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Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas.
Cancer Genome Atlas Research Network. Electronic address: elizabeth.demicco@sinaihealthsystem.ca, Cancer Genome Atlas Research Network
(2017) Cell 171: 950-965.e28
MeSH Terms: Adult, Aged, Aged, 80 and over, Cluster Analysis, DNA Copy Number Variations, Epigenomics, Genome, Human, Genome-Wide Association Study, Humans, Middle Aged, Mutation, Sarcoma, Young Adult
Show Abstract · Added October 30, 2019
Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types.
Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
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Integrated molecular analysis reveals complex interactions between genomic and epigenomic alterations in esophageal adenocarcinomas.
Peng D, Guo Y, Chen H, Zhao S, Washington K, Hu T, Shyr Y, El-Rifai W
(2017) Sci Rep 7: 40729
MeSH Terms: Adenocarcinoma, Cell Line, Tumor, Comparative Genomic Hybridization, Computational Biology, DNA Copy Number Variations, DNA Methylation, Epigenesis, Genetic, Epigenomics, Esophageal Neoplasms, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Gene Ontology, Gene Regulatory Networks, Genomics, Humans
Show Abstract · Added April 18, 2017
The incidence of esophageal adenocarcinoma (EAC) is rapidly rising in the United States and Western countries. In this study, we carried out an integrative molecular analysis to identify interactions between genomic and epigenomic alterations in regulating gene expression networks in EAC. We detected significant alterations in DNA copy numbers (CN), gene expression levels, and DNA methylation profiles. The integrative analysis demonstrated that altered expression of 1,755 genes was associated with changes in CN or methylation. We found that expression alterations in 84 genes were associated with changes in both CN and methylation. These data suggest a strong interaction between genetic and epigenetic events to modulate gene expression in EAC. Of note, bioinformatics analysis detected a prominent K-RAS signature and predicted activation of several important transcription factor networks, including β-catenin, MYB, TWIST1, SOX7, GATA3 and GATA6. Notably, we detected hypomethylation and overexpression of several pro-inflammatory genes such as COX2, IL8 and IL23R, suggesting an important role of epigenetic regulation of these genes in the inflammatory cascade associated with EAC. In summary, this integrative analysis demonstrates a complex interaction between genetic and epigenetic mechanisms providing several novel insights for our understanding of molecular events in EAC.
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15 MeSH Terms
Epigenomic reprogramming during pancreatic cancer progression links anabolic glucose metabolism to distant metastasis.
McDonald OG, Li X, Saunders T, Tryggvadottir R, Mentch SJ, Warmoes MO, Word AE, Carrer A, Salz TH, Natsume S, Stauffer KM, Makohon-Moore A, Zhong Y, Wu H, Wellen KE, Locasale JW, Iacobuzio-Donahue CA, Feinberg AP
(2017) Nat Genet 49: 367-376
MeSH Terms: Carcinogenesis, Carcinoma, Pancreatic Ductal, Chromatin, Epigenesis, Genetic, Epigenomics, Gene Expression, Glucose, Heterochromatin, Histones, Humans, Neoplasm Metastasis, Pancreatic Neoplasms
Show Abstract · Added July 20, 2018
During the progression of pancreatic ductal adenocarcinoma (PDAC), heterogeneous subclonal populations emerge that drive primary tumor growth, regional spread, distant metastasis, and patient death. However, the genetics of metastases largely reflects that of the primary tumor in untreated patients, and PDAC driver mutations are shared by all subclones. This raises the possibility that an epigenetic process might operate during metastasis. Here we report large-scale reprogramming of chromatin modifications during the natural evolution of distant metastasis. Changes were targeted to thousands of large chromatin domains across the genome that collectively specified malignant traits, including euchromatin and large organized chromatin histone H3 lysine 9 (H3K9)-modified (LOCK) heterochromatin. Remarkably, distant metastases co-evolved a dependence on the oxidative branch of the pentose phosphate pathway (oxPPP), and oxPPP inhibition selectively reversed reprogrammed chromatin, malignant gene expression programs, and tumorigenesis. These findings suggest a model whereby linked metabolic-epigenetic programs are selected for enhanced tumorigenic fitness during the evolution of distant metastasis.
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Epigenetic and genetic variation in GATA5 is associated with gastric disease risk.
Sobota RS, Kodaman N, Mera R, Piazuelo MB, Bravo LE, Pazos A, Zabaleta J, Delgado AG, El-Rifai W, Morgan DR, Wilson KT, Correa P, Williams SM, Schneider BG
(2016) Hum Genet 135: 895-906
MeSH Terms: Adult, DNA Methylation, Epigenomics, Female, GATA5 Transcription Factor, Genetic Association Studies, Genotype, Helicobacter Infections, Helicobacter pylori, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, Risk Factors, Stomach Neoplasms
Show Abstract · Added May 28, 2016
Gastric cancer incidence varies considerably among populations, even those with comparable rates of Helicobacter pylori infection. To test the hypothesis that genetic variation plays a role in gastric disease, we assessed the relationship between genotypes and gastric histopathology in a Colombian study population, using a genotyping array of immune-related single nucleotide polymorphisms (SNPs). Two synonymous SNPs (rs6061243 and rs6587239) were associated with progression of premalignant gastric lesions in a dominant-effects model after correction for multiple comparisons (p = 2.63E-07 and p = 7.97E-07, respectively); effect sizes were β = -0.863 and β = -0.815, respectively, where β is an estimate of effect on histopathology scores, which ranged from 1 (normal) to 5 (dysplasia). In our replication cohort, a second Colombian population, both SNPs were associated with histopathology when additively modeled (β = -0.256, 95 % CI = -0.47, -0.039; and β = -0.239, 95 % CI = -0.45, -0.024), and rs6587239 was significantly associated in a dominant-effects model (β = -0.330, 95 % CI = -0.66, 0.00). Because promoter methylation of GATA5 has previously been associated with gastric cancer, we also tested for the association of methylation status with more advanced histopathology scores in our samples and found a significant relationship (p = 0.001). A multivariate regression model revealed that the effects of both the promoter methylation and the exonic SNPs in GATA5 were independent. A SNP-by-methylation interaction term was also significant. This interaction between GATA5 variants and GATA5 promoter methylation indicates that the association of either factor with gastric disease progression is modified by the other.
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Blood Epigenetic Age may Predict Cancer Incidence and Mortality.
Zheng Y, Joyce BT, Colicino E, Liu L, Zhang W, Dai Q, Shrubsole MJ, Kibbe WA, Gao T, Zhang Z, Jafari N, Vokonas P, Schwartz J, Baccarelli AA, Hou L
(2016) EBioMedicine 5: 68-73
MeSH Terms: Aged, Aging, DNA Methylation, Epigenomics, Female, Humans, Male, Middle Aged, Neoplasms
Show Abstract · Added May 2, 2016
Biological measures of aging are important for understanding the health of an aging population, with epigenetics particularly promising. Previous studies found that tumor tissue is epigenetically older than its donors are chronologically. We examined whether blood Δage (the discrepancy between epigenetic and chronological ages) can predict cancer incidence or mortality, thus assessing its potential as a cancer biomarker. In a prospective cohort, Δage and its rate of change over time were calculated in 834 blood leukocyte samples collected from 442 participants free of cancer at blood draw. About 3-5 years before cancer onset or death, Δage was associated with cancer risks in a dose-responsive manner (P = 0.02) and a one-year increase in Δage was associated with cancer incidence (HR: 1.06, 95% CI: 1.02-1.10) and mortality (HR: 1.17, 95% CI: 1.07-1.28). Participants with smaller Δage and decelerated epigenetic aging over time had the lowest risks of cancer incidence (P = 0.003) and mortality (P = 0.02). Δage was associated with cancer incidence in a 'J-shaped' manner for subjects examined pre-2003, and with cancer mortality in a time-varying manner. We conclude that blood epigenetic age may mirror epigenetic abnormalities related to cancer development, potentially serving as a minimally invasive biomarker for cancer early detection.
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In-depth genomic data analyses revealed complex transcriptional and epigenetic dysregulations of BRAFV600E in melanoma.
Guo X, Xu Y, Zhao Z
(2015) Mol Cancer 14: 60
MeSH Terms: Cell Transformation, Neoplastic, DNA Methylation, Down-Regulation, Epigenesis, Genetic, Epigenomics, Gene Expression Regulation, Neoplastic, Genomics, Humans, Melanoma, Microphthalmia-Associated Transcription Factor, Proto-Oncogene Proteins B-raf, Skin Neoplasms, Transcription, Genetic, Transcriptome, Transforming Growth Factor beta1, Up-Regulation
Show Abstract · Added April 6, 2017
BACKGROUND - The recurrent BRAF driver mutation V600E (BRAF (V600E)) is currently one of the most clinically relevant mutations in melanoma. However, the genome-wide transcriptional and epigenetic dysregulations induced by BRAF (V600E) are still unclear. The investigation of this driver mutation's functional consequences is critical to the understanding of tumorigenesis and the development of therapeutic strategies.
METHODS AND RESULTS - We performed an integrative analysis of transcriptomic and epigenomic changes disturbed by BRAF (V600E) by comparing the gene expression and methylation profiles of 34 primary cutaneous melanoma tumors harboring BRAF (V600E) with those of 27 BRAF (WT) samples available from The Cancer Genome Atlas (TCGA). A total of 711 significantly differentially expressed genes were identified as putative BRAF (V600E) target genes. Functional enrichment analyses revealed the transcription factor MITF (p < 3.6 × 10(-16)) and growth factor TGFB1 (p < 3.1 × 10(-9)) were the most significantly enriched up-regulators, with MITF being significantly up-regulated, whereas TGFB1 was significantly down-regulated in BRAF (V600E), suggesting that they may mediate tumorigenesis driven by BRAF (V600E). Further investigation using the MITF ChIP-Seq data confirmed that BRAF (V600E) led to an overall increased level of gene expression for the MITF targets. Furthermore, DNA methylation analysis revealed a global DNA methylation loss in BRAF (V600E) relative to BRAF (WT). This might be due to BRAF dysregulation of DNMT3A, which was identified as a potential target with significant down-regulation in BRAF (V600E). Finally, we demonstrated that BRAF (V600E) targets may play essential functional roles in cell growth and proliferation, measured by their effects on melanoma tumor growth using a short hairpin RNA silencing experimental dataset.
CONCLUSIONS - Our integrative analysis identified a set of BRAF (V600E) target genes. Further analyses suggested a complex mechanism driven by mutation BRAF (V600E) on melanoma tumorigenesis that disturbs specific cancer-related genes, pathways, and methylation modifications.
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Extrapolating histone marks across developmental stages, tissues, and species: an enhancer prediction case study.
Capra JA
(2015) BMC Genomics 16: 104
MeSH Terms: Acetylation, Animals, Cell Differentiation, Embryonic Development, Embryonic Stem Cells, Enhancer Elements, Genetic, Epigenomics, Gene Expression Regulation, Developmental, Heart, Histone Code, Histones, Humans, Machine Learning, Mice
Show Abstract · Added February 22, 2016
BACKGROUND - Dynamic activation and inactivation of gene regulatory DNA produce the expression changes that drive the differentiation of cellular lineages. Identifying regulatory regions active during developmental transitions is necessary to understand how the genome specifies complex developmental programs and how these processes are disrupted in disease. Gene regulatory dynamics are mediated by many factors, including the binding of transcription factors (TFs) and the methylation and acetylation of DNA and histones. Genome-wide maps of TF binding and DNA and histone modifications have been generated for many cellular contexts; however, given the diversity and complexity of animal development, these data cover only a small fraction of the cellular and developmental contexts of interest. Thus, there is a need for methods that use existing epigenetic and functional genomics data to analyze the thousands of contexts that remain uncharacterized.
RESULTS - To investigate the utility of histone modification data in the analysis of cellular contexts without such data, I evaluated how well genome-wide H3K27ac and H3K4me1 data collected in different developmental stages, tissues, and species were able to predict experimentally validated heart enhancers active at embryonic day 11.5 (E11.5) in mouse. Using a machine-learning approach to integrate the data from different contexts, I found that E11.5 heart enhancers can often be predicted accurately from data from other contexts, and I quantified the contribution of each data source to the predictions. The utility of each dataset correlated with nearness in developmental time and tissue to the target context: data from late developmental stages and adult heart tissues were most informative for predicting E11.5 enhancers, while marks from stem cells and early developmental stages were less informative. Predictions based on data collected in non-heart tissues and in human hearts were better than random, but worse than using data from mouse hearts.
CONCLUSIONS - The ability of these algorithms to accurately predict developmental enhancers based on data from related, but distinct, cellular contexts suggests that combining computational models with epigenetic data sampled from relevant contexts may be sufficient to enable functional characterization of many cellular contexts of interest.
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14 MeSH Terms
Intraindividual variation and short-term temporal trend in DNA methylation of human blood.
Shvetsov YB, Song MA, Cai Q, Tiirikainen M, Xiang YB, Shu XO, Yu H
(2015) Cancer Epidemiol Biomarkers Prev 24: 490-7
MeSH Terms: Adult, Aged, Blood Chemical Analysis, Cohort Studies, CpG Islands, DNA, DNA Methylation, Epigenomics, Female, Genome, Human, Humans, Middle Aged, Prospective Studies
Show Abstract · Added April 3, 2018
BACKGROUND - Between- and within-person variation in DNA methylation levels are important parameters to be considered in epigenome-wide association studies. Temporal change is one source of within-person variation in DNA methylation that has been linked to aging and disease.
METHODS - We analyzed CpG-site-specific intraindividual variation and short-term temporal trend in leukocyte DNA methylation among 24 healthy Chinese women, with blood samples drawn at study entry and after 9 months. Illumina HumanMethylation450 BeadChip was used to measure methylation. Intraclass correlation coefficients (ICC) and trend estimates were summarized by genomic location and probe type.
RESULTS - The median ICC was 0.36 across nonsex chromosomes and 0.80 on the X chromosome. There was little difference in ICC profiles by genomic region and probe type. Among CpG loci with high variability between participants, more than 99% had ICC > 0.8. Statistically significant trend was observed in 10.9% CpG loci before adjustment for cell-type composition and in 3.4% loci after adjustment.
CONCLUSIONS - For CpG loci differentially methylated across subjects, methylation levels can be reliably assessed with one blood sample. More samples per subject are needed for low-variability and unmethylated loci. Temporal changes are largely driven by changes in cell-type composition of blood samples, but temporal trend unrelated to cell types is detected in a small percentage of CpG sites.
IMPACT - This study shows that one measurement can reliably assess methylation of differentially methylated CpG loci. Cancer Epidemiol Biomarkers Prev; 24(3); 490-7. ©2014 AACR.
©2014 American Association for Cancer Research.
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Epigenome-wide association study of fasting measures of glucose, insulin, and HOMA-IR in the Genetics of Lipid Lowering Drugs and Diet Network study.
Hidalgo B, Irvin MR, Sha J, Zhi D, Aslibekyan S, Absher D, Tiwari HK, Kabagambe EK, Ordovas JM, Arnett DK
(2014) Diabetes 63: 801-7
MeSH Terms: Blood Glucose, Diabetes Mellitus, Type 2, Epigenesis, Genetic, Epigenomics, Gene Expression Regulation, Homeostasis, Humans, Insulin, Insulin Resistance, Reproducibility of Results, Risk Factors, Transcriptome
Show Abstract · Added March 7, 2014
Known genetic susceptibility loci for type 2 diabetes (T2D) explain only a small proportion of heritable T2D risk. We hypothesize that DNA methylation patterns may contribute to variation in diabetes-related risk factors, and this epigenetic variation across the genome can contribute to the missing heritability in T2D and related metabolic traits. We conducted an epigenome-wide association study for fasting glucose, insulin, and homeostasis model assessment of insulin resistance (HOMA-IR) among 837 nondiabetic participants in the Genetics of Lipid Lowering Drugs and Diet Network study, divided into discovery (N = 544) and replication (N = 293) stages. Cytosine guanine dinucleotide (CpG) methylation at ∼470,000 CpG sites was assayed in CD4(+) T cells using the Illumina Infinium HumanMethylation 450 Beadchip. We fit a mixed model with the methylation status of each CpG as the dependent variable, adjusting for age, sex, study site, and T-cell purity as fixed-effects and family structure as a random-effect. A Bonferroni corrected P value of 1.1 × 10(-7) was considered significant in the discovery stage. Significant associations were tested in the replication stage using identical models. Methylation of a CpG site in ABCG1 on chromosome 21 was significantly associated with insulin (P = 1.83 × 10(-7)) and HOMA-IR (P = 1.60 × 10(-9)). Another site in the same gene was significant for HOMA-IR and of borderline significance for insulin (P = 1.29 × 10(-7) and P = 3.36 × 10(-6), respectively). Associations with the top two signals replicated for insulin and HOMA-IR (P = 5.75 × 10(-3) and P = 3.35 × 10(-2), respectively). Our findings suggest that methylation of a CpG site within ABCG1 is associated with fasting insulin and merits further evaluation as a novel disease risk marker.
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Genetics and epigenetics in perioperative medicine.
Bain CR, Shaw AD
(2012) Curr Opin Crit Care 18: 548-54
MeSH Terms: Epigenomics, Gene Expression, Genetic Variation, Genome-Wide Association Study, Humans, Perioperative Care, Pharmacogenetics, Risk Factors
Show Abstract · Added October 20, 2015
PURPOSE OF REVIEW - To summarize is to review recent progress in 'genomic' science and how this may be applied to the perioperative environment. Although investigations that relate genetic variation to perioperative outcomes continue, it is increasingly apparent that epigenetic mechanisms may contribute to much of the observed variation in complex outcomes not otherwise explained by differences in genetic sequence.
RECENT FINDINGS - Examples of recent findings relating to the role of epigenetic modifications in complex disease and outcomes are derived from research into type 1 diabetes, pain, and the hypoxic response. These studies provide models for future cohort study design, potential perioperative drug targets, and hypothesis development. Genetic and epigenetic factors combine to alter both gene expression and drug responses at both pharmacokinetic and pharmacodynamic levels. These factors impact on the efficacy and safety of multiple drug classes used in perioperative medicine.
SUMMARY - Enhancing our understanding of the way in which patients as genomic organisms interact with the perioperative environment requires a more sophisticated appreciation of the factors governing gene expression than has been the case to date. Epigenetic mechanisms are sure to play a pivotal role in what is essentially an acquired phenotype.
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8 MeSH Terms