Significant associations between driver gene mutations and DNA methylation alterations across many cancer types

AbstractRecent evidence shows that mutations in several driver genes can cause aberrant methylation patterns, a hallmark of cancer. In light of these findings, we hypothesized that the landscapes of tumor genomes and epigenomes are tightly interconnected. We measured this relationship using principal component analyses and methylation-mutation associations applied at the nucleotide level and with respect to genome-wide trends. We found a few mutated driver genes were associated with genome-wide patterns of aberrant hypomethylation or CpG island hypermethylation in specific cancer types. We identified associations between 737 mutated driver genes and site-specific methylation changes. Moreover, using these mutation-methylation associations, we were able to distinguish between two uterine and two thyroid cancer subtypes. The driver gene mutation-associated methylation differences between the thyroid cancer subtypes were linked to differential gene expression in JAK-STAT signaling, NADPH oxidation, and other cancer-related pathways. These results establish that driver-gene mutations are associated with methylation alterations capable of shaping regulatory network functions. In addition, the methodology presented here can be used to subdivide tumors into more homogeneous subsets corresponding to their underlying molecular characteristics, which could improve treatment efficacy.Author summaryMutations that alter the function of driver genes by changing DNA nucleotides have been recognized as a key player in cancer progression. Recent evidence showed that DNA methylation, a molecular signature that is used for controlling gene expression and that consists of cytosine residues with attached methyl groups in the context of CG dinucleotides, is also highly dysregulated in cancer and contributes to carcinogenesis. However, whether those methylation alterations correspond to mutated driver genes in cancer remains unclear. In this study, we analyzed 4,302 tumors from 18 cancer types and demonstrated that driver gene mutations are inherently connected with the aberrant DNA methylation landscape in cancer. We showed that those driver gene-associated methylation patterns can classify heterogeneous tumors in a cancer type into homogeneous subtypes and have the potential to influence the genes that contribute to tumor growth. This finding could help us to better understand the fundamental connection between driver gene mutations and DNA methylation alterations in cancer and to further improve the cancer treatment.

Download Full-text

Abstract 40: Disturbed Flow Alters Genomewide DNA Methylation Patterns, Regulating Endothelial Gene Expression and Atherosclerosis

Arteriosclerosis Thrombosis and Vascular Biology ◽

10.1161/atvb.34.suppl_1.40 ◽

2014 ◽

Vol 34 (suppl_1) ◽

Author(s):

Jessilyn Dunn ◽

Haiwei Qiu ◽

Soyeon Kim ◽

Daudi Jjingo ◽

Ryan Hoffman ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Dna Methyltransferase ◽

Methylation Status ◽

Western Diet ◽

Dependent Manner ◽

Gene Promoters ◽

Genome Wide ◽

Methylation Patterns ◽

Endothelial Gene Expression

Atherosclerosis preferentially occurs in arterial regions of disturbed blood flow (d-flow), which alters gene expression, endothelial function, and atherosclerosis. Here, we show that d-flow regulates genome-wide DNA methylation patterns in a DNA methyltransferase (DNMT)-dependent manner. We found that d-flow induced expression of DNMT1, but not DNMT3a or DNMT3b, in mouse arterial endothelium in vivo and in cultured endothelial cells by oscillatory shear (OS) compared to unidirectional laminar shear in vitro. The DNMT inhibitor 5-Aza-2’deoxycytidine (5Aza) or DNMT1 siRNA significantly reduced OS-induced endothelial inflammation. Moreover, 5Aza reduced lesion formation in two atherosclerosis models using ApoE-/- mice (western diet for 3 months and the partial carotid ligation model with western diet for 3 weeks). To identify the 5Aza mechanisms, we conducted two genome-wide studies: reduced representation bisulfite sequencing (RRBS) and transcript microarray using endothelial-enriched gDNA and RNA, respectively, obtained from the partially-ligated left common carotid artery (LCA exposed to d-flow) and the right contralateral control (RCA exposed to s-flow) of mice treated with 5Aza or vehicle. D-flow induced DNA hypermethylation in 421 gene promoters, which was significantly prevented by 5Aza in 335 genes. Systems biological analyses using the RRBS and the transcriptome data revealed 11 mechanosensitive genes whose promoters were hypermethylated by d-flow but rescued by 5Aza treatment. Of those, five genes contain hypermethylated cAMP-response-elements in their promoters, including the transcription factors HoxA5 and Klf3. Their methylation status could serve as a mechanosensitive master switch in endothelial gene expression. Our results demonstrate that d-flow controls epigenomic DNA methylation patterns in a DNMT-dependent manner, which in turn alters endothelial gene expression and induces atherosclerosis.

Download Full-text

Changes in DNA Methylation and Gene Expression of Insulin and Obesity-Related Gene PIK3R1 after Roux-en-Y Gastric Bypass

International Journal of Molecular Sciences ◽

10.3390/ijms21124476 ◽

2020 ◽

Vol 21 (12) ◽

pp. 4476

Author(s):

Marcela A S Pinhel ◽

Natália Y Noronha ◽

Carolina F Nicoletti ◽

Vanessa AB Pereira ◽

Bruno AP de Oliveira ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Weight Loss ◽

Gastric Bypass ◽

Related Gene ◽

Cpg Sites ◽

Genome Wide ◽

Genetically Determined ◽

Methylation Patterns ◽

Weight Loss Interventions

Weight regulation and the magnitude of weight loss after a Roux-en-Y gastric bypass (RYGB) can be genetically determined. DNA methylation patterns and the expression of some genes can be altered after weight loss interventions, including RYGB. The present study aimed to evaluate how the gene expression and DNA methylation of PIK3R1, an obesity and insulin-related gene, change after RYGB. Blood samples were obtained from 13 women (35.9 ± 9.2 years) with severe obesity before and six months after surgical procedure. Whole blood transcriptome and epigenomic patterns were assessed by microarray-based, genome-wide technologies. A total of 1966 differentially expressed genes were identified in the pre- and postoperative periods of RYGB. From these, we observed that genes involved in obesity and insulin pathways were upregulated after surgery. Then, the PIK3R1 gene was selected for further RT-qPCR analysis and cytosine-guanine nucleotide (CpG) sites methylation evaluation. We observed that the PI3KR1 gene was upregulated, and six DNA methylation CpG sites were differently methylated after bariatric surgery. In conclusion, we found that RYGB upregulates genes involved in obesity and insulin pathways.

Download Full-text

Significant associations between driver gene mutations and DNA methylation alterations across many cancer types

PLoS Computational Biology ◽

10.1371/journal.pcbi.1005840 ◽

2017 ◽

Vol 13 (11) ◽

pp. e1005840 ◽

Cited By ~ 13

Author(s):

Yun-Ching Chen ◽

Valer Gotea ◽

Gennady Margolin ◽

Laura Elnitski

Keyword(s):

Dna Methylation ◽

Gene Mutations ◽

Driver Gene ◽

Cancer Types

Download Full-text

A Genome-Wide Study of DNA Methylation Patterns and Gene Expression Levels in Multiple Human and Chimpanzee Tissues

PLoS Genetics ◽

10.1371/journal.pgen.1001316 ◽

2011 ◽

Vol 7 (2) ◽

pp. e1001316 ◽

Cited By ~ 142

Author(s):

Athma A. Pai ◽

Jordana T. Bell ◽

John C. Marioni ◽

Jonathan K. Pritchard ◽

Yoav Gilad

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Expression Levels ◽

Genome Wide ◽

A Genome ◽

Methylation Patterns ◽

Genome Wide Study ◽

Gene Expression Levels

Download Full-text

Genome-Wide DNA Methylation Analysis Shows Enrichment of Differential Methylation in “Open Seas” and Enhancers and Reveals Hypomethylation in DNMT3A Mutated Cytogenetically Normal AML (CN-AML)

Blood ◽

10.1182/blood.v120.21.653.653 ◽

2012 ◽

Vol 120 (21) ◽

pp. 653-653 ◽

Cited By ~ 2

Author(s):

Ying Qu ◽

Andreas Lennartsson ◽

Verena I. Gaidzik ◽

Stefan Deneberg ◽

Sofia Bengtzén ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Cpg Island ◽

Cpg Islands ◽

Differential Methylation ◽

Methylation Analysis ◽

Cpg Sites ◽

Genome Wide ◽

Genomic Regions ◽

Methylation Patterns

Abstract Abstract 653 DNA methylation is involved in multiple biologic processes including normal cell differentiation and tumorigenesis. In AML, methylation patterns have been shown to differ significantly from normal hematopoietic cells. Most studies of DNA methylation in AML have previously focused on CpG islands within the promoter of genes, representing only a very small proportion of the DNA methylome. In this study, we performed genome-wide methylation analysis of 62 AML patients with CN-AML and CD34 positive cells from healthy controls by Illumina HumanMethylation450K Array covering 450.000 CpG sites in CpG islands as well as genomic regions far from CpG islands. Differentially methylated CpG sites (DMS) between CN-AML and normal hematopoietic cells were calculated and the most significant enrichment of DMS was found in regions more than 4kb from CpG Islands, in the so called open sea where hypomethylation was the dominant form of aberrant methylation. In contrast, CpG islands were not enriched for DMS and DMS in CpG islands were dominated by hypermethylation. DMS successively further away from CpG islands in CpG island shores (up to 2kb from CpG Island) and shelves (from 2kb to 4kb from Island) showed increasing degree of hypomethylation in AML cells. Among regions defined by their relation to gene structures, CpG dinucleotide located in theoretic enhancers were found to be the most enriched for DMS (Chi χ2<0.0001) with the majority of DMS showing decreased methylation compared to CD34 normal controls. To address the relation to gene expression, GEP (gene expression profiling) by microarray was carried out on 32 of the CN-AML patients. Totally, 339723 CpG sites covering 18879 genes were addressed on both platforms. CpG methylation in CpG islands showed the most pronounced anti-correlation (spearman ρ =-0.4145) with gene expression level, followed by CpG island shores (mean spearman rho for both sides' shore ρ=-0.2350). As transcription factors (TFs) have shown to be crucial for AML development, we especially studied differential methylation of an unbiased selection of 1638 TFs. The most enriched differential methylation between CN-AML and normal CD34 positive cells were found in TFs known to be involved in hematopoiesis and with Wilms tumor protein-1 (WT1), activator protein 1 (AP-1) and runt-related transcription factor 1 (RUNX1) being the most differentially methylated TFs. The differential methylation in WT 1 and RUNX1 was located in intragenic regions which were confirmed by pyro-sequencing. AML cases were characterized with respect to mutations in FLT3, NPM1, IDH1, IDH2 and DNMT3A. Correlation analysis between genome wide methylation patterns and mutational status showed statistically significant hypomethylation of CpG Island (p<0.0001) and to a lesser extent CpG island shores (p<0.001) and the presence of DNMT3A mutations. This links DNMT3A mutations for the first time to a hypomethylated phenotype. Further analyses correlating methylation patterns to other clinical data such as clinical outcome are ongoing. In conclusion, our study revealed that non-CpG island regions and in particular enhancers are the most aberrantly methylated genomic regions in AML and that WT 1 and RUNX1 are the most differentially methylated TFs. Furthermore, our data suggests a hypomethylated phenotype in DNMT3A mutated AML. Disclosures: No relevant conflicts of interest to declare.

Download Full-text

Genome-wide molecular effects of the neuropsychiatric 16p11 CNVs in an iPSC-to-iN neuronal model

10.1101/2020.02.09.940965 ◽

2020 ◽

Author(s):

Thomas R. Ward ◽

Xianglong Zhang ◽

Louis C. Leung ◽

Bo Zhou ◽

Kristin Muench ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Cell Model ◽

Copy Number Variants ◽

Induced Pluripotent Stem Cell ◽

Neuronal Model ◽

Autism Spectrum ◽

Genome Wide ◽

Induced Pluripotent ◽

Methylation Patterns

AbstractCopy number variants (CNVs), either deletions or duplications, at the 16p11.2 locus in the human genome are known to increase the risk for autism spectrum disorders (ASD), schizophrenia, and for several other developmental conditions. Here, we investigate the global effects on gene expression and DNA methylation using a 16p11.2 CNV patient-derived induced pluripotent stem cell (iPSC) to induced neuron (iN) cell model system. This approach revealed genome-wide and cell-type specific alterations to both gene expression and DNA methylation patterns and also yielded specific leads on genes potentially contributing to some of the known 16p11.2 patient phenotypes. PCSK9 is identified as a possible contributing factor to the symptoms seen in carriers of the 16p11.2 CNVs. The protocadherin (PCDH) gene family is found to have altered DNA methylation patterns in the CNV patient samples. The iPSC lines used for this study are available through a repository as a resource for research into the molecular etiology of the clinical phenotypes of 16p11.2 CNVs and into that of neuropsychiatric and neurodevelopmental disorders in general.

Download Full-text

Cancer-specific associations of driver genes with immunotherapy outcome

10.1101/2020.06.16.155895 ◽

2020 ◽

Cited By ~ 1

Author(s):

Tomi Jun ◽

Tao Qing ◽

Guanlan Dong ◽

Maxim Signaevski ◽

Julia F Hopkins ◽

...

Keyword(s):

Immune Checkpoint Inhibitor ◽

Gene Mutations ◽

Driver Gene ◽

Oncogenic Signaling ◽

Multiple Cancer ◽

Driver Genes ◽

Tumor Mutation Burden ◽

Mutation Burden ◽

Cancer Types ◽

Oncogenic Signaling Pathways

AbstractGenomic features such as microsatellite instability (MSI) and tumor mutation burden (TMB) are predictive of immune checkpoint inhibitor (ICI) response. However, they do not account for the functional effects of specific driver gene mutations, which may alter the immune microenvironment and influence immunotherapy outcomes. By analyzing a multi-cancer cohort of 1,525 ICI-treated patients, we identified 12 driver genes in 6 cancer types associated with treatment outcomes, including genes involved in oncogenic signaling pathways (NOTCH, WNT, FGFR) and chromatin remodeling. Mutations of PIK3CA, PBRM1, SMARCA4, and KMT2D were associated with worse outcomes across multiple cancer types. In comparison, genes showing cancer-specific associations—such as KEAP1, BRAF, and RNF43—harbored distinct variant types and variants, some of which were individually associated with outcomes. In colorectal cancer, a common RNF43 indel was a putative neoantigen associated with higher immune infiltration and favorable ICI outcomes. Finally, we showed that selected mutations were associated with PD-L1 status and could further stratify patient outcomes beyond MSI or TMB, highlighting their potential as biomarkers for immunotherapy.

Download Full-text

Diagnostic classification based on DNA methylation profiles using sequential machine learning approaches

10.1101/2021.04.12.439479 ◽

2021 ◽

Author(s):

M. W. Wojewodzic ◽

J. P. Lavender

Keyword(s):

Machine Learning ◽

Dna Methylation ◽

Machine Learning Algorithms ◽

Aberrant Methylation ◽

Learning Approaches ◽

Tissue Samples ◽

Non Invasive ◽

Genome Wide ◽

Cancer Types ◽

Methylation Patterns

AbstractAberrant methylation patterns in human DNA have great potential for the discovery of novel diagnostic and disease progression biomarkers. In this paper, we used machine learning algorithms to identify promising methylation sites for diagnosing cancerous tissue and to classify patients based on methylation values at these sites.We used genome-wide DNA methylation patterns from both cancerous and normal tissue samples, obtained from the Genomic Data Commons consortium and trialled our methods on three types of urological cancer. A decision tree was used to identify the methylation sites most useful for diagnosis.The identified locations were then used to train a neural network to classify samples as either cancerous or non-cancerous. Using this two-step approach we found strong indicative biomarker panels for each of the three cancer types.These methods could likely be translated to other cancers and improved by using non-invasive liquid methods such as blood instead of biopsy tissue.

Download Full-text

Pioneer transcription factors are associated with the modulation of DNA methylation patterns across cancers

10.1101/2021.05.10.443359 ◽

2021 ◽

Author(s):

Roza Berhanu Lemma ◽

Thomas Fleischer ◽

Emily Martinsen ◽

Vessela N Kristensen ◽

Ragnhild Eskeland ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Transcription Factors ◽

Gene Expression Regulation ◽

De Novo ◽

Aberrant Methylation ◽

Cancer Types ◽

Aberrant Dna Methylation ◽

Methylation Patterns ◽

Mcf 7

Methylation of cytosines on DNA is a prominent modification associated with gene expression regulation. Aberrant DNA methylation patterns have recurrently been linked to dysregulation of the regulatory program in cancer cells. To shed light on the underlying molecular mechanism driving this process, we hypothesized that aberrant methylation patterns could be controlled by the binding of specific transcription factors (TFs) across cancer types. By combining DNA methylation arrays and gene expression data with TF binding sites (TFBSs), we explored the interplay between TF binding and DNA methylation in 19 cancer cohorts. We performed emQTL (expression-methylation quantitative trait loci) analyses in each cohort and identified 13 TFs whose expression levels are correlated with local DNA methylation patterns around their binding site in at least 2 cancer types. The 13 TFs are mainly associated with local demethylation and are enriched for pioneer function, suggesting a specific role for these TFs in modulating chromatin structure and transcription in cancer patients. Furthermore, we confirmed that de novo methylation is precluded across cancers at CpGs lying in genomic regions enriched for TF-binding signatures associated with SP1, CTCF, NRF1, GABPA, KLF9, and/or YY1. The modulation of DNA methylation associated with TF binding was observed at cis-regulatory regions controlling immune- and cancer-associated pathways, corroborating that the emQTL signals were derived from both cancer and tumour-infiltrating cells. As a case example, we experimentally confirmed that FOXA1 knock-down is associated with higher methylation in regions bound by FOXA1 in breast cancer MCF-7 cells. Finally, we reported physical interactions between FOXA1 with TET1 and TET2 at physiological levels in MCF-7 cells, adding further support for FOXA1 attracting TET1 and TET2 to induce local demethylation in cancer.

Download Full-text

Proteogenomic view of cancer epigenetics: the impact of DNA methylation on the cancer proteome

10.1101/340760 ◽

2018 ◽

Author(s):

Majed Mohamed Magzoub ◽

Marcos Prunello ◽

Kevin Brennan ◽

Olivier Gevaert

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

High Throughput ◽

Tumor Stage ◽

Driver Genes ◽

Cancer Epigenetics ◽

Mesenchymal Transition ◽

Cancer Subtypes ◽

Proteomic Data ◽

The Impact

AbstractAberrant DNA methylation disrupts normal gene expression in cancer and broadly contributes to oncogenesis. We previously developed MethylMix, a model-based algorithmic approach to identify epigenetically regulated driver genes. MethylMix identifies genes where methylation likely executes a functional role by using transcriptomic data to select only methylation events that can be linked to changes in gene expression. However, given that proteins more closely link genotype to phenotype recent high-throughput proteomic data provides an opportunity to more accurately identify functionally relevant abnormal methylation events. Here we present ProteoMix, which refines nominations for epigenetic driver genes by leveraging quantitative high-throughput proteomic data to select only genes where DNA methylation is predictive of protein abundance. Applying our algorithm across three cancer cohorts we find that ProteoMix narrows candidate nominations, where the effect of DNA methylation is often buffered at the protein level. Next, we find that ProteoMix genes are enriched for biological processes involved in cancer including functions involved in epithelial and mesenchymal transition. ProteoMix results are also enriched for tumor markers which are predictive of clinical features like tumor stage and we find clustering on ProteoMix genes captures cancer subtypes.

Download Full-text