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通过临床数据库分析和 Kaplan-Meier 曲线分析鉴定结直肠癌的潜在生物标志物。

Identification of potential biomarkers for colorectal cancer by clinical database analysis and Kaplan-Meier curves analysis.

机构信息

Second Clinical Medical College, Binzhou Medical University, Yantai, China.

Department of General Surgery Center, Linyi People's Hospital, Linyi, China.

出版信息

Medicine (Baltimore). 2023 Feb 10;102(6):e32877. doi: 10.1097/MD.0000000000032877.

Abstract

This study aimed to explore critical genes as potential biomarkers for the diagnosis and prognosis of colorectal cancer (CRC) for clinical utility. To identify and screen candidate genes involved in CRC carcinogenesis and disease progression, we downloaded microarray datasets GSE89076, GSE73360, and GSE32323 from the GEO database identified differentially expressed genes (DEGs), and performed a functional enrichment analysis. A protein-protein interaction network was constructed, and correlated module analysis was performed using STRING and Cytoscape. The Kaplan-Meier survival curve shows the survival of the hub genes. The expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), and PCNA in tissues and changes in tumor grade were analyzed. A total of 329 DEGs were identified, including 264 upregulated and 65 downregulated genes. The functions and pathways of DEGs include the mitotic cell cycle, poly(A) RNA binding replication, ATP binding, DNA replication, ribosome biogenesis in eukaryotes, and RNA transport. Forty-seven Hub genes were identified, and biological process analysis showed that these genes were mainly enriched in cell cycle and DNA replication. Patients with mutations in CDK1, PCNA, and CCNB1 had poorer survival rates. CDK1, PCNA, and CCNB1 were significantly overexpressed in the tumor tissues. The expression of CDK1 and CCNB1 gradually decreased with increasing tumor grade. CDK1, CCNB1, and PCNA can be used as potential markers for the diagnosis and prognosis of CRC. These genes are overexpressed in colon cancer tissues and are associated with low survival rates in CRC patients.

摘要

本研究旨在探索关键基因作为结直肠癌(CRC)诊断和预后的潜在生物标志物,以实现临床应用。为了鉴定和筛选参与 CRC 发生和疾病进展的候选基因,我们从 GEO 数据库中下载了微阵列数据集 GSE89076、GSE73360 和 GSE32323,识别差异表达基因(DEGs),并进行了功能富集分析。构建了蛋白质-蛋白质相互作用网络,并使用 STRING 和 Cytoscape 进行了相关模块分析。Kaplan-Meier 生存曲线显示了关键基因的生存情况。分析了组织中细胞周期蛋白依赖性激酶(CDK1)、细胞周期蛋白 B1(CCNB1)和 PCNA 的表达以及肿瘤分级的变化。共鉴定出 329 个 DEGs,包括 264 个上调基因和 65 个下调基因。DEGs 的功能和通路包括有丝分裂细胞周期、多(A)RNA 结合复制、ATP 结合、DNA 复制、真核生物核糖体生物发生和 RNA 转运。鉴定出 47 个 Hub 基因,生物过程分析表明这些基因主要富集在细胞周期和 DNA 复制中。CDK1、PCNA 和 CCNB1 突变的患者生存率较差。CDK1、PCNA 和 CCNB1 在肿瘤组织中表达明显上调。随着肿瘤分级的增加,CDK1 和 CCNB1 的表达逐渐降低。CDK1、CCNB1 和 PCNA 可作为 CRC 诊断和预后的潜在标志物。这些基因在结肠癌组织中过度表达,与 CRC 患者的低生存率相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/015b/9907961/21b8220ea256/medi-102-e32877-g001.jpg

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