Screening and Studying of Blood miRNAs as Potential Diagnostic Markers for Papillary Thyroid Carcinoma.

IF 2.7 4区医学 Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

OncoTargets and therapy Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI:10.2147/OTT.S489559

Xize Li, Wen Qin, Wenting Wang, Weilin Liu, Tianyi Dong, Aixiang Liu, Haojie Cai, Zhouhan Xu, Jiping Zeng

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引用次数: 0

Abstract

Objective: MiRNAs play a pivotal role in tumorigenesis and development by exerting negative regulation on the expression of target genes. In this study, bioinformatics techniques and online database were employed to investigate the specific miRNA-target gene regulatory network in PTC, which was subsequently validated using human blood samples and compared to existing tumor markers.

Methods: The miRNA (GSE50901) and Gene Expression (GSE113629) chip screening data of human PTC tissues were retrieved from GEO database. A comparative analysis was conducted using the GEO2R to identify differentially expressed miRNAs and target genes of the patients with PTC. Prediction of the miRNA-target gene regulatory network, related signal transduction pathways, biological effects and their relationship to prognosis was performed based on GO, KEGG, qRT-PCR detection of human blood samples, analysis of correlation on the existing pathological tumor markers, and ROC.

Results: Compared to the corresponding normal thyroid tissues, a total of 2116 miRNAs were found to be differentially expressed in PTC patients, including 1968 up-regulated and 148 down-regulated genes. The abnormally expressed genes primarily participated in signal pathways associated with tumorigenesis and abnormal gene transcription. By utilizing data from the GEO database, five miRNAs closely linked to PTC prognosis were identified, which were miR-221-3p, miR-222-3p, miR-182-5p, miR-135a-5p, and miR-34a-5p, with elucidating the target genes. Experimental validation, correlation analysis with tumor markers along with bioinformatics analysis revealed a significant increase in expression levels of miR-182-5p in PTC patients which positively correlated with poor prognosis. These molecules could play crucial roles in both initiation and progression of PTC.

Conclusion: This study identified potential novel blood-based miRNA biomarkers for PTC through bioinformatics analysis combined with the detection of human blood samples, thereby offering new possibilities for significant biomarkers associated with diagnosis and prognosis of PTC.

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血液 miRNAs 作为甲状腺乳头状癌潜在诊断标志物的筛选和研究

目的miRNA通过对靶基因的表达进行负调控，在肿瘤发生和发展过程中发挥着关键作用。本研究利用生物信息学技术和在线数据库研究了 PTC 中特定的 miRNA-靶基因调控网络，随后利用人体血液样本进行了验证，并与现有的肿瘤标志物进行了比较：方法：从 GEO 数据库中检索了人类 PTC 组织的 miRNA（GSE50901）和基因表达（GSE113629）芯片筛选数据。利用 GEO2R 进行比较分析，以确定 PTC 患者中差异表达的 miRNA 和靶基因。根据GO、KEGG、人体血液样本的qRT-PCR检测、现有病理肿瘤标志物的相关性分析和ROC，对miRNA-靶基因调控网络、相关信号转导通路、生物学效应及其与预后的关系进行了预测：结果发现：与相应的正常甲状腺组织相比，PTC 患者共有 2116 个 miRNAs 存在差异表达，其中包括 1968 个上调基因和 148 个下调基因。异常表达的基因主要参与与肿瘤发生相关的信号通路和异常基因转录。通过利用GEO数据库的数据，发现了5个与PTC预后密切相关的miRNA，分别是miR-221-3p、miR-222-3p、miR-182-5p、miR-135a-5p和miR-34a-5p，并阐明了其靶基因。实验验证、与肿瘤标志物的相关性分析以及生物信息学分析表明，miR-182-5p 在 PTC 患者中的表达水平显著增加，与预后不良呈正相关。这些分子可能在 PTC 的发生和发展过程中发挥关键作用：本研究通过生物信息学分析和人体血液样本检测，发现了潜在的新型血液 miRNA 生物标志物，从而为寻找与 PTC 诊断和预后相关的重要生物标志物提供了新的可能性。

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来源期刊

OncoTargets and therapy BIOTECHNOLOGY & APPLIED MICROBIOLOGY-ONCOLOGY

CiteScore

9.70

自引率

0.00%

发文量

221

审稿时长

1 months

期刊介绍： OncoTargets and Therapy is an international, peer-reviewed journal focusing on molecular aspects of cancer research, that is, the molecular diagnosis of and targeted molecular or precision therapy for all types of cancer. The journal is characterized by the rapid reporting of high-quality original research, basic science, reviews and evaluations, expert opinion and commentary that shed novel insight on a cancer or cancer subtype. Specific topics covered by the journal include: -Novel therapeutic targets and innovative agents -Novel therapeutic regimens for improved benefit and/or decreased side effects -Early stage clinical trials Further considerations when submitting to OncoTargets and Therapy: -Studies containing in vivo animal model data will be considered favorably. -Tissue microarray analyses will not be considered except in cases where they are supported by comprehensive biological studies involving multiple cell lines. -Biomarker association studies will be considered only when validated by comprehensive in vitro data and analysis of human tissue samples. -Studies utilizing publicly available data (e.g. GWAS/TCGA/GEO etc.) should add to the body of knowledge about a specific disease or relevant phenotype and must be validated using the authors’ own data through replication in an independent sample set and functional follow-up. -Bioinformatics studies must be validated using the authors’ own data through replication in an independent sample set and functional follow-up. -Single nucleotide polymorphism (SNP) studies will not be considered.