCI结合,识别溶剂暴露的突变作为潜在的免疫原体.
- 用预测的疫苗在小鼠中引起了治疗性活跃的T细胞反应.
结论:
- 一个预测算法可以有效地识别免疫性突变.
- 这种方法有助于开发个性化癌症疫苗.
- 该方法允许药理动力学监测T细胞对癌症疫苗的反应.
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