Integrated profiling reveals a global correlation between epigenetic and genetic alterations in mesothelioma.
ABSTRACT Development of mesothelioma is linked mainly to asbestos exposure, but the combined contributions of genetic and epigenetic alterations are unclear. We investigated the potential relationships between gene copy number (CN) alterations and DNA methylation profiles in a case series of pleural mesotheliomas (n = 23). There were no instances of significantly correlated CN alteration and methylation at probed loci, whereas averaging loci over their associated genes revealed only two genes with significantly correlated CN and methylation alterations. In contrast to the lack of discrete correlations, the overall extent of tumor CN alteration was significantly associated with DNA methylation profile when comparing CN alteration extent among methylation profile classes. Further, there was evidence that this association was partially attributable to prevalent allele loss at the DNA methyltransferase gene DNMT1. Our findings define a strong association between global genetic and global epigenetic dysregulation in mesothelioma, rather than a discrete, local coordination of gene inactivation.
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ABSTRACT: It is now appreciated that both genetic alteration, e.g. mutations, and aberrant epigenetic changes, e.g. DNA methylation, cause cancer. Epigenetic dysregulation is potentially reversible which makes it attractive as targets for cancer prevention. Synthetic drugs targeting enzymes, e.g. DNA methyltransferase and histone deacetylase, that regulate epigenetic patterns are active in clinical settings. In addition, dietary factors have been suggested to have potential to reverse aberrant epigenetic patterns. Uncovering the human epigenome can lead us to better understand the dynamics of DNA methylation in disease progression which can further assist in cancer prevention.FEBS letters 11/2010; 585(13):2129-36. · 3.54 Impact Factor
Article: Cell cycle and aging, morphogenesis, and response to stimuli genes are individualized biomarkers of glioblastoma progression and survival.[show abstract] [hide abstract]
ABSTRACT: Glioblastoma is a complex multifactorial disorder that has swift and devastating consequences. Few genes have been consistently identified as prognostic biomarkers of glioblastoma survival. The goal of this study was to identify general and clinical-dependent biomarker genes and biological processes of three complementary events: lifetime, overall and progression-free glioblastoma survival. A novel analytical strategy was developed to identify general associations between the biomarkers and glioblastoma, and associations that depend on cohort groups, such as race, gender, and therapy. Gene network inference, cross-validation and functional analyses further supported the identified biomarkers. A total of 61, 47 and 60 gene expression profiles were significantly associated with lifetime, overall, and progression-free survival, respectively. The vast majority of these genes have been previously reported to be associated with glioblastoma (35, 24, and 35 genes, respectively) or with other cancers (10, 19, and 15 genes, respectively) and the rest (16, 4, and 10 genes, respectively) are novel associations. Pik3r1, E2f3, Akr1c3, Csf1, Jag2, Plcg1, Rpl37a, Sod2, Topors, Hras, Mdm2, Camk2g, Fstl1, Il13ra1, Mtap and Tp53 were associated with multiple survival events.Most genes (from 90 to 96%) were associated with survival in a general or cohort-independent manner and thus the same trend is observed across all clinical levels studied. The most extreme associations between profiles and survival were observed for Syne1, Pdcd4, Ighg1, Tgfa, Pla2g7, and Paics. Several genes were found to have a cohort-dependent association with survival and these associations are the basis for individualized prognostic and gene-based therapies. C2, Egfr, Prkcb, Igf2bp3, and Gdf10 had gender-dependent associations; Sox10, Rps20, Rab31, and Vav3 had race-dependent associations; Chi3l1, Prkcb, Polr2d, and Apool had therapy-dependent associations. Biological processes associated glioblastoma survival included morphogenesis, cell cycle, aging, response to stimuli, and programmed cell death. Known biomarkers of glioblastoma survival were confirmed, and new general and clinical-dependent gene profiles were uncovered. The comparison of biomarkers across glioblastoma phases and functional analyses offered insights into the role of genes. These findings support the development of more accurate and personalized prognostic tools and gene-based therapies that improve the survival and quality of life of individuals afflicted by glioblastoma multiforme.BMC Medical Genomics 06/2011; 4:49. · 3.69 Impact Factor