基于胃肠道癌症转录数据的瘤突变负担的持续预测
Beibei Hu1, Guohui Yin2, Jialin Zhu1
1Department of Gastroenterology, First Affiliated Hospital of China Medical University, Shenyang, China.
BMC medical informatics and decision making
|December 19, 2024
概括
瘤突变负担 (TMB) 预测了胃肠道癌症中的免疫检查点抑制剂 (ICI) 反应. 使用转录组数据的深度神经网络 (DNN) 模型准确预测TMB,与免疫透和临床结果相关联.
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:
- 瘤突变负担 (TMB) 是免疫检查点抑制剂 (ICI) 的生物标志物.
- 目前的TMB检测方法,如全外体测序 (WES) 和癌症基因面板 (CGP) 是昂贵的.
- 转录组数据为TMB评估提供了一个潜在的替代方案.
研究的目的:
- 利用转录组数据开发一个具有成本效益的模型来预测胃肠道瘤中的TMB.
- 研究TMB与免疫细胞透和临床病理参数之间的相关性.
主要方法:
- 使用TCGA转录组,体突变和食道癌 (ESCA),胃腺癌 (STAD),结肠腺癌 (COAD) 和直肠腺癌 (READ) 的临床数据.
- 执行数据可视化,差异基因表达分析,基因组丰富分析 (GSEA),并为TMB预测构建了一个深度神经网络 (DNN) 模型.
- 使用遗传算法优化了DNN模型.
主要成果:
- 高TMB组显示了CD4+/CD8+T细胞的丰富,并激活了抑制瘤的途径.
- 高TMB与多个免疫细胞的透增加以及临床参数 (年龄,M,N,AJCC阶段,整体存活率) 相相关.
- 优化的DNN模型在预测TMB方面取得了很高的准确性 (Pearson的r=0.98,0.82,0.92;R2=0.95,0.82,0.7分别用于训练,验证和测试集).
结论:
- 在胃肠道癌症中,TMB与临床病理学参数有关.
- 患有高TMB的患者表现出更大的免疫细胞透.
- 一个基于31个基因的DNN模型准确地预测了胃肠道瘤中的TMB.
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