Identifying microRNA-mRNA regulatory network in gemcitabine-resistant cells derived from human pancreatic cancer cells
Identifying microRNA-mRNA regulatory network in gemcitabine-resistant cells derived from human pancreatic cancer cells
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DOI：
10.1007/s13277-015-3097-8
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发表时间：
2015-06-01
期刊：
影响因子：
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通讯作者：
Meng, Zhiqiang
中科院分区：
文献类型：
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作者：
Shen, Yehua;Pan, Yan;Meng, Zhiqiang
由于早期诊断困难，超过80%的患者无法切除胰腺癌。化疗是晚期胰腺癌最常用的治疗方法。吉西他滨(GEM)是标准化疗中常用的药物，其耐药性的产生往往导致治疗失败。然而，吉西他滨耐药的分子机制仍不清楚。因此，我们试图探索与吉西他滨耐药相关的microRNA-mRNA网络，并寻找克服吉西他滨耐药的分子靶点。通过将SW1990胰腺癌细胞长期暴露于浓度递增的吉西他滨，我们建立了一株对吉西他滨耐药的细胞株(SW1990/GEM)，该细胞株具有较高的IC_(50)(生长抑制50%所需浓度，847.23 mU/M)。RNA-seq分析检测SW1990细胞和SW1990/GEM细胞的mRNA和microRNA表达谱。通过比较对照SW1990细胞的结果，确定了SW1990/GEM细胞中507个上调基因和550个下调基因是与吉西他滨敏感性相关的差异表达基因。基因本体论(GO)分析表明，差异表达基因与不同的生物学过程有关。上调的基因主要与药物反应和细胞凋亡有关，下调的基因主要与细胞周期进展和RNA剪接相关。同时，在SW1990/GEM细胞中也检测到了在耐药发展中起重要作用的差异表达的microRNAs，共鉴定出56个差异microRNAs。此外，通过Q-PCR分析确定了所选基因和microRNAs的表达谱。进一步，结合差异表达的microRNAs和mRNAs以及这些microRNAs的预测靶点，构建了一个核心的microRNA-mRNA调控网络，其中包括枢纽microRNAs，如hsa-miR-643、hsa-miR-4644、hsa-miR-4650-5p、hsa-miR-4455、hsa-miR-1261和hsa-miR-3676。在已鉴定的差异基因中，也观察到了microRNA-mRNA网络中这些中枢microRNAs的预测靶标。因此，构建了吉西他滨耐药胰腺癌细胞的差异基因和microRNA表达模式。因此，这些数据可能有助于胰腺癌患者耐药的检测和治疗，基于microRNA-mRNA网络的分析有望更有效，并为深入了解耐药的分子机制提供依据。
Pancreatic cancer is unresectable in over 80 % of patients owing to difficulty in early diagnosis. Chemotherapy is the most frequently adopted therapy for advanced pancreatic cancer. The development of drug resistance to gemcitabine (GEM), which is always used in standard chemotherapy, often results in therapeutic failure. However, the molecular mechanisms underlying the gemcitabine resistance remain unclear. Therefore, we sought to explore the microRNA-mRNA network that is associated with the development of gemcitabine resistance and to identify molecular targets for overcoming the gemcitabine resistance. By exposing SW1990 pancreatic cancer cells to long-term gemcitabine with increasing concentrations, we established a gemcitabine-resistant cell line (SW1990/GEM) with a high IC50 (the concentration needed for 50 % growth inhibition, 847.23 mu M). The mRNA and microRNA expression profiles of SW1990 cells and SW1990/GEM cells were determined using RNA-seq analysis. By comparing the results in control SW1990 cells, 507 upregulated genes and 550 downregulated genes in SW1990/GEM cells were identified as differentially expressed genes correlated with gemcitabine sensitivity. Gene ontology (GO) analysis showed that the differentially expressed genes were related to diverse biological processes. The upregulated genes were mainly associated with drug response and apoptosis, and the downregulated genes were correlated with cell cycle progression and RNA splicing. Concurrently, the differentially expressed microRNAs, which are the important player in drug resistance development, were also examined in SW1990/GEM cells, and 56 differential microRNAs were identified. Additionally, the expression profiles of selected genes and microRNAs were confirmed by using Q-PCR assays. Furthermore, combining the differentially expressed microRNAs and mRNAs as well as the predicted targets for these microRNAs, a core microRNA-mRNA regulatory network was constructed, which included hub microRNAs, such as hsa-miR-643, hsa-miR-4644, hsa-miR-4650-5p, hsa-miR-4455, hsa-miR-1261, and hsa-miR-3676. The predicted targets of these hub microRNAs in the microRNA-mRNA network were also observed in the identified differential genes. As a result, a differential gene and microRNA expression pattern was constructed in gemcitabine-resistant pancreatic cancer cells. Therefore, these data may be useful for the detection and treatment of drug resistance in pancreatic cancer patients, and the microRNA-mRNA network-based analysis is expected to be more effective and provides deep insights into the molecular mechanism of drug resistance.