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与免疫细胞死亡相关的长非编码RNA影响了针对肺腺癌的免疫治疗

Dongjie Sun^1,2, Chi Zhang³

¹Department of Translational Medicine, The First Hospital of Jilin University, Changchun, China.

Oncology research

|August 7, 2023

概括

这项研究确定了10种与免疫细胞死亡相关的长非编码RNA (lncRNAs),可预测肺腺癌 (LUAD) 的存活率. 这种新型风险特征也对瘤微环境具有特征,并为LUAD患者指导个性化治疗策略.

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:

肺腺癌 (LUAD) 是全球癌症死亡的主要原因.
免疫性细胞死亡 (ICD) 触发了自适应性免疫反应,但其通过长非编码RNA (lncRNAs) 在LUAD中的作用尚未被探索.
了解瘤微环境和预后生物标志物对于LUAD治疗至关重要.

研究的目的:

在LUAD中调查ICD相关 lncRNAs 的预后意义.
开发一种风险特征,用于预测LUAD患者的生存率和免疫微环境特征.
评估这种特征在指导个性化治疗和预测药物敏感性方面的潜力.

主要方法:

单变和最小绝对收缩和选择操作员 (LASSO) 考克斯回归分析以确定预后性ICD相关的lncRNAs.
构建和验证10-lncRNA LUAD.风险签名的构建和验证.
免疫微环境分析,体质突变分析,瘤免疫功能障碍和排除 (TIDE) 分析,以及抗癌药物IC50值的预测.

主要成果:

构建了一个包含10个ICD相关的lncRNAs的风险特征,并被验证为LUAD总生存率的可靠预测指标.
这种特征与免疫细胞透,瘤突变负担和免疫逃避相关.
高风险患者表现出良好的免疫疗法反应指标 (检查点基因表达升高,TIDE得分低) 和对特定抗癌药物的敏感性.

结论:

10-lncRNA风险特征有效预测LUAD患者的预后,并描述瘤免疫微环境.
这个签名有可能指导免疫疗法选择和个性化治疗策略在LUAD中.
需要进一步验证,以便将此签名纳入用于管理LUAD的临床实践.

关键词:

生物信息学是一种生物信息学.免疫原性细胞死亡肺部腺癌瘤是肺部腺癌.预测模型是一个预测模型.瘤透透的情况

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