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化疗耐药非小细胞肺癌中的微小RNA表达分析及生物学通路

MicroRNA Expression Analysis and Biological Pathways in Chemoresistant Non-Small Cell Lung Cancer.

作者信息

Papadaki Chara, Mortoglou Maria, Boukouris Aristeidis E, Gourlia Krystallia, Markaki Maria, Lagoudaki Eleni, Koutsopoulos Anastasios, Tsamardinos Ioannis, Mavroudis Dimitrios, Agelaki Sofia

机构信息

Laboratory of Translational Oncology, School of Medicine, University of Crete, 71500 Heraklion, Greece.

Department of Medical Oncology, University General Hospital, 71500 Heraklion, Greece.

出版信息

Cancers (Basel). 2025 Jul 29;17(15):2504. doi: 10.3390/cancers17152504.

DOI:10.3390/cancers17152504
PMID:40805201
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12346453/
Abstract

Alterations in DNA damage repair mechanisms can impair the therapeutic effectiveness of cisplatin. MicroRNAs (miRNAs), key regulators of DNA damage repair processes, have been proposed as promising biomarkers for predicting the response to platinum-based chemotherapy (CT) in non-small cell lung cancer (NSCLC). In this study, by using a bioinformatics approach, we identified six miRNAs, which were differentially expressed (DE) between NSCLC patients characterized as responders and non-responders to platinum-based CT. We further validated the differential expression of the selected miRNAs on tumor and matched normal tissues from patients with resected NSCLC. Two miRNA microarray expression datasets were retrieved from the Gene Expression Omnibus (GEO) repository, comprising a total of 69 NSCLC patients (N = 69) treated with CT and annotated data from their response to treatment. Differential expression analysis was performed using the Linear Models for Microarray Analysis (Limma) package in R to identify DE miRNAs between responders (N = 33) and non-responders (N = 36). Quantitative real-time PCR (qRT-PCR) was used to assess miRNA expression levels in clinical tissue samples (N = 20). Analysis with the Limma package revealed 112 DE miRNAs between responders and non-responders. A random-effects meta-analysis further identified 24 miRNAs that were consistently up- or downregulated in at least two studies. Survival analysis using the Kaplan-Meier plotter (KM plotter) indicated that 22 of these miRNAs showed significant associations with prognosis in NSCLC. Functional and pathway enrichment analysis revealed that several of the identified miRNAs were linked to key pathways implicated in DNA damage repair, including the p53, Hippo, PI3K and TGF-β signaling pathways. We finally distinguished a six-miRNA signature consisting of miR-26a, miR-29c, miR-34a, miR-30e-5p, miR-30e-3p and miR-497, which were downregulated in non-responders and are involved in at least three DNA damage repair pathways. Comparative expression analysis on tumor and matched normal tissues from surgically treated NSCLC patients confirmed their differential expression in clinical samples. In summary, we identified a signature of six miRNAs that are suppressed in NSCLC and may serve as a predictor of cisplatin response in NSCLC.

摘要

DNA损伤修复机制的改变会削弱顺铂的治疗效果。微小RNA(miRNA)作为DNA损伤修复过程的关键调节因子,已被视为预测非小细胞肺癌(NSCLC)对铂类化疗(CT)反应的有前景的生物标志物。在本研究中,我们采用生物信息学方法,鉴定出六种miRNA,它们在对铂类CT有反应和无反应的NSCLC患者之间存在差异表达(DE)。我们进一步验证了所选miRNA在手术切除的NSCLC患者的肿瘤组织和配对正常组织中的差异表达。从基因表达综合数据库(GEO)中检索了两个miRNA微阵列表达数据集,共包括69例接受CT治疗的NSCLC患者(N = 69)以及他们对治疗反应的注释数据。使用R语言中的微阵列分析线性模型(Limma)软件包进行差异表达分析,以鉴定有反应者(N = 33)和无反应者(N = 36)之间的DE miRNA。采用定量实时PCR(qRT-PCR)评估临床组织样本(N = 20)中的miRNA表达水平。使用Limma软件包分析显示,有反应者和无反应者之间有112个DE miRNA。随机效应荟萃分析进一步鉴定出至少在两项研究中持续上调或下调的24个miRNA。使用Kaplan-Meier绘图仪(KM绘图仪)进行的生存分析表明,其中22个miRNA与NSCLC的预后有显著关联。功能和通路富集分析显示,鉴定出的几种miRNA与DNA损伤修复相关的关键通路有关,包括p53、Hippo、PI3K和TGF-β信号通路。我们最终区分出一个由miR-26a、miR-29c、miR-34a、miR-30e-5p、miR-30e-3p和miR-497组成的六miRNA特征序列,它们在无反应者中下调,并且参与至少三种DNA损伤修复途径。对手术治疗NSCLC患者的肿瘤组织和配对正常组织进行的比较表达分析证实了它们在临床样本中的差异表达。总之,我们鉴定出一个在NSCLC中被抑制的六miRNA特征序列,它可能作为NSCLC中顺铂反应的预测指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/16be86aa60c3/cancers-17-02504-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/e12ffa3985c9/cancers-17-02504-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/aae61a5bac8e/cancers-17-02504-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/12f641646d31/cancers-17-02504-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/3dc83263e229/cancers-17-02504-g004a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/477f0d296bdb/cancers-17-02504-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/16be86aa60c3/cancers-17-02504-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/e12ffa3985c9/cancers-17-02504-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/aae61a5bac8e/cancers-17-02504-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/12f641646d31/cancers-17-02504-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/3dc83263e229/cancers-17-02504-g004a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/477f0d296bdb/cancers-17-02504-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43a9/12346453/16be86aa60c3/cancers-17-02504-g006.jpg

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Cisplatin-induced activation of TGF-β signaling contributes to drug resistance.
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