Identification of the Prognostic Significance of Somatic Mutation-Derived LncRNA Signatures of Genomic Instability in Lung Adenocarcinoma.
Identification of the Prognostic Significance of Somatic Mutation-Derived LncRNA Signatures of Genomic Instability in Lung Adenocarcinoma.
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DOI：
10.3389/fcell.2021.657667
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发表时间：
2021
影响因子：
5.5
通讯作者：
Jin Y
中科院分区：
文献类型：
--
作者：
Geng W;Lv Z;Fan J;Xu J;Mao K;Yin Z;Qing W;Jin Y
背景资料：肺腺癌（LUAD）是一种高度异质性的肿瘤，具有大量的体细胞突变和基因组不稳定性，这是癌症的新标志。长链非编码RNA（lncRNA）是有前途的癌症生物标志物，据报道其参与基因组不稳定性。然而，基因组不稳定性相关lncRNA（GInLncRNA）的鉴定及其临床意义尚未在LUAD中进行研究。研究方法：我们通过结合457例LUAD患者的体细胞突变和转录组数据来确定GInLncRNA，并使用共表达网络和基因本体（GO）富集分析来探讨其潜在功能。然后，我们通过考克斯回归和LASSO回归筛选GInLncRNA，以构建基因组不稳定性相关的lncRNA签名（GInLncSig）。随后，我们使用突变相关性分析、外部验证、模型比较、独立预后意义分析和临床分层分析评估了GInLncSig。最后，我们建立了LUAD患者预后预测的诺模图，并在测试集和整个TCGA数据集中进行了验证。结果如下：我们鉴定了161种GInLncRNA，筛选其中7种以开发预后GInLncSig模型（LINC 01133、LINC 01116、LINC 01671、FAM 83 A-AS 1、PLAC 4、MIR 223 HG和AL590226.1）。GInLncSig独立预测LUAD患者的总生存期，与其他类似特征相比，表现出改善的性能。此外，GInLncSig与体细胞突变模式相关，表明其能够反映LUAD中基因组的不稳定性。最后，包括GInLncSig和肿瘤阶段的列线图表现出用于预测患者预后的改进的稳健性和临床实用性。结论：我们的研究确定了LUAD预后预测的特征，包括7个与基因组不稳定性相关的lncRNA，这可能为LUAD患者的临床分层管理和治疗决策提供有用的指标。
Background: Lung adenocarcinoma (LUAD) is a highly heterogeneous tumor with substantial somatic mutations and genome instability, which are emerging hallmarks of cancer. Long non-coding RNAs (lncRNAs) are promising cancer biomarkers that are reportedly involved in genomic instability. However, the identification of genome instability-related lncRNAs (GInLncRNAs) and their clinical significance has not been investigated in LUAD. Methods: We determined GInLncRNAs by combining somatic mutation and transcriptome data of 457 patients with LUAD and probed their potential function using co-expression network and Gene Ontology (GO) enrichment analyses. We then filtered GInLncRNAs by Cox regression and LASSO regression to construct a genome instability-related lncRNA signature (GInLncSig). We subsequently evaluated GInLncSig using correlation analyses with mutations, external validation, model comparisons, independent prognostic significance analyses, and clinical stratification analyses. Finally, we established a nomogram for prognosis prediction in patients with LUAD and validated it in the testing set and the entire TCGA dataset. Results: We identified 161 GInLncRNAs, of which seven were screened to develop a prognostic GInLncSig model (LINC01133, LINC01116, LINC01671, FAM83A-AS1, PLAC4, MIR223HG, and AL590226.1). GInLncSig independently predicted the overall survival of patients with LUAD and displayed an improved performance compared to other similar signatures. Furthermore, GInLncSig was related to somatic mutation patterns, suggesting its ability to reflect genome instability in LUAD. Finally, a nomogram comprising the GInLncSig and tumor stage exhibited improved robustness and clinical practicability for predicting patient prognosis. Conclusion: Our study identified a signature for prognostic prediction in LUAD comprising seven lncRNAs associated with genome instability, which may provide a useful indicator for clinical stratification management and treatment decisions for patients with LUAD.
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