脑肿瘤肿瘤通路相关基因的定量分析。

Q4 Medicine
Z Majerčíková, K Dibdiaková, M Galanda, T Galanda, R Richterová, B Kolarovszki, P Račay, J Hatok
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引用次数: 0

摘要

背景:脑肿瘤是一组异质性的恶性肿瘤,其特点是肿瘤间和肿瘤内的异质性。其中,最具侵略性的,尽管医学进步,仍然无法治愈的是胶质母细胞瘤。其中一个原因是该疾病的高复发率和对替莫唑胺的耐药性,替莫唑胺是脑肿瘤化疗的黄金标准。因此,在转录水平上绘制负责肿瘤发生的途径可能有助于确定不同胶质肿瘤的原因和侵袭性行为。患者和方法:从星形细胞瘤(N = 6)、胶质母细胞瘤(N = 22)和脑膜瘤(N = 14)患者中进行活检。对照组由从健康人脑中分离的RNA组成(N = 3)。使用human Cancer PathwayFinder™实时PCR阵列以96孔格式分析逆转录的cdna。每个样本的9条信号通路(血管生成、细胞凋亡、细胞周期和衰老、DNA损伤和修复、上皮-间质转化、缺氧、整体代谢和端粒动力学)中84个基因的表达均被检测。结果:通过确定选定基因的相对表达,我们在涉及肿瘤发生的信号通路的背景下表征了个体脑恶性肿瘤的转录组谱。我们在胶质母细胞瘤、脑膜瘤和星形细胞瘤中分别观察到50%、52.4和53.6%的基因缺失。与对照组相比,与上皮-间质转化相关的基因(CDH2、FOXC2、GSC、SNAI2和SOX10)、细胞衰老(BMI1、ETS2、MAP2K1和SOD1)、DNA修复(DDB2、ERCC3、GADD45G和LIG4)和端粒动态(TEP1、TERF2IP、TNKS和TNKS2)发生了最显著的变化,且具有统计学意义。结论:根据获得的数据,我们可以得出结论,个体诊断在转录组谱上存在差异。因此,为了在脑肿瘤诊断中提供多种代谢途径的综合和靶向治疗,个体分子方法是必要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantitative profiling of genes associated with cancer pathways in brain tumors.

Background: Brain tumors are a heterogeneous group of malignancies characterized by inter- and intratumoral heterogeneity. Among them, the most aggressive and, despite advances in medicine, still incurable remains glioblastoma. One of the reasons is the high recurrence rate of the disease and resistance to temozolomide, a golden standard in chemotherapy of brain tumors. Therefore, mapping the pathways responsible for tumorigenesis at the transcriptional level may help to determine the causes and aggressive behavior among different glial tumors.

Patients and methods: Biopsies from patients with astrocytoma (N = 6), glioblastoma (N = 22), and meningioma (N = 14) were included in the sample set. A control group consisted of RNA isolated from healthy human brain (N = 3). The reverse-transcribed cDNAs were analyzed using the Human Cancer PathwayFinder™ real-time PCR Array in a 96-well format. The expression of 84 genes belonging to 9 signaling pathways (angiogenesis, apoptosis, cell cycle and senescence, DNA damage and repair, epithelial-to-mesenchymal transition, hypoxia, overall metabolism, and telomere dynamics) was determined for each sample.

Results: By determining the relative expression of selected genes, we characterized the transcriptomic profile of individual brain malignancies in the context of signaling pathways involved in tumorigenesis. We observed deregulation in 50, 52.4 and 53.6% % of the genes in glioblastomas, meningiomas and astrocytomas, respectively. The most pronounced changes with statistical significance compared to control were observed in the genes associated with epithelial-to-mesenchymal transition (CDH2, FOXC2, GSC, SNAI2, and SOX10), cellular senescence (BMI1, ETS2, MAP2K1, and SOD1), DNA repair (DDB2, ERCC3, GADD45G, and LIG4), and dynamic of telomeres (TEP1, TERF2IP, TNKS, and TNKS2).

Conclusion: Based on the obtained data, we can conclude that individual diagnoses differ in transcriptomic profile. An individual molecular approach is therefore necessary in order to provide comprehensive and targeted therapy on multiple metabolic pathways in the diagnosis of brain tumors.

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来源期刊
Klinicka Onkologie
Klinicka Onkologie Medicine-Oncology
CiteScore
1.00
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37
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