Combined gene expression and protein interaction analysis of dynamic modularity in glioma prognosis

Abstract

Because of the variety of factors affecting glioma prognosis, prediction of patient survival is particularly difficult. Protein-protein interaction (PPI) networks have been considered with regard to how their spatial characteristics relate to glioma. However, the dynamic nature of PPIs in vivo makes them temporally and spatially complex events. Integration of prognosis-specific co-expression information adds further dynamic features to these networks. Although some biomarkers for glioma prognosis have been identified, none is sufficient for accurate prediction of either prognosis or improved survival. We have established co-expressed protein-interaction networks that integrate protein-protein interactions with glioma gene-expression profiles related to different survival times. Biomarkers related to glioma prognosis were identified by comparative analysis of the dynamic features of the glioma prognosis network, particularly subnetworks. Four significantly differently expressed genes (SDEGs) are upregulated and ten SDEGs downregulated as lifetime is extended. In addition, 97 enhanced differently co-expressed protein interactions (DCPIs) and 99 weakened DCPIs were associated with glioma patient lifetime extension. We propose a method for estimating glioma prognosis on the basis of the construction of a dynamic modular network. We have used this method to identify dynamic genes and interactions related to glioma prognosis. Among these, enhanced MYC expression was related to lifetime extension, as were interactions between E2F1 and RB1 and between EGFR and p38. This method is a novel means of studying the molecular mechanisms determining prognosis in glioma.

Impact of nuclear factor erythroid-derived 2–like 2 and p62/sequestosome expression on prognosis of patients with gliomas

“…The 5-year survival rates of low-grade gliomas and high-grade gliomas were 30% to 70% and less than 10%, respectively [2,3]. The median survival time of glioblastoma (GB; the most aggressive type of glioma) was only 9 to 12 months [4]. Only 0.05% to 4.7% of GB patients survived for 5 years after diagnosis [1].…”

microRNA-328 is a favorable prognostic marker in human glioma via suppressing invasive and proliferative phenotypes of malignant cells

“…GBM (WHO grade IV), which is highly infiltrative making complete surgical resection impossible, is characterized by a dismal prognosis, with a median survival of approximately 1 year [3]. The current standard therapy for this disease includes maximal safe resection followed by radiotherapy in combination with temozolomide [4]. However, the tumors progress rapidly, demonstrating relative resistance to both radiotherapy and most chemotherapeutic agents.…”

TGF-β-induced miR10a/b expression promotes human glioma cell migration by targeting PTEN

“…Despite the recent advances in surgery, radiotherapy and chemotherapy, the survival chances of patients with glioma remain poor. The median overall survival of patients with malignant glioma is <1 year and local recurrence occurs in >90% of patients (2). As the survival rates of cancer patients improve, the incidence of brain metastases is rising (3).…”