预测来自体突变的瘤特异拼接作为新抗原候选物的来源
Franziska Lang1,2, Patrick Sorn1, Martin Suchan1
1TRON-Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz 55131, Germany.
Bioinformatics advances
|June 12, 2024
概括
我们开发了splice2neo,以识别由突变引起的瘤特异性拼接事件,生成用于癌症免疫治疗的新新抗原候选人. 这种方法增强了瘤的特异性,并扩大了潜在的治疗点.
科学领域:
- 在瘤学瘤学.
- 生物信息学是一种生物信息学.
- 免疫学 免疫学 免疫学
背景情况:
- 新抗原对于癌症免疫疗法至关重要.
- 替代拼接可以产生新抗原.
- 区分瘤特异性拼接与正常拼接是具有挑战性的.
研究的目的:
- 开发一种计算工具,用于识别由体质突变驱动的瘤特异性拼接接口.
- 从突变诱导的拼接事件中生成新抗原候选物.
- 为了验证这些新抗原的瘤特异性和治疗潜力.
主要方法:
- 开发splice2neo R包,以整合突变数据与RNA测序.
- 使用EasyQuant工具进行向RNA-seq分析.
- 应用了严格的检测规则,并通过健康组织样本和实验确认验证了发现.
主要成果:
- 鉴定出每位患有高瘤特异性 (FDR <5%) 的患者平均有1.7个突变衍生拼接接口.
- 在实验中证实了瘤特异性的前子跳转.
- 来自拼接的新表位基因与点突变衍生的新表位基因相比,与野生类型基因的自我相似性较低.
- 预测主要基因相容性复合体 (MHC) -I和MHC-II对大多数拼接衍生的新表位细胞的结合.
结论:
- 突变驱动的拼接是新抗原发现的可行来源.
- 拼接2neo有效地识别了瘤特定的拼接接口.
- 这种方法扩大了针对个性化癌症免疫疗法的新抗原候选人.
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