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文章:

结直肠癌中ASPHD1与ZBTB12的预后价值:基于机器学习的整合生物信息学分析

The Prognostic Value ofASPHD1andZBTB12in Colorectal Cancer: A Machine Learning-Based Integrated Bioinformatics Approach

原文发布日期:28 August 2023

DOI: 10.3390/cancers15174300

类型: Article

开放获取: 是

 

英文摘要:

Introduction:Colorectal cancer (CRC) is a common cancer associated with poor outcomes, underscoring a need for the identification of novel prognostic and therapeutic targets to improve outcomes. This study aimed to identify genetic variants and differentially expressed genes (DEGs) using genome-wide DNA and RNA sequencing followed by validation in a large cohort of patients with CRC.Methods:Whole genome and gene expression profiling were used to identify DEGs and genetic alterations in 146 patients with CRC. Gene Ontology, Reactom, GSEA, and Human Disease Ontology were employed to study the biological process and pathways involved in CRC. Survival analysis on dysregulated genes in patients with CRC was conducted using Cox regression and Kaplan–Meier analysis. The STRING database was used to construct a protein–protein interaction (PPI) network. Moreover, candidate genes were subjected to ML-based analysis and the Receiver operating characteristic (ROC) curve. Subsequently, the expression of the identified genes was evaluated by Real-time PCR (RT-PCR) in another cohort of 64 patients with CRC. Gene variants affecting the regulation of candidate gene expressions were further validated followed by Whole Exome Sequencing (WES) in 15 patients with CRC.Results:A total of 3576 DEGs in the early stages of CRC and 2985 DEGs in the advanced stages of CRC were identified.ASPHD1andZBTB12genes were identified as potential prognostic markers. Moreover, the combination ofASPHDandZBTB12genes was sensitive, and the two were considered specific markers, with an area under the curve (AUC) of 0.934, 1.00, and 0.986, respectively. The expression levels of these two genes were higher in patients with CRC. Moreover, our data identified two novel genetic variants—the rs925939730 variant inASPHD1and the rs1428982750 variant inZBTB1—as being potentially involved in the regulation of gene expression.Conclusions:Our findings provide a proof of concept for the prognostic values of two novel genes—ASPHD1andZBTB12—and their associated variants (rs925939730 and rs1428982750) in CRC, supporting further functional analyses to evaluate the value of emerging biomarkers in colorectal cancer.

 

摘要翻译: 

引言:结直肠癌是一种常见且预后较差的恶性肿瘤,亟需寻找新的预后标志物和治疗靶点以改善患者结局。本研究旨在通过全基因组DNA和RNA测序技术鉴定遗传变异及差异表达基因,并在大规模结直肠癌患者队列中进行验证。 方法:通过对146例结直肠癌患者进行全基因组测序和基因表达谱分析,鉴定差异表达基因及遗传变异。采用基因本体论、Reactom通路数据库、基因集富集分析和人类疾病本体论探究结直肠癌相关的生物学过程及信号通路。运用Cox回归和Kaplan-Meier法对结直肠癌患者差异表达基因进行生存分析,并通过STRING数据库构建蛋白质相互作用网络。对候选基因进行机器学习分析及受试者工作特征曲线评估。随后在64例结直肠癌患者队列中通过实时荧光定量PCR验证目标基因表达水平,并对15例患者进行全外显子组测序,进一步验证影响候选基因表达的遗传变异。 结果:研究共鉴定出结直肠癌早期阶段3576个差异表达基因和晚期阶段2985个差异表达基因。ASPHD1和ZBTB12基因被确定为潜在预后标志物。联合检测ASPHD1和ZBTB12基因具有较高敏感性,两者作为特异性标志物的曲线下面积分别为0.934、1.00和0.986。这两个基因在结直肠癌患者中表达水平显著升高。此外,研究新发现两个可能参与基因表达调控的遗传变异:ASPHD1基因的rs925939730变异和ZBTB12基因的rs1428982750变异。 结论:本研究从概念上验证了ASPHD1和ZBTB12这两个新型基因及其相关变异(rs925939730和rs1428982750)在结直肠癌中的预后价值,为开展进一步功能学研究以评估新兴生物标志物在结直肠癌中的应用价值提供了依据。

 

原文链接:

The Prognostic Value ofASPHD1andZBTB12in Colorectal Cancer: A Machine Learning-Based Integrated Bioinformatics Approach

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