Department of Biostatistics (Section on Statistical Genetics), University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
PLoS One. 2012;7(1):e29653. doi: 10.1371/journal.pone.0029653. Epub 2012 Jan 5.
Previous reports have implicated an induction of genes in IFN/STAT1 (Interferon/STAT1) signaling in radiation resistant and prosurvival tumor phenotypes in a number of cancer cell lines, and we have hypothesized that upregulation of these genes may be predictive of poor survival outcome and/or treatment response in Glioblastoma Multiforme (GBM) patients. We have developed a list of 8 genes related to IFN/STAT1 that we hypothesize to be predictive of poor survival in GBM patients. Our working hypothesis that over-expression of this gene signature predicts poor survival outcome in GBM patients was confirmed, and in addition, it was demonstrated that the survival model was highly subtype-dependent, with strong dependence in the Proneural subtype and no detected dependence in the Classical and Mesenchymal subtypes. We developed a specific multi-gene survival model for the Proneural subtype in the TCGA (the Cancer Genome Atlas) discovery set which we have validated in the TCGA validation set. In addition, we have performed network analysis in the form of Bayesian Network discovery and Ingenuity Pathway Analysis to further dissect the underlying biology of this gene signature in the etiology of GBM. We theorize that the strong predictive value of the IFN/STAT1 gene signature in the Proneural subtype may be due to chemotherapy and/or radiation resistance induced through prolonged constitutive signaling of these genes during the course of the illness. The results of this study have implications both for better prediction models for survival outcome in GBM and for improved understanding of the underlying subtype-specific molecular mechanisms for GBM tumor progression and treatment response.
先前的报告表明,在许多癌细胞系中,IFN/STAT1(干扰素/STAT1)信号转导中的基因诱导与辐射抗性和促进存活的肿瘤表型有关,我们假设这些基因的上调可能是胶质母细胞瘤(GBM)患者生存结局和/或治疗反应不良的预测因子。我们已经确定了一组与 IFN/STAT1 相关的 8 个基因,我们假设这些基因与 GBM 患者的不良生存相关。我们的工作假设是,该基因特征的过表达预测了 GBM 患者的不良生存结果,这一假设得到了证实,此外,还表明该生存模型高度依赖于亚型,在神经前亚型中依赖性很强,而在经典型和间质型中则没有检测到依赖性。我们在 TCGA(癌症基因组图谱)发现集中为神经前亚型开发了一个特定的多基因生存模型,并在 TCGA 验证集中进行了验证。此外,我们还进行了贝叶斯网络发现和 IPA(Ingenuity Pathway Analysis)形式的网络分析,以进一步剖析该基因特征在 GBM 发病机制中的潜在生物学。我们推测,IFN/STAT1 基因特征在神经前亚型中的强预测价值可能是由于这些基因在疾病过程中的持续组成性信号导致的化疗和/或辐射抗性。这项研究的结果不仅对 GBM 生存结局的更好预测模型具有意义,而且对深入了解 GBM 肿瘤进展和治疗反应的潜在亚型特异性分子机制也具有意义。