Scientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Department of Pediatrics, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Thromb Res. 2023 Mar;223:131-138. doi: 10.1016/j.thromres.2023.01.029. Epub 2023 Feb 2.
Essential thrombocythemia (ET) is a rare myeloproliferative malignancy which may lead to severe thrombohemorrhagic complications. The diagnosis of ET is primarily based on bone marrow morphology and exclusion of other possibilities of myeloproliferative neoplastic diseases; the lack of gene biomarkers fails to provide a prompt diagnosis of ET. Therefore, this study was designed to identify biomarkers for early ET diagnosis, especially that associated with immune cell infiltration, by using the Gene Expression Omnibus (GEO) database and machine-learning algorithms.
Two publicly available gene expression profiles (GSE9827 and GSE123732) from the GEO database were used to identify the differentially expressed genes (DEGs) between bone marrow samples of ET patients and healthy individuals, and functional enrichment analyses were conducted. The least absolute shrinkage and selection operator (LASSO) regression model and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) machine-learning algorithm were performed to select the candidate gene biomarker. The expression level and diagnostic effectiveness of the identified gene biomarker were further validated using GSE567 and GSE2006 datasets. The involvement of infiltrating immune cells and their correlations with the gene biomarker were examined using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm.
There were 105 DEGs identified between ET and healthy control samples. Disease Ontology (DO) analysis showed that the diseases enriched by those DEGs were mainly human cancers, neurological diseases and inflammation while Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that pathways related to immune responses were primarily involved. The heat shock protein, DNAJB2, was identified as the potential biomarker for ET diagnosis with high effectiveness, with the area under the receiver operating characteristic (ROC) curve (AUC) equals to 0.905 in the validation cohort. The expression level of DNAJB2 in ET samples was indeed significantly higher than that in healthy control ones. The immune cell infiltration analysis showed that DNAJB2 was positively correlated with CD8+ T cells in ET with the proportion significantly higher than that in normal controls.
The present study identified DNAJB2 as a novel diagnostic biomarker for ET with high effectiveness based on ET and normal samples from the GEO database, which provides new insights into predicting ET with accuracy and promptness in clinical practice.
特发性血小板增多症(ET)是一种罕见的骨髓增殖性恶性肿瘤,可能导致严重的血栓出血并发症。ET 的诊断主要基于骨髓形态学和排除其他骨髓增殖性肿瘤疾病的可能性;缺乏基因生物标志物无法及时诊断 ET。因此,本研究旨在通过基因表达综合数据库(GEO)和机器学习算法,寻找用于早期 ET 诊断的生物标志物,特别是与免疫细胞浸润相关的生物标志物。
使用 GEO 数据库中两个公开的基因表达谱(GSE9827 和 GSE123732),鉴定 ET 患者和健康个体骨髓样本之间的差异表达基因(DEGs),并进行功能富集分析。使用最小绝对收缩和选择算子(LASSO)回归模型和支持向量机-递归特征消除(SVM-RFE)机器学习算法筛选候选基因生物标志物。使用 GSE567 和 GSE2006 数据集进一步验证鉴定基因生物标志物的表达水平和诊断效果。使用估计相对 RNA 转录物亚群的细胞类型鉴定(CIBERSORT)算法检测浸润免疫细胞的参与及其与基因生物标志物的相关性。
在 ET 和健康对照样本之间鉴定出 105 个 DEGs。疾病本体论(DO)分析表明,这些 DEGs 富集的疾病主要是人类癌症、神经疾病和炎症,而京都基因与基因组百科全书(KEGG)分析表明,主要涉及免疫反应相关的途径。热休克蛋白 DNAJB2 被鉴定为 ET 诊断的潜在生物标志物,具有较高的有效性,在验证队列中的受试者工作特征(ROC)曲线下面积(AUC)等于 0.905。ET 样本中 DNAJB2 的表达水平确实明显高于健康对照组。免疫细胞浸润分析表明,在 ET 中,DNAJB2 与 CD8+T 细胞呈正相关,其比例明显高于正常对照。
本研究基于 GEO 数据库中的 ET 和正常样本,鉴定出 DNAJB2 是一种新的 ET 诊断生物标志物,具有较高的有效性,为临床实践中准确、及时地预测 ET 提供了新的见解。