Hierarchical control of coherent gene clusters defines the molecular mechanisms of glioblastoma. Issue 4 (4th February 2015)

• Record Type: Journal Article
• Authors: Tsigelny, Igor F.; Kouznetsova, Valentina L.; Jiang, Pengfei; Pingle, Sandeep C.; Kesari, Santosh
• Is Part Of: Molecular bioSystems. Volume 11:Issue 4(2015:Apr.)
• Page Start: 1012
• Page End: 1028
• Publication Date: 2015-02-04
• Subjects: Molecular biology -- Periodicals; Biochemistry -- Periodicals; 571.7405
• DOI: 10.1039/c5mb00007f
• Languages: English
• ISSNs: 1742-206X

Abstract

Abstract : We report an integrative networks-based analysis to identify a system of coherent gene modules in primary and secondary glioblastoma. Abstract : 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.