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与线粒体相关的lncRNAs:预测肺腺癌的预后,瘤微环境和治疗反应

Qianhui Zhou¹, Jiali Xiong¹, Yan Gao¹

¹Department of Respiratory and Critical Care Medicine, Zhuzhou Central Hospital, Zhuzhou, 412000, Hunan, China.

Functional & integrative genomics

|October 21, 2023

概括

这项研究开发了一种13-lncRNA肺腺癌 (LUAD) 预后模型,以预测患者的结果和指导治疗. 该模型准确地区分高风险和低风险的LUAD患者,显示了改善癌症治疗的潜力.

科学领域:

在瘤学瘤学.
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:

肺癌,特别是肺腺癌 (LUAD),在全球具有很高的发病率和死亡率.
准确的预后生物标志物对于改善LUAD患者的治疗结果和治疗策略至关重要.

研究的目的:

确定新型线粒体相关的长非编码RNA (lncRNAs) 作为 LUAD 预后的潜在生物标志物.
开发和验证基于这些已识别的 lncRNAs 的 LUAD 预后预测模型.

主要方法:

使用皮尔森相关性分析选了2175个与线粒体相关的lncRNAs.
采用单变量,拉索和多变量考克斯回归分析来选择13个预后 lncRNA.
使用临床数据,卡普兰-梅尔曲线和接收器操作特征 (ROC) 分析验证了预后模型.

主要成果:

开发了一种包括13种线粒体关联lncRNA的预后模型,证明了独立的预后意义.
该模型准确地预测了整体存活率 (OS),AUC-ROC值分别为0.746,0.692和0.726,分别在1,3年和5年.
在高风险和低风险组之间观察到免疫功能,免疫检查点和药物敏感性的显著差异.

结论:

开发的13-lncRNA预后模型作为LUAD患者预后的独立预测器.
该模型通过评估免疫状态和药物敏感性,为个性化治疗策略提供了潜力.
进一步的研究可以利用这些发现来加强LUAD治疗干预措施.

关键词:

肺部腺癌是肺部腺癌.线粒体中的线粒体.预测模型的预测模型.风险评分风险评分风险评分在cnRNA中.

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