基因和蛋白质序列特征增强了HLA I类联结体预测
Kaspar Bresser1, Benoit P Nicolet2, Anita Jeko3
1Department of Molecular Oncology and Immunology, Netherlands Cancer Institute, Oncode Institute, Amsterdam, the Netherlands; Department of Hematology, Leiden University Medical Center, Leiden, the Netherlands.
Cell reports
|June 13, 2024
概括
基因和蛋白质序列特征显著影响T细胞免疫疗法的人类白细胞抗原 (HLA) 连接体呈现. 整合这些"硬编码"特征可以提高HLA连接体预测的准确性,与基因表达数据相提并论.
科学领域:
- 免疫学 免疫学 免疫学
- 蛋白质组学是指蛋白质组学.
- 生物信息学是一种生物信息学.
背景情况:
- 基于T细胞的免疫疗法依赖于具有可向人白细胞抗原 (HLA) 类 I 连接体的恶性组织.
- 虽然已知HLA亲和力和蛋白质酶处理等类因素,但基因和蛋白质序列特征对表位素呈现的影响不太清楚.
研究的目的:
- 系统地评估7,135个基因和蛋白质序列特征对HLA连接体采样的贡献.
- 为了确定这些序列特征是否可以改善预测HLA连接体呈现.
主要方法:
- 进行了HLA联体体质谱学.
- 分析了7135个基因和蛋白质序列特征.
- 在机器学习模型中集成序列特征.
主要成果:
- 确定了mRNA和蛋白质丰度/周转的预测修饰剂,包括mRNA甲基化和蛋白质无化部位,作为HLA连接体存在的信息.
- 证明将这些序列特征集成到机器学习模型中可以显著增强HLA连接体预测.
- 表明序列特征集成实现了与实验基因表达数据可比的预测准确性.
结论:
- 基因和蛋白质序列特征是HLA连接体呈现的有价值,以前被低估的决定因素.
- 整合"硬编码"序列信息可以提高HLA连接体呈现的预测能力,这对于免疫疗法开发至关重要.
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