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大规模的转录变异决定了癌症免疫治疗的新表位

Shiliang Ji¹, Feifan Wang¹, Yongjie Wu¹

¹State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China.

Science advances

|January 31, 2025

概括

这项研究引入了一种新方法,将核糖体新生链复杂结合的mRNA测序 (FL-RNC seq) 和人工智能结合起来,以发现用于癌症疫苗的大规模转录变异 (LSTV) 衍生新表位,提高免疫性和疗效.

科学领域:

免疫学免疫学免疫学
基因组学就是基因组学.
生物信息学是一种生物信息学.

背景情况:

有效的癌症疫苗需要精确的新表位发现,但目前的方法在识别免疫原性表位上存在局限性.
传统的方法往往无法捕捉潜在的全谱新表位,特别是那些来自复杂的转录基因事件的新表位.

研究的目的:

开发和验证一个新的工作流程,用于全面的新位标识,重点是大规模的转录变体 (LSTV).
在临床前癌症模型中评估LSTV衍生新表位的治疗潜力.

主要方法:

使用全长核糖体新生链复杂结合的mRNA测序 (FL-RNCseq) 进行新表位发现.
基于人工智能 (AI) 的综合预测模型,以提高新表位物识别准确度.
在MC38小鼠模型中开发并测试了一种合成的mRNA脂质纳米粒子疫苗编码,识别了LSTV衍生的新表位.

主要成果:

在MC38小鼠模型中确定了22个LSTV衍生的新表位.
证明了基于LSTV的mRNA疫苗可以作为独立疗法和与抗PD-1免疫疗法结合,抑制瘤进展.
在接种疫苗后观察到强大的T细胞特异性免疫力和瘤微环境的调制.

结论:

开发的工作流程扩展了针对个性化癌症疫苗的新位源谱.
来自LSTV的疫苗显示出在癌症免疫治疗中更广泛应用的巨大潜力.
全面的新表位标识对于推进癌症疫苗开发至关重要.

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