Epigenome-wide DNA methylation landscape of melanoma progression to brain metastasis reveals aberrations on homeobox D cluster associated with prognosis

Marzese, Diego M.; Scolyer, Richard A.; Huynh, Jamie L.; Huang, Sharon K.; Hirose, Hajime; Chong, Kelly K.; Kiyohara, Eiji; Wang, Jinhua; Kawas, Neal P.; Donovan, Nicholas; Hata, Keisuke; Wilmott, James S.; Murali, Rajmohan; Buckland, Michael E.; Shivalingam, Brindha; Thompson, John F.; Morton, Donald L.; Kelly, Daniel F.; Hoon, Dave S.B.

doi:10.1093/hmg/ddt420

Cited by 103 publications

(149 citation statements)

References 59 publications

(67 reference statements)

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“…Our analysis also identified hypermethylation in the HOXD12, TNFRSF10C, FGFR2 and TERT genes. These results confirm recent 450 K array methylation analysis (the same platform as used in TCGA methylation assays) that reported high levels of promoter methylation in these genes in melanoma [32,33].…”

Section: Dna Methylation Landscape Of Frequently Deregulated Genes Insupporting

confidence: 89%

Scan_Tcga Tools for Integrated Epigenomic and Transcriptomic Analysis of Tumor Subgroups

et al. 2016

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Aim:The Cancer Genome Atlas contains multiple levels of genomic data (mutation, gene expression, DNA methylation, copy number variation) for 33 cancer types for almost 11,000 patients. However, a dearth of appropriate software tools makes it difficult for bench scientists to use these data effectively. Materials & methods: Here, we present a suite of flexible, fast and command line-based scripts that will allow retrieval and analysis of DNA methylation (tool: scan_tcga_methylation.awk), mRNA (tool: scan_tcga_mRNA.awk) and miRNA expression (tool: scan_tcga_miRNAs.awk) from cancer genome atlas network level 3 data. Results: We demonstrate the utility of these tools by analyzing DNA methylation and mRNA expression signatures of 60 frequently deregulated cancer genes and also of 30 miRNAs in primary (n = 102) and metastatic melanoma patients (n = 367). Conclusion: Our analysis illustrates the validity of the scan_tcga tools and reveals the epigenomic signatures and importance of identifying smaller patient subgroups with distinct molecular profiles.

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Section: Dna Methylation Landscape Of Frequently Deregulated Genes Insupporting

confidence: 89%

Scan_Tcga Tools for Integrated Epigenomic and Transcriptomic Analysis of Tumor Subgroups

et al. 2016

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“…DNase I hypersensitivity data from melanoma cells were extracted according to a method described previously (Marzese et al 2014) (GEO accession number GSM1008599). DNase I hypersensitive sites were defined as open chromatin regions.…”

Section: Characterization Of Open and Closed Chromatinmentioning

confidence: 99%

A widespread role of the motif environment in transcription factor binding across diverse protein families

et al. 2015

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Transcriptional regulation requires the binding of transcription factors (TFs) to short sequence-specific DNA motifs, usually located at the gene regulatory regions. Interestingly, based on a vast amount of data accumulated from genomic assays, it has been shown that only a small fraction of all potential binding sites containing the consensus motif of a given TF actually bind the protein. Recent in vitro binding assays, which exclude the effects of the cellular environment, also demonstrate selective TF binding. An intriguing conjecture is that the surroundings of cognate binding sites have unique characteristics that distinguish them from other sequences containing a similar motif that are not bound by the TF. To test this hypothesis, we conducted a comprehensive analysis of the sequence and DNA shape features surrounding the core-binding sites of 239 and 56 TFs extracted from in vitro HT-SELEX binding assays and in vivo ChIP-seq data, respectively. Comparing the nucleotide content of the regions around the TF-bound sites to the counterpart unbound regions containing the same consensus motifs revealed significant differences that extend far beyond the core-binding site. Specifically, the environment of the bound motifs demonstrated unique sequence compositions, DNA shape features, and overall high similarity to the core-binding motif. Notably, the regions around the binding sites of TFs that belong to the same TF families exhibited similar features, with high agreement between the in vitro and in vivo data sets. We propose that these unique features assist in guiding TFs to their cognate binding sites.

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“…Most studies of DNA methylation changes in cancers have focused on promoter regions, since hypermethylation of promoters is a key mechanism for gene silencing (Esteller 2007). Less attention has been given to aberrant DNA methylation in other regions of the genome, such as enhancers Marzese et al 2014;Ziller et al 2013;Brocks et al 2014), and to its influence on gene expression in cancer.…”

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confidence: 99%

Enhancer methylation dynamics contribute to cancer plasticity and patient mortality

et al. 2016

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During development, enhancers play pivotal roles in regulating gene expression programs; however, their involvement in cancer progression has not been fully characterized. We performed an integrative analysis of DNA methylation, RNA-seq, and small RNA-seq profiles from thousands of patients, including 25 diverse primary malignances and seven body sites of metastatic melanoma. We found that enhancers are consistently the most differentially methylated regions (DMR) as cancer progresses from normal to primary tumors and then to metastases, compared to other genomic features. Remarkably, identification of enhancer DMRs (eDMRs) enabled classification of primary tumors according to physiological organ systems, and in metastasis eDMRs are the most correlated with patient outcome. To further understand the eDMR role in cancer progression, we developed a model to predict genes and microRNAs that are regulated by enhancer and not promotor methylation, which shows high accuracy with chromatin architecture methods and was experimentally validated. Interestingly, among all metastatic melanoma eDMRs, the most correlated with patient survival were eDMRs that "switched" their methylation patterns back and forth between normal, primary, and metastases and target cancer drivers, e.g., KIT. We further demonstrated that eDMR target genes were modulated in melanoma by the bone metastasis microenvironment, suggesting that eDMRs respond to microenvironmental cues in metastatic niches. Our findings that aberrant methylation in cancer cells mostly affects enhancers, which contribute to tumor progression and cancer cell plasticity, will facilitate development of epigenetic anticancer approaches.

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Epigenome-wide DNA methylation landscape of melanoma progression to brain metastasis reveals aberrations on homeobox D cluster associated with prognosis

Cited by 103 publications

References 59 publications

Scan_Tcga Tools for Integrated Epigenomic and Transcriptomic Analysis of Tumor Subgroups

Scan_Tcga Tools for Integrated Epigenomic and Transcriptomic Analysis of Tumor Subgroups

A widespread role of the motif environment in transcription factor binding across diverse protein families

Enhancer methylation dynamics contribute to cancer plasticity and patient mortality

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