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两种与炎症相关的基因模型可以预测肺腺癌患者的预后风险

Wei Yang¹, Junqi Long², Gege Li¹

¹Department of Thoracic Surgery, Beijing Tuberculosis and Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico

|March 7, 2025

概括

研究人员开发了一个两种mRNA模型来预测肺腺癌 (LUAD) 风险. 这种强大的诊断工具可以识别具有明显临床结果的患者子组,指导个性化治疗策略.

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:

肺腺癌 (LUAD) 缺乏有效的诊断研究,用于根据临床结果对患者进行分层.
识别使用炎症相关基因的子组对于改善LUAD患者管理至关重要.

研究的目的:

根据基因表达来识别LUAD内的分子子组.
使用特定的mRNA生物标志物,开发一个用于LUAD患者预后的预测模型.
在独立的患者队列中验证模型的有效性.

主要方法:

在癌症基因组图谱 (TCGA) 的mRNA表达数据中应用K-means聚类,以定义两个LUAD分子子组.
用于功能探索的基因组丰富分析 (GSEA),免疫透和基因组变异分析 (GSVA).
单变/多变Cox回归和拉索回归用于识别预后mRNA并构建预测模型.

主要成果:

确定了两种LUAD亚型,免疫丰富和非免疫丰富,与临床预后相关.
构建了一个新的两种mRNA (MS4A1和MS4A2) 模型,将LUAD患者分为高风险和低风险组,预后显著不同.
该模型在培训和三个独立的验证集中展示了强大而独立的预测能力.

结论:

一个经过验证的,强大的两mRNA模型有效地预测了LUAD患者的风险和临床结果.
该模型具有强大的预测能力,独立于其他临床因素.
该工具可以为LUAD患者指导个性化治疗策略.

关键词:

考克斯回归法考克斯回归法与炎症相关的基因卢阿德 (Luad) 的意思是说.预测预后预测预测

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