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来自异常RNA剪接的癌症新抗原的全面分析

Daniel P Wickland¹, Colton McNinch^2,3, Erik Jessen³

¹Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA.

Journal for immunotherapy of cancer

|May 16, 2024

概括

SPLICE-neo从异常RNA转录中识别出新的癌症新抗原,通过分析拼接位突变和de novo拼接事件来增强免疫瘤学,以发现强大的瘤抗原.

科学领域:

在瘤学瘤学.
免疫学免疫学免疫学
生物信息学是一种生物信息学.

背景情况:

癌症新抗原对于下一代免疫瘤疗法至关重要.
之前的计算框架,如REAL-neo,通过突变和基因融合识别了新抗原.
异常的RNA转录呈现了一种新的新抗原来源.

研究的目的:

开发SPLICE-neo,一种用于从异常RNA转录中识别新抗原的计算工具.
分析由DNA拼接位突变和de novoRNA拼接事件引起的新抗原.
优先考虑和评估已识别的拼接新抗原的新抗原潜力.

主要方法:

在11,892个TCGA瘤中分析拼接部位突变,以确定拼接配置文件.
利用新的逻辑模型从拼接位突变计算转录异型.
通过RNA测序识别新的RNA拼接事件,将读数映射到新型的外子结点上.
根据表达水平和z分数对异常转录进行排名.
将排名最高的异构体转化为蛋白质,并通过REAL-neo评估新抗原潜力.
使用体外T2结合试验验证顶部拼接新抗原候选人与HLA-A*02:01结合.

主要成果:

在BRCA,LUAD,LUSC和LIHC中发现了大量的拼接新抗原.
拼接新抗原对整体新抗原负载做出了重大贡献.
几种拼接新抗原表现出强大的瘤抗原性,具有强大的HLA结合,超过了流感病毒对照.

结论:

SPLICE-neo是第一个用于识别和优先考虑来自DNA拼接位突变和de novoRNA异常拼接的拼接新抗原的全面工具.
新的逻辑模型使得从拼接位突变的全长异常转录的组装和优先考虑成为可能.
SPLICE-neo有效地识别了涉及多个外的复杂外跳跃事件.

关键词:

基因组基因组基因组基因组基因组人类白细胞抗原 - - HLA 免疫治疗是一种免疫疗法.主要组织相容性复杂 - - MHC.下一代测序 - - 国家基因系统 (NGS)

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