Tsigelny Igor F, Kouznetsova Valentina L, Jiang Pengfei, Pingle Sandeep C, Kesari Santosh
Department of Neurosciences, University of California San Diego, 9500 Gilman Dr., MSC 0752, La Jolla, CA 92093-0752, USA.
Mol Biosyst. 2015 Apr;11(4):1012-28. doi: 10.1039/c5mb00007f.
Glioblastoma is a highly-aggressive and rapidly-lethal tumor characterized by resistance to therapy. Although data on multiple genes, proteins, and pathways are available, the key challenge is deciphering this information and identifying central molecular targets. Therapeutically targeting individual molecules is often unsuccessful due to the presence of compensatory and redundant pathways, and crosstalk. A systems biology approach that involves a hierarchical gene group networks analysis can delineate the coherent functions of different disease mediators. Here, we report an integrative networks-based analysis to identify a system of coherent gene modules in primary and secondary glioblastoma. Our study revealed a hierarchical transcriptional control of genes in these modules. We elucidated those modules responsible for conversion of the glioma-associated microglia/macrophages into glioma-supportive, immunosuppressive cells. Further, we identified clusters comprising mediators of angiogenesis, proliferation, and cell death for both primary and secondary glioblastomas. Data obtained for these clusters point to a possible role of transcription regulators that function as the gene modules mediators in glioblastoma pathogenesis. We elucidated a set of possible transcription regulators that can be targeted to affect the selected gene clusters at specific levels for glioblastoma. Our innovative approach to construct informative disease models may hold the key to successful management of complex diseases including glioblastoma and other cancers.
胶质母细胞瘤是一种极具侵袭性且致死率高的肿瘤,其特点是对治疗具有抗性。尽管有关于多个基因、蛋白质和信号通路的数据,但关键挑战在于解读这些信息并确定核心分子靶点。由于存在补偿性和冗余信号通路以及信号串扰,针对单个分子进行治疗往往并不成功。一种涉及分层基因组网络分析的系统生物学方法能够描绘不同疾病介质的协同功能。在此,我们报告一种基于整合网络的分析方法,以识别原发性和继发性胶质母细胞瘤中协同基因模块的系统。我们的研究揭示了这些模块中基因的分层转录调控。我们阐明了那些负责将胶质瘤相关的小胶质细胞/巨噬细胞转化为支持胶质瘤的免疫抑制细胞的模块。此外,我们为原发性和继发性胶质母细胞瘤确定了包含血管生成、增殖和细胞死亡介质的簇。从这些簇获得的数据表明转录调节因子可能在胶质母细胞瘤发病机制中作为基因模块介质发挥作用。我们阐明了一组可能的转录调节因子,针对它们可以在特定水平影响胶质母细胞瘤的选定基因簇。我们构建信息丰富的疾病模型的创新方法可能是成功管理包括胶质母细胞瘤和其他癌症在内的复杂疾病的关键。