Pang Yonghua, Liang Jiahui, Deng Yakai, Chen Weinan, Shen Yunyan, Li Jing, Wang Xin, Ren Zhiyao
Department of Orthopedics, The 904th Hospital of the Joint Logistics Support Force, People's Liberation Army of China, Wuxi, Jiangsu, China.
Department of Breast Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Front Immunol. 2025 Apr 4;16:1449355. doi: 10.3389/fimmu.2025.1449355. eCollection 2025.
Early diagnosis of Ewing sarcoma (ES) is critical for improving patient prognosis. However, the accurate diagnosis of ES remains challenging, underscoring the need for novel diagnostic biomarkers to enhance diagnostic precision and reliability. This study aimed to identify potential gene expression-based biomarkers for the diagnosis of ES.
We selected the GSE17679, GSE45544, and GSE68776 datasets from the Gene Expression Omnibus (GEO) database. After correcting for batch effects, we combined ES and normal tissue samples from the GSE17679 and GSE45544 datasets to create a combined cohort. Two-thirds of both the tumor and normal samples from the combined cohort were randomly selected for the training cohort, while the remaining one-third served as the internal validation cohort. Additionally, the GSE68776 dataset was used for external validation. To identify key diagnostic genes, we applied three machine learning algorithms: least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF).
HOXC6 was identified as a key diagnostic biomarker for ES. It demonstrated strong diagnostic performance across all cohorts, with area under the curve (AUC) values of 0.956 (95% CI: 0.909-0.990) in the training cohort, 0.995 (95% CI: 0.977-1.000) in the internal validation cohort, and 0.966 (95% CI: 0.910-0.999) in the external validation cohort. Functional validation through HOXC6 knockdown in the RD-ES cell line revealed that its suppression significantly inhibited cell proliferation and migration. Furthermore, transcriptome sequencing suggested potential oncogenic mechanisms underlying HOXC6 function.
These findings highlight HOXC6 as a promising diagnostic biomarker for ES, demonstrating robust performance across multiple datasets. Additionally, its functional role suggests potential as a therapeutic target.
尤因肉瘤(ES)的早期诊断对于改善患者预后至关重要。然而,ES的准确诊断仍然具有挑战性,这突出了需要新的诊断生物标志物来提高诊断的准确性和可靠性。本研究旨在确定基于基因表达的潜在ES诊断生物标志物。
我们从基因表达综合数据库(GEO)中选择了GSE17679、GSE45544和GSE68776数据集。在校正批次效应后,我们将来自GSE17679和GSE45544数据集的ES和正常组织样本合并,创建一个合并队列。从合并队列中随机选择肿瘤和正常样本的三分之二作为训练队列,其余三分之一作为内部验证队列。此外,GSE68776数据集用于外部验证。为了确定关键诊断基因,我们应用了三种机器学习算法:最小绝对收缩和选择算子(LASSO)、支持向量机递归特征消除(SVM-RFE)和随机森林(RF)。
HOXC6被确定为ES的关键诊断生物标志物。它在所有队列中均表现出强大的诊断性能,训练队列中的曲线下面积(AUC)值为0.956(95%CI:0.909-0.990),内部验证队列中为0.995(95%CI:0.977-1.000),外部验证队列中为0.966(95%CI:0.910-0.999)。通过在RD-ES细胞系中敲低HOXC6进行功能验证,结果显示其抑制显著抑制了细胞增殖和迁移。此外,转录组测序揭示了HOXC6功能潜在的致癌机制。
这些发现突出了HOXC6作为ES有前景的诊断生物标志物,在多个数据集中表现出强大性能。此外,其功能作用表明它有作为治疗靶点的潜力。