METHODS: Transcriptional expression profiling including a control (untreated) and three groups receiving α2b-interferon, γ-interferon and HeberFERON was performed using an Illumina HT-12 microarray platform. Unsupervised methods for gene and sample grouping, identification of differentially expressed genes, functional enrichment and network analysis computational biology methods were applied to identify distinctive transcription patterns of HeberFERON. Validation of most representative genes was performed by qPCR. For the cell cycle analysis of cells treated with HeberFERON for 24 h, 48 and 72 h we used flow cytometry.
RESULTS: The three treatments show different behavior based on the gene expression profiles. The enrichment analysis identified several mitotic cell cycle related events, in particular from prometaphase to anaphase, which are exclusively targeted by HeberFERON. The FOXM1 transcription factor network that is involved in several cell cycle phases and is highly expressed in GBMs, is significantly down regulated. Flow cytometry experiments corroborated the action of HeberFERON on the cell cycle in a dose and time dependent manner with a clear cellular arrest as of 24 h post-treatment. Despite the fact that p53 was not down-regulated, several genes involved in its regulatory activity were functionally enriched. Network analysis also revealed a strong relationship of p53 with genes targeted by HeberFERON. We propose a mechanistic model to explain this distinctive action, based on the simultaneous activation of PKR and ATF3, p53 phosphorylation changes, as well as its reduced MDM2 mediated ubiquitination and export from the nucleus to the cytoplasm. PLK1, AURKB, BIRC5 and CCNB1 genes, all regulated by FOXM1, also play central roles in this model. These and other interactions could explain a G2/M arrest and the effect of HeberFERON on the proliferation of U-87MG.
CONCLUSIONS: We proposed molecular mechanisms underlying the distinctive behavior of HeberFERON compared to the treatments with the individual interferons in U-87MG model, where cell cycle related events were highly relevant.
方法:转录表达谱包括对照组(未治疗)和接受α2b-干扰素的三组,使用IlluminaHT-12微阵列平台进行γ-干扰素和HeberFERON。无监督的基因和样本分组方法,差异表达基因的鉴定,应用功能富集和网络分析计算生物学方法来鉴定HeberFERON的独特转录模式。大多数代表性基因的验证通过qPCR进行。对于用HeberFERON处理24小时的细胞的细胞周期分析,48和72小时,我们使用流式细胞术。
结果:基于基因表达谱,三种处理显示出不同的行为。富集分析确定了几个有丝分裂细胞周期相关事件,特别是从前中期到后期,这是Heberferon的唯一目标。FOXM1转录因子网络参与多个细胞周期阶段,在GBM中高度表达,大幅下调。流式细胞术实验证实了HeberFERON以剂量和时间依赖性方式对细胞周期的作用,治疗后24小时有明显的细胞停滞。尽管p53没有下调,在功能上富集了几个参与其调节活性的基因。网络分析还揭示了p53与HeberFERON靶向基因的强关系。我们提出了一个机械模型来解释这种独特的行为,基于PKR和ATF3的同时激活,p53磷酸化改变,以及其减少的MDM2介导的泛素化和从细胞核到细胞质的输出。PLK1,AURKB,BIRC5和CCNB1基因,所有这些都由FOXM1监管,在这一模式中也起着核心作用。这些和其他相互作用可以解释G2/M阻滞和HeberFERON对U-87MG增殖的影响。
结论:我们提出了与U-87MG模型中单个干扰素治疗相比,HeberFERON独特行为的分子机制,其中细胞周期相关事件高度相关。