基于PI3K/AKT/MTOR途径相关基因的风险评分模型,用于预测肺状细胞癌的生存,瘤微环境,免疫治疗和药物敏感性

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Updated: Jan 11, 2026

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

Published on: April 6, 2016

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Qiang Zhang¹, Jianhua Zhu², Huiyong Han³

¹Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University.

Journal of environmental pathology, toxicology and oncology : official organ of the International Society for Environmental Toxicology and Cancer

|November 10, 2025

概括

一个新的11基因模型预测了肺状细胞癌 (LUSC) 患者的结果. 较低风险的患者表现出更好的生存率,增强的抗瘤免疫力和更好的药物敏感性,有助于个性化LUSC治疗策略.

科学领域:

在瘤学瘤学.
分子生物学分子生物学
生物信息学是一种生物信息学.

背景情况:

PI3K/AKT/MTOR (PAM) 信号通路是肺状细胞癌 (LUSC) 的潜在治疗标.
在LUSC中,PAM通路相关基因 (PAG) 的预后价值在很大程度上仍未被探索.
识别预后标志物对于改善LUSC患者的治疗结果和治疗策略至关重要.

研究的目的:

调查PAG在肺状细胞癌 (LUSC) 的预后意义.
开发和验证基于PAG的LUSC的预后模型.
探索LUSC的预后模型,免疫透和药物敏感性之间的关系.

主要方法:

为了LUSC,利用了TCGA和GEO数据库中的转录组数据和临床特征.
使用回归分析构建了一个11基因预后模型 (Riskscore).
验证了模型的预测性能,并使用生物信息学工具和软件包评估了免疫透和药物敏感性.

主要成果:

开发了一个11基因风险评分模型,将患者分为高风险 (HR) 和低风险 (LR) 组.
该LR组表现出显著更长的生存时间,有利的免疫透 (B细胞,Tfh细胞) 和更高的抗瘤免疫分数.
对于特定的向疗法 (Alpelisib,Ibrutinib,Sapitinib,Savolitinib),LR患者的TIDE得分和IC50值较低.

结论:

11基因风险评分模型为预测LUSC预后提供了可靠的工具.
该LR组的改善生存率,免疫特征和药物敏感性表明免疫疗法和向治疗的潜在益处.
这项研究为个性化治疗策略和LUSC的预后预测提供了宝贵的见解.

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