一种新的转录因子特征的发展,准确的宫颈癌预后

IF 0.5 4区 医学 Q4 OBSTETRICS & GYNECOLOGY European journal of gynaecological oncology Pub Date : 2023-01-01 DOI:10.22514/ejgo.2023.079
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引用次数: 0

摘要

宫颈癌(CC)是妇女癌症相关死亡的主要原因。在肿瘤发展过程中,转录因子调控原癌基因和抑癌基因的转录。我们研究了使用转录因子作为宫颈癌患者预后生物标志物的可能性。从Gene Expression Omnibus数据库下载单细胞rna测序数据,以鉴定不同类型CC细胞中的特异性活化转录因子,并获得公开的CC大量rna测序和临床数据,以使用生存分析和随机生存森林方法鉴定相关的预后转录因子。使用训练和测试数据集验证了所建立的转录因子相关预测随机生存森林模型的准确性和有效性。我们在宫颈癌组织细胞中发现了特异性的活化转录因子。构建了3个转录因子(PBX4 (PBX Homeobox 4)、EBF2 (EBF转录因子2)和ZNF696(锌指蛋白696))对宫颈癌患者的预后特征,显示出良好的生存预测。基因功能富集分析提示预后特征与不同的肿瘤相关信号通路之间存在相关性。采用基于3-转录因子特征的随机生存森林模型,将宫颈癌患者分层为低危组和高危组,总生存率存在显著差异(p <0.001)。随时间变化的接收机算子特征曲线下面积对相应特征的训练和测试数据集具有较强的预测精度。CC具有转录激活的细胞异质性。我们的分析提供了一种新的与CC相关的转录因子预后模型,这些转录因子可以作为宫颈癌患者有效的预后生物标志物和潜在的治疗靶点。
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Development of a novel transcription factor signature for accurate cervical cancer prognosis
Cervical cancer (CC) is a leading cause of cancer-related deaths in women. During tumor development, transcriptional factors regulate the transcription of proto-oncogenes and tumor suppressor genes. We examined the possibility of using transcription factors as prognostic biomarkers for patients with cervical cancer. Single-cell RNA-sequencing data were downloaded from the Gene Expression Omnibus database to identify specific activated transcription factors in different types of cells from CC. Publicly available bulk RNA-sequencing and clinical data of CC were obtained to identify associated prognostic transcription factors using survival analysis and the random survival forest methods. Accuracy and effectiveness of the established transcription factor-related predictive random survival forest model were verified using training and test datasets. We identified specific activated transcription factors in tissue cells of cervical cancer. A 3-transcription factors (PBX4 (PBX Homeobox 4), EBF2 (EBF Transcription Factor 2) and ZNF696 (Zinc Finger Protein 696)) prognostic signature for patients with cervical cancer was constructed showing good survival prediction. Gene function enrichment analysis indicated a correlation between the prognostic characteristics and different signaling pathways associated with cancer. Using the random survival forest model based on the 3-transcription factor signature, patients with cervical cancer were stratified into low- and high-risk groups with significant variations in overall survival (p < 0.001). The area under the curve of the time-dependent receiver operator characteristic revealed a strong predictive accuracy for training and test datasets of the corresponding signature. CC has cellular heterogeneity of transcriptional activation. Our analyses provide a novel transcription factor-associated prognostic model for CC. These transcription factors could be used as effective prognostic biomarkers and potential therapeutic targets for patients with cervical cancer.
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来源期刊
自引率
25.00%
发文量
58
审稿时长
1 months
期刊介绍: EJGO is dedicated to publishing editorial articles in the Distinguished Expert Series and original research papers, case reports, letters to the Editor, book reviews, and newsletters. The Journal was founded in 1980 the second gynaecologic oncology hyperspecialization Journal in the world. Its aim is the diffusion of scientific, clinical and practical progress, and knowledge in female neoplastic diseases in an interdisciplinary approach among gynaecologists, oncologists, radiotherapists, surgeons, chemotherapists, pathologists, epidemiologists, and so on.
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