基于 5 个枢纽基因的慢性血栓栓塞性肺动脉高压新型诊断模型的鉴定。
Identification of a Novel Diagnosis Model based on 5 Hub Genes for Chronic Thromboembolic Pulmonary Hypertension.
机构信息
Department of Intensive Care Unit, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, China.
Department of Respiratory Medicine, People's Hospital of Longhua, The Affiliated Hospital of Southern Medical University, Shenzhen, 518109, China.
出版信息
Curr Med Chem. 2024;31(13):1754-1768. doi: 10.2174/0929867330666230605125512.
BACKGROUND
As a type of precapillary pulmonary hypertension, chronic thromboembolic pulmonary hypertension (CTEPH) results from incomplete pulmonary embolism resolution. In this study, we aimed to determine biomarker genes for predicting the prognosis of CTEPH.
METHODS
RNAseq of CTEPH was collected from the public database, namely Gene Expression Omnibus (GEO), including GSE84538 and GSE188938, which combined a dataset (GSE). Differentially expressed genes (DEG) or miRNA (DEM) were identified by limma package. Functional enrichment analysis was performed by the WebGestaltR package. Then, the miRNA-mRNA network was presented by Cytoscape, and the protein-protein interactions (PPI) network was constructed by STRING. MCODE was mined by mature MCODE algorithm. Immune infiltration analysis was conducted by ESTIMATER and ssGSEA analysis. A diagnosis model was established by SVM algorithm.
RESULTS
In the GSE dataset, CTEPH samples had a lower GOBP_RESPONSE_- TO_OXIDATIVE_STRESS score. A total of 628 DEGs and 31 DEMs were identified between CTEPH and normal samples. Afterward, DEGs were intersected with genes, which correlated with the GOBP_RESPONSE_TO_OXIDATIVE_STRESS score. A 26 DEMs-152 DEGs network was constructed, and a PPI network was established based on 152 DEGs to find 149 target genes. From the above 149 target genes, 3 modules were extracted to obtain 15 core targets. Finally, 5 hub genes were obtained by the intersection of 15 core targets and genes in MCODE2. A total of 5 hub genes were positively correlated with most immune cell scores as well as GOBP_RESPONSE_TO_OXIDATIVE_ STRESS. It was found that a diagnosis model based on 5 hub genes had a well diagnostic ability for CTEPH.
CONCLUSION
We identified 5 hub genes associated with oxidative stress. It can be concluded that they may be beneficial in diagnosing CTEPH.
背景
作为一种前毛细血管性肺动脉高压，慢性血栓栓塞性肺动脉高压（CTEPH）是由不完全性肺栓塞消退引起的。本研究旨在确定预测 CTEPH 预后的生物标志物基因。
方法
从公共数据库（即基因表达综合数据库（GEO））中收集 CTEPH 的 RNAseq，包括 GSE84538 和 GSE188938，这些数据集合并为一个数据集（GSE）。通过 limma 包鉴定差异表达基因（DEG）或 miRNA（DEM）。通过 WebGestaltR 包进行功能富集分析。然后，通过 Cytoscape 呈现 miRNA-mRNA 网络，通过 STRING 构建蛋白质-蛋白质相互作用（PPI）网络。通过成熟的 MCODE 算法挖掘 MCODE。通过 ESTIMATER 和 ssGSEA 分析进行免疫浸润分析。通过 SVM 算法建立诊断模型。
结果
在 GSE 数据集，CTEPH 样本的 GOBP_RESPONSE_-TO-OXIDATIVE_STRESS 评分较低。在 CTEPH 与正常样本之间共鉴定出 628 个 DEG 和 31 个 DEM。之后，将 DEG 与与 GOBP_RESPONSE_TO-OXIDATIVE_STRESS 评分相关的基因进行了交集。构建了一个由 26 个 DEMs-152 个 DEG 组成的网络，并基于 152 个 DEG 建立了一个 PPI 网络，以找到 149 个靶基因。从上述 149 个靶基因中提取了 3 个模块，得到 15 个核心靶基因。最后，通过 15 个核心靶基因与 MCODE2 中基因的交集获得了 5 个枢纽基因。这 5 个枢纽基因与大多数免疫细胞评分和 GOBP_RESPONSE_TO-OXIDATIVE_STRESS 呈正相关。发现基于 5 个枢纽基因的诊断模型对 CTEPH 具有良好的诊断能力。
结论
我们鉴定出与氧化应激相关的 5 个枢纽基因。可以得出结论，它们可能有助于诊断 CTEPH。
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