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Integrative analysis of novel hypomethylation and gene expression signatures in glioblastomas.

ABSTRACT: Molecular and clinical heterogeneity critically hinders better treatment outcome for glioblastomas (GBMs); integrative analysis of genomic and epigenomic data may provide useful information for improving personalized medicine. By applying training-validation approach, we identified a novel hypomethylation signature comprising of three CpGs at non-CpG island (CGI) open sea regions for GBMs. The hypomethylation signature consistently predicted poor prognosis of GBMs in a series of discovery and validation datasets. It was demonstrated as an independent prognostic indicator, and showed interrelationships with known molecular marks such as MGMT promoter methylation status, and glioma CpG island methylator phenotype (G-CIMP) or IDH1 mutations. Bioinformatic analysis found that the hypomethylation signature was closely associated with the transcriptional status of an EGFR/VEGFA/ANXA1-centered gene network. The integrative molecular analysis finally revealed that the gene network defined two distinct clinically relevant molecular subtypes reminiscent of different immature neuroglial lineages in GBMs. The novel hypomethylation signature and relevant gene network may provide new insights into prognostic classification, molecular characterization, and treatment development for GBMs.

SUBMITTER: Yin A

PROVIDER: S-EPMC5685695 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Integrative analysis of novel hypomethylation and gene expression signatures in glioblastomas.

Yin Anan A Etcheverry Amandine A He Yalong Y Aubry Marc M Barnholtz-Sloan Jill J Zhang Luhua L Mao Xinggang X Chen Weijun W Liu Bolin B Zhang Wei W Mosser Jean J Zhang Xiang X

Oncotarget 20170711 52

Molecular and clinical heterogeneity critically hinders better treatment outcome for glioblastomas (GBMs); integrative analysis of genomic and epigenomic data may provide useful information for improving personalized medicine. By applying training-validation approach, we identified a novel hypomethylation signature comprising of three CpGs at non-CpG island (CGI) open sea regions for GBMs. The hypomethylation signature consistently predicted poor prognosis of GBMs in a series of discovery and va ...[more]

PMID: 29163774

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Project description:BackgroundDengue is a major arthropod-borne viral disease spreading rapidly across the globe. The absence of vaccines and inadequate vector control measures leads to further expansion of dengue in many regions globally. Hence, the identification of genes involved in the pathogenesis of dengue will help to understand the molecular basis of the disease and the genes responsible for the disease progression.MethodsIn the present study, a meta-analysis was carried out using dengue gene expression data obtained from Gene Expression Omnibus repository. The differentially expressed genes such as CCNB1 and CCNB2 (G2/mitotic-specific cyclin-B2 and B1) were upregulated in dengue fever to control (DF-CO) and severe dengue (dengue hemorrhagic fever [DHF]) to control (DHF-CO) were identified as key genes for controlling the major pathways (cell cycle, oocyte meiosis, p53 signaling pathway, cellular senescence and progesterone-mediated oocyte maturation). Similarly, interferon alpha-inducible (IFI27) genes, type-I and type-III interferon (IFN) signaling genes (STAT1 and STAT2), B cell activation and survival genes (TNFSF13B, TNFRSF17) and toll like receptor (TLR7) genes were differentially up activated during DF-CO and DHF-CO. Followed by, Cytoscape was used to identify the immune system process and topological analysis.ResultsThe results showed that the top differentially expressed genes under the statistical significance p <0.001, which is majorly involved in Kyoto Encyclopedia of Genes and Genomes orthology K05868 and K21770 with gene names CCNB1 and CCNB2. In addition to this, the immune system profile showed up-regulation of IL12A, CXCR3, TNFSF13B, IFI27, TNFRSF17, STAT, STAT2, and TLR7 genes in DF-CO and DHF-CO act as immunological signatures for inducing the immune response towards dengue infection.ConclusionsThe current study could aid in understanding of molecular pathogenesis, genes and corresponding pathway upon dengue infection, and could facilitate for identification of novel drug targets and prognostic markers.

Dataset Information

Integrative analysis of novel hypomethylation and gene expression signatures in glioblastomas.

Publications

Integrative analysis of novel hypomethylation and gene expression signatures in glioblastomas.

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