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基于转录组数据的PI3K/AKT/mTOR途径状态表明,胰腺管道腺癌患者的异质性和免疫调节

Peng Xie^1,2, Si-Yuan Tan^1,2, Hai-Feng Li^1,2

¹Department of Surgery, School of Medicine, Southeast University, Nanjing, China.

The journal of gene medicine

|July 24, 2023

概括

准PI3K/AKT/mTOR通路对胰腺癌显示出有希望的结果. 这项研究确定了不同的途径状态和免疫特征,可以预测患者的预后和治疗反应.

科学领域:

在瘤学瘤学.
分子生物学分子生物学
免疫学免疫学免疫学

背景情况:

胰腺管腺癌 (PDAC) 是一种致命的癌症,治疗选择有限.
在PDAC中,PI3K/AKT/mTOR通路经常被激活,导致瘤的进展.

研究的目的:

研究针对PDAC中的PI3K/AKT/mTOR途径的治疗潜力.
根据路径激活和免疫细胞透,在PDAC中识别不同的分子亚型.
开发患者预后和治疗反应的预测模型.

主要方法:

评估了PI3K抑制剂taselisib对PDAC细胞活性的影响.
分析了来自公共数据库 (GTEx,TCGA) 的基因表达数据,以识别失调的PI3K/AKT/mTOR通路相关基因 (PRG).
利用无监督的集群来根据转录组数据将PDAC患者分为不同的分子亚型.
开发了一个基于机器学习的风险评分,使用PRG表达式配置文件.

主要成果:

塔塞利西布治疗显著降低了PDAC细胞活力.
确定了两个不同的患者群 (A和B),具有差异性免疫细胞透和通路激活.
集群A显示PI3K/AKT/mTOR通路激活率更高,预后不佳,对PI3K抑制剂和化疗反应更好.
机器学习衍生的风险评分准确地预测了整体存活率,而低风险组的存活率显著增加.

结论:

针对PI3K/AKT/mTOR途径为PDAC提供了一个可行的治疗策略.
独特的途径激活状态和瘤微环境特征,包括免疫调节,具有显著的预后价值.
开发的风险评分和途径分析可以帮助预测个体患者的结果并指导治疗决策.

关键词:

在PI3K/AKT/mTOR中使用.免疫微观环境免疫微环境机器学习是机器学习.胰腺管道腺癌瘤预后预后预后

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