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与免疫相关的长非编码RNA签名用于舌头状细胞癌

Daniel Hu¹, Diana V Messadi^1,2

¹School of Dentistry, University of California, Los Angeles, CA 90095-1668, USA.

Current oncology (Toronto, Ont.)

|May 26, 2023

概括

这项研究确定了六种与免疫相关的长非编码RNA (lncRNA) 作为舌头状细胞癌 (TSCC) 的关键预后生物标志物. 这些lncRNAs形成了一个模型,可以预测患者的生存率,并指导TSCC的个性化免疫疗法策略.

科学领域:

在瘤学瘤学.
基因组学就是基因组学.
免疫学免疫学免疫学

背景情况:

舌头状细胞癌 (TSCC) 是一种严重的头癌亚型,预后不佳,死亡率高.
舌头瘤发生的潜在分子机制尚未完全理解.
确定可靠的预后生物标志物对于改善TSCC患者的治疗结果至关重要.

研究的目的:

确定和评估与免疫相关的长非编码RNA (lncRNAs) 作为TSCC的潜在预后生物标志物.
开发基于这些已识别的 lncRNAs 的预后模型.
评估预后模型在预测患者存活率和指导免疫治疗方面的临床有用性.

主要方法:

利用癌症基因组图谱 (TCGA) 来获取TSCC lncRNA表达数据以及免疫学数据库和分析门户网站 (ImmPort) 来获取与免疫相关的基因.
采用皮尔森相关性分析来识别与免疫相关的 lncRNAs.
应用单变量和多变量考克斯回归,卡普兰-梅尔生存分析,主要组件分析 (PCA) 和接收器操作特征 (ROC) 分析,用于模型开发和验证.

主要成果:

鉴定了六种与免疫相关的lncRNAs (MIR4713HG,AC104088.1,LINC00534,NAALADL2-AS2,AC083967.1,FNDC1-IT1) 在TSCC中具有显著的预后价值.
开发了六个lncRNA预后模型,与已确定的临床病理因素相比,其预测能力更强.
卡普兰-梅尔分析显示,低风险组的整体存活率明显优于高风险组;ROC分析显示出良好的预测准确性 (AUCs范围为0.691至0.790).

结论:

建立了一个强大的预后模型,基于TSCC的六个与免疫相关的lncRNA.
开发的模型对于预测患者存活率具有临床意义.
这种预后模型可能有助于为TSCC患者开发个性化免疫治疗策略.

关键词:

与免疫相关的基因在ncRNA中,我们可以预后预后预后生存分析,生存分析.舌头状细胞癌瘤

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