A Novel Methylation-Based Model for Prognostic Prediction in Lung Adenocarcinoma

IF 1.8 4区生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY

Current Genomics Pub Date : 2024-01-23 DOI:10.2174/0113892029277397231228062412

Manyuan Li, Xufeng Deng, Dong Zhou, Xiaoqing Liu, Jigang Dai, Quanxing Liu

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引用次数: 0

Abstract

Objective:: Specific methylation sites have shown promise in the early diagnosis of lung adenocarcinoma (LUAD). However, their utility in predicting LUAD prognosis remains unclear. This study aimed to construct a reliable methylation-based predictor for accurately predicting the prognosis of LUAD patients. Method:: DNA methylation data and survival data from LUAD patients were obtained from the TCGA and a GEO series. A DNA methylation-based signature was developed using univariate least absolute shrinkage and selection operators and multivariate Cox regression models. Result:: Eight CpG sites were identified and validated as optimal prognostic signatures for the overall survival of LUAD patients. Receiver operating characteristic analysis demonstrated the high predictive ability of the eight-site methylation signature combined with clinical factors for overall survival. Conclusion:: This research successfully identified a novel eight-site methylation signature for predicting the overall survival of LUAD patients through bioinformatic integrated analysis of gene methylation markers used in the early diagnosis of lung cancer.

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基于甲基化的新型肺腺癌预后预测模型

目的：：特定的甲基化位点有望用于肺腺癌（LUAD）的早期诊断。然而，它们在预测肺腺癌预后方面的作用仍不明确。本研究旨在构建一种可靠的基于甲基化的预测因子，以准确预测 LUAD 患者的预后。方法：从 TCGA 和 GEO 系列中获取 LUAD 患者的 DNA 甲基化数据和生存数据。使用单变量最小绝对缩减和选择算子以及多变量考克斯回归模型建立了基于DNA甲基化的特征。结果：：鉴定并验证了八个 CpG 位点是 LUAD 患者总生存期的最佳预后特征。接收者操作特征分析表明，八个位点甲基化特征与临床因素相结合，对总生存期具有很高的预测能力。结论本研究通过对肺癌早期诊断中使用的基因甲基化标记进行生物信息学综合分析，成功鉴定出一种新型的八个位点甲基化特征，用于预测 LUAD 患者的总生存率。

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

Current Genomics 生物-生化与分子生物学

CiteScore

5.20

自引率

0.00%

发文量

审稿时长

>0 weeks

期刊介绍： Current Genomics is a peer-reviewed journal that provides essential reading about the latest and most important developments in genome science and related fields of research. Systems biology, systems modeling, machine learning, network inference, bioinformatics, computational biology, epigenetics, single cell genomics, extracellular vesicles, quantitative biology, and synthetic biology for the study of evolution, development, maintenance, aging and that of human health, human diseases, clinical genomics and precision medicine are topics of particular interest. The journal covers plant genomics. The journal will not consider articles dealing with breeding and livestock. Current Genomics publishes three types of articles including: i) Research papers from internationally-recognized experts reporting on new and original data generated at the genome scale level. Position papers dealing with new or challenging methodological approaches, whether experimental or mathematical, are greatly welcome in this section. ii) Authoritative and comprehensive full-length or mini reviews from widely recognized experts, covering the latest developments in genome science and related fields of research such as systems biology, statistics and machine learning, quantitative biology, and precision medicine. Proposals for mini-hot topics (2-3 review papers) and full hot topics (6-8 review papers) guest edited by internationally-recognized experts are welcome in this section. Hot topic proposals should not contain original data and they should contain articles originating from at least 2 different countries. iii) Opinion papers from internationally recognized experts addressing contemporary questions and issues in the field of genome science and systems biology and basic and clinical research practices.