探讨 CFTR 和 PKIA 基因的甲基化状态作为肺腺癌潜在的生物标志物。

Exploring the methylation status of CFTR and PKIA genes as potential biomarkers for lung adenocarcinoma.

机构信息

Xuzhou Central Hospital, Xuzhou, Jiangsu, 221000, China.

The 2nd Medical College of Binzhou Medical University, Yantai, Shandong, 264000, China.

出版信息

Orphanet J Rare Dis. 2023 Aug 29;18(1):246. doi: 10.1186/s13023-023-02807-1.

DOI:10.1186/s13023-023-02807-1

PMID:37644544

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10466921/

Abstract

BACKGROUND

One of the most prevalent cancers in the world is lung cancer, with adenocarcinoma (LUAD) making up a significant portion of cases. According to the National Cancer Institute (NCI), there are new cases and fatality rates per 100,000 individuals as follows: New instances of lung and bronchial cancer occur annually at a rate of 50.0 per 100,000 persons. The yearly death rate for men and women is 35.0 per 100,000. DNA methylation is one of the earliest discovered and widely studied epigenetic regulatory mechanisms, and its abnormality is closely related to the occurrence and development of cancer. However, the prognostic value of DNA methylation and LUAD needs to be further explored to improve the survival prediction of LUAD patients.

METHODS

The transcriptome data and clinical data of LUAD were downloaded from TCGA and GEO databases, and the Illumina Human Methylation450 array (450k array) data were downloaded from the TCGA database. Firstly, the intersection of the expressed genes of the two databases is corrected, the differential analysis is performed, and the methylation data is evaluated by the MethylMix package to obtain differentially methylated genes. Independent prognostic genes were screened out using univariate and multivariate Cox regression analysis, and a methylation prognostic model was developed using univariate Cox analysis and validated with the GSE30219 dataset in the GEO database. Survival analysis between methylation high-risk and low-risk groups was performed and a methylation-based gene prognostic model was constructed. Finally, the prediction of potential drugs associated with the LUAD gene signature using Drug Sensitivity Genomics in Cancer (GDSC).

RESULTS

In this study, a total of 555 samples from the TCGA database and 307 samples from GSE30219 were included, and a total of 24 differential methylation driver genes were identified. Univariate and multivariate Cox regression analyzes were used to screen out independent prognostic genes, involving 2 genes: CFTR, PKIA. Survival analysis was different between the methylation high-risk group and the low-risk group, the CFTR high methylation group and the low methylation group were poor, and the opposite was true for PKIA.

CONCLUSIONS

Our study revealed that the methylation status of CFTR and PKIA can serve as potential prognostic biomarkers and therapeutic targets in lung cancer.

摘要

背景

肺癌是世界上最常见的癌症之一，其中腺癌（LUAD）占很大比例。根据美国国家癌症研究所（NCI）的数据，每 10 万人中有新发病例和死亡率如下：每年每 10 万人中有 50.0 例肺癌和支气管癌新发病例。男性和女性的年死亡率为每 10 万人 35.0 例。DNA 甲基化是最早发现和广泛研究的表观遗传调控机制之一，其异常与癌症的发生和发展密切相关。然而，DNA 甲基化和 LUAD 的预后价值需要进一步探讨，以提高 LUAD 患者的生存预测。

方法

从 TCGA 和 GEO 数据库下载 LUAD 的转录组数据和临床数据，并从 TCGA 数据库下载 Illumina Human Methylation450 阵列（450k 阵列）数据。首先，校正两个数据库中表达基因的交集，进行差异分析，并使用 MethylMix 包评估甲基化数据，以获得差异甲基化基因。使用单因素和多因素 Cox 回归分析筛选独立预后基因，并使用单因素 Cox 分析建立甲基化预后模型，使用 GEO 数据库中的 GSE30219 数据集进行验证。对甲基化高风险和低风险组之间的生存分析进行分析，并构建基于甲基化的基因预后模型。最后，使用癌症药物敏感性基因组学（GDSC）预测与 LUAD 基因特征相关的潜在药物。

结果

本研究共纳入 TCGA 数据库 555 例和 GSE30219 数据库 307 例，共鉴定出 24 个差异甲基化驱动基因。使用单因素和多因素 Cox 回归分析筛选出独立预后基因，涉及 2 个基因：CFTR、PKIA。生存分析显示，甲基化高风险组和低风险组之间存在差异，CFTR 高甲基化组和低甲基化组预后不良，PKIA 则相反。