Construction and validation of a prognostic model of lncRNAs associated with RNA methylation in lung adenocarcinoma.

IF 1.5 4区医学 Q4 ONCOLOGY

Translational cancer research Pub Date : 2025-02-28 Epub Date: 2025-02-24 DOI:10.21037/tcr-24-1085

Liren Zhang, Lei Yang, Xiaobo Chen, Qiubo Huang, Zhiqiang Ouyang, Ran Wang, Bingquan Xiang, Hong Lu, Wenjun Ren, Ping Wang

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引用次数: 0

Abstract

Background: Lung adenocarcinoma (LUAD) is a common type of lung cancer and one of the leading causes of cancer death worldwide. Long non-coding RNAs (lncRNAs) play a crucial role in tumors. The purpose of this study was to explore the expression of lncRNAs associated with RNA methylation modification and their prognostic value in LUAD.

Methods: The RNA sequencing and clinical data were downloaded from The Cancer Genome Atlas dataset, and the messenger RNA and lncRNAs were annotated by Ensemble. The lncRNAs related to RNA methylation regulators (RMlncRNAs) were filtered by Pearson correlation analysis between differentially expressed lncRNAs and RNA methylation regulators. Univariate Cox regression analysis, multivariate Cox regression analysis, and least absolute shrinkage and selection operator regression analysis were used to construct a prognostic model. The receiver operating characteristic curve (ROC) was plotted to validate the predictive value of the prognostic model. Then, tumor mutational burden (TMB) and microsatellite instability were used to compare the immunotherapy response. Finally, to perform a drug sensitivity analysis, the half-maximal inhibitory concentration (IC₅₀) of targeted drugs was calculated using pRRophetic package.

Results: In total, 18 RMlncRNAs associated with the prognosis of LUAD patients were identified. Then, six feature lncRNAs (NFYC-AS1, OGFRP1, MIR4435-2HG, TDRKH-AS1, DANCR, and TMPO-AS1) were used to construct a prognostic model. The ROC curves for training, testing, and validation sets showed that the prognosis model was effective. The subindex based on the prognostic model had a high correlation with TMB. The high-risk group might be subject to greater immune resistance according to the comparison of Tumor Immune Dysfunction and Exclusion scores. Finally, the IC₅₀ of 11 drugs had differences between high- and low-risk group, and only three of the drug's target genes (ERBB4, CASP8, and CD86) were differentially expressed.

Conclusions: In conclusion, a prognostic model based on six feature lncRNAs (NFYC-AS1, OGFRP1, MIR4435-2HG, TDRKH-AS1, DANCR, and TMPO-AS1) was constructed by bioinformatics analysis, which might provide a new insight into the evaluation and treatment of LUAD.

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肺腺癌中与RNA甲基化相关的lncrna预后模型的构建和验证。

背景：肺腺癌（LUAD）是一种常见的肺癌类型，也是全球癌症死亡的主要原因之一。长链非编码rna （lncRNAs）在肿瘤中起着至关重要的作用。本研究的目的是探讨与RNA甲基化修饰相关的lncRNAs在LUAD中的表达及其预后价值。方法：从The Cancer Genome Atlas数据集下载RNA测序和临床数据，使用Ensemble软件对其中的信使RNA和lncrna进行注释。通过差异表达lncrna与RNA甲基化调节因子之间的Pearson相关分析筛选出与RNA甲基化调节因子相关的lncrna （rmlncrna）。采用单因素Cox回归分析、多因素Cox回归分析、最小绝对收缩和选择算子回归分析构建预后模型。绘制受试者工作特征曲线（ROC）以验证预后模型的预测价值。然后用肿瘤突变负荷（tumor mutational burden， TMB）和微卫星不稳定性（microsatellite instability）来比较免疫治疗反应。最后，使用prophytic包装计算目标药物的半最大抑制浓度（IC50），进行药物敏感性分析。结果：共鉴定出18个与LUAD患者预后相关的rmlncrna。然后，使用6个特征lncrna （NFYC-AS1、OGFRP1、MIR4435-2HG、TDRKH-AS1、DANCR和TMPO-AS1）构建预后模型。训练集、检验集和验证集的ROC曲线显示预后模型是有效的。基于预后模型的分类指数与TMB有较高的相关性。根据肿瘤免疫功能障碍和排斥评分的比较，高危人群可能存在更大的免疫抵抗。最后，11种药物的IC50在高危组和低危组之间存在差异，只有3种药物的靶基因（ERBB4、CASP8和CD86）存在差异表达。结论：通过生物信息学分析，构建了基于NFYC-AS1、OGFRP1、MIR4435-2HG、TDRKH-AS1、DANCR和TMPO-AS1六个特征lncrna的预后模型，为LUAD的评估和治疗提供了新的思路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Translational cancer research ONCOLOGY-

CiteScore

2.10

自引率

0.00%

发文量

252

期刊介绍： Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.