Hidden among the crowd: differential DNA methylation-expression correlations in cancer occur at important oncogenic pathways

Orgueira, Adrián Mosquera

doi:10.3389/fgene.2015.00163

Cited by 12 publications

(14 citation statements)

References 77 publications

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“…This finding was unexpected because SET accumulation is associated with loss of DNA methylation, which activates the expression of genes that are typically silenced by methylation [ 21 ]. A plausible explanation is that DNA methylation responds differently to the gene expression control machinery due to the interaction with other factors, including histone modifiers [ 22 ]. In addition, SET negatively regulates the expression of genes involved in cellular detoxification [ 23 ] and also participates as a subunit of the inhibitor of histone acetyltransferases complex that represses transcription [ 24 ], suggesting that the SET controls gene expression through a DNA methylation-independent mechanism.…”

Section: Resultsmentioning

confidence: 99%

SET oncoprotein accumulation regulates transcription through DNA demethylation and histone hypoacetylation

et al. 2017

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Epigenetic modifications are essential in the control of normal cellular processes and cancer development. DNA methylation and histone acetylation are major epigenetic modifications involved in gene transcription and abnormal events driving the oncogenic process. SET protein accumulates in many cancer types, including head and neck squamous cell carcinoma (HNSCC); SET is a member of the INHAT complex that inhibits gene transcription associating with histones and preventing their acetylation. We explored how SET protein accumulation impacts on the regulation of gene expression, focusing on DNA methylation and histone acetylation. DNA methylation profile of 24 tumour suppressors evidenced that SET accumulation decreased DNA methylation in association with loss of 5-methylcytidine, formation of 5-hydroxymethylcytosine and increased TET1 levels, indicating an active DNA demethylation mechanism. However, the expression of some suppressor genes was lowered in cells with high SET levels, suggesting that loss of methylation is not the main mechanism modulating gene expression. SET accumulation also downregulated the expression of 32 genes of a panel of 84 transcription factors, and SET directly interacted with chromatin at the promoter of the downregulated genes, decreasing histone acetylation. Gene expression analysis after cell treatment with 5-aza-2′-deoxycytidine (5-AZA) and Trichostatin A (TSA) revealed that histone acetylation reversed transcription repression promoted by SET. These results suggest a new function for SET in the regulation of chromatin dynamics. In addition, TSA diminished both SET protein levels and SET capability to bind to gene promoter, suggesting that administration of epigenetic modifier agents could be efficient to reverse SET phenotype in cancer.

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Section: Resultsmentioning

confidence: 99%

SET oncoprotein accumulation regulates transcription through DNA demethylation and histone hypoacetylation

et al. 2017

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“…Several previous studies have explored DNA methylation profiling (14,(19)(20)(21), and it would be ideal to compare our classification system with that proposed by Sahm et al by performing RNA-seq and methylation profiling on the same samples (14). (Methylation and expression may (45) or may not (46) correlate.) Unfortunately, the data in these papers are not publicly available, and thus could not be compared.…”

Section: Discussionmentioning

confidence: 99%

Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors

Patel

Wan

Al‐Ouran

et al. 2019

Preprint

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Meningiomas account for one-third of all primary brain tumors. Although typically benign, about 20% of meningiomas are aggressive, and despite the rigor of the current histopathological classification system, there remains considerable uncertainty in predicting tumor behavior. Here, we analyzed 160 tumors from all three WHO grades (I-III) using clinical, gene expression and sequencing data. Unsupervised clustering analysis identified three molecular types (A, B, and C) that reliably predicted recurrence. These groups did not directly correlate with the WHO grading system, which would classify more than half of the tumors in the most aggressive molecular type as benign. Transcriptional and biochemical analyses revealed that aggressive meningiomas involve loss of the repressor function of the DREAM complex, which results in cell cycle activation; only tumors in this category tend to recur after full resection. These findings should improve our ability to predict recurrence and develop targeted treatments for these clinically challenging tumors. Significance StatementMeningiomas are the most common primary brain tumors. Although most of these tumors are benign, one-fifth will recur despite apparently complete resection. Several studies have demonstrated that genomic approaches can yield important insights into the biology of these tumors. We performed RNA sequencing and whole-exome sequencing of 160 tumors from 140 patients, which identified three distinct groups of meningioma that correlate with recurrence better than the current WHO grading system. Our analysis also revealed that the most aggressive type was characterized by loss of the repressive DREAM complex. These findings should improve prognostication for patients and lead to viable therapeutic targets.

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“…to form an enzyme complex that targets ACLY, a protein often over-expressed in cancers, for degradation [55]. Pseudogene UBE2MP1 was found to have a significant expression-methylation-correlation difference between normal and cancerous breast tissue [53]. UBE2MP1 was also found to be amplified in gastric cancers with amplified copy number variations in the 16p11.2 region, a mutation found to be associated with shorter overall survival [57], and was predicted to be a driver of lung adenocarcinoma [56].…”

Section: Novel Findings By Tigarmentioning

confidence: 95%

“…TIGAR identified 3 novel independent TWAS risk genes (KLHL25, UBE2MP1, and FRG1EP ) for breast cancer. Gene KLHL25 has known biological functions involved in carcinogenesis, while genes UBE2MP1 and FRG1EP are near such a gene [53][54][55][56][57].…”

Section: Novel Findings By Tigarmentioning

confidence: 99%

TIGAR-V2: Efficient TWAS Tool with Nonparametric Bayesian eQTL Weights of 49 Tissue Types from GTEx V8

Parrish

Gibson

Epstein

et al. 2021

Preprint

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Standard Transcriptome-Wide Association Study (TWAS) methods first train gene expression prediction models using reference transcriptomic data, and then test the association between the predicted genetically regulated gene expression and phenotype of interest. Most existing TWAS tools require cumbersome preparation of genotype input files and extra coding to enable parallel computation. To improve the efficiency of TWAS tools, we develop TIGAR-V2, which directly reads VCF files, enables parallel computation, and reduces up to 90% computation cost compared to the original version. TIGAR-V2 can train gene expression imputation models using either nonparametric Bayesian Dirichlet Process Regression (DPR) or Elastic-Net (as used by PrediXcan), perform TWAS using either individual-level or summary-level GWAS data, and implements both burden and variance-component test statistics for inference. We trained gene expression prediction models by DPR for 49 tissues using GTEx V8 by TIGAR-V2 and illustrated the usefulness of these nonparametric Bayesian DPR eQTL weights through TWAS of breast and ovarian cancer utilizing public GWAS summary statistics. We identified 88 and 37 risk genes respectively for breast and ovarian cancer, most of which are either known or near previously identified GWAS (~95%) or TWAS (~40%) risk genes of the corresponding phenotype and three novel independent TWAS risk genes with known functions in carcinogenesis. These findings suggest that TWAS can provide biological insight into the transcriptional regulation of complex diseases. TIGAR-V2 tool, trained Bayesian cis-eQTL weights, and LD information from GTEX V8 are publicly available, providing a useful resource for mapping risk genes of complex diseases.

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Hidden among the crowd: differential DNA methylation-expression correlations in cancer occur at important oncogenic pathways

Cited by 12 publications

References 77 publications

SET oncoprotein accumulation regulates transcription through DNA demethylation and histone hypoacetylation

SET oncoprotein accumulation regulates transcription through DNA demethylation and histone hypoacetylation

Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors

TIGAR-V2: Efficient TWAS Tool with Nonparametric Bayesian eQTL Weights of 49 Tissue Types from GTEx V8

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