Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

DNA methylation biomarkers for non-invasive detection of triple negative breast cancer using liquid biopsy

ABSTRACT: Non-invasive detection of aberrant DNA methylation could provide invaluable biomarkers for earlier detection of triple negative breast cancer (TNBC) which could help clinicians for easier and more efficient treatment options. We evaluated genome-wide DNA methylation data derived from TNBC and normal breast tissues, peripheral blood of TNBC cases and controls, and reference samples of sorted blood and mammary cells. Differentially methylated regions (DMRs) between TNBC and normal breast tissues were stringently selected, verified, and externally validated. A machine learning algorithm was applied to select the top DMRs, which then were evaluated on plasma-derived circulating cell-free DNA (cfDNA) samples of TNBC patients and healthy controls. We identified 23 DMRs accounting for the methylation profile of blood cells and reference mammary cells and then selected six top DMRs for cfDNA analysis. We quantified un-/methylated copies of these DMRs by droplet digital PCR analysis in a plasma test set from TNBC patients and healthy controls and confirmed our findings obtained on tissues. Differential cfDNA methylation was confirmed in an independent validation set of plasma samples. A methylation score combining signatures of the top three DMRs overlapping with the SPAG6, LINC10606, and TBCD/ZNF750 genes had the best capability to discriminate TNBC patients from controls (AUC=0.74 in test set and AUC=0.77 in validation set). Our findings demonstrate the usefulness of cfDNA-based methylation signatures as non-invasive liquid biopsy markers for diagnosis of TNBC.

ORGANISM(S): Homo sapiens

PROVIDER: GSE207998 | GEO | 2022/11/23

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Genome-wide plasma cell-free DNA methylation profiling in lung cancer patients using MeDIP-seq

Project description:As a non-invasive blood testing, the detection of cell-free DNA (cfDNA) methylation in plasma is raising increasing interest due to its diagnostic and biology applications. Although extensively used in cfDNA methylation analysis, bisulfite sequencing is less cost-effective. Through enriching methylated cfDNA fragments with MeDIP followed by deep sequencing, we aimed to characterize cfDNA methylome in cancer patients. In this study, we investigated the cfDNA methylation patterns in lung cancer patients by MeDIP-seq. MEDIPS package was used for the identification of differentially methylated regions (DMRs) between patients and normal ones. Overall, we identified 330 differentially methylated regions (DMRs) in gene promoter regions, 33 hypermethylation and 297 hypomethylation respectively, by comparing lung cancer patients and healthy individuals as controls. The 33 hypermethylation regions represent 32 genes. Some of the genes had been previously reported to be associated with lung cancers, such as GAS7, AQP10, HLF, CHRNA9 and HOPX. Taken together, our study provided an alternative method of cfDNA methylation analysis in lung cancer patients with potential clinical applications.

2019-03-31 | E-MTAB-7163 | biostudies-arrayexpress

Cell-free DNA 5-hydroxymethylcytosine as a marker for common cancer detection

Project description:We used a highly sensitive nano-5hmC-Seal method and profiled the genome-wide distribution of 5-hydroxymethylcytosine (5hmC) in plasma cell-free DNA (cfDNA) from 384 patients with bladder, breast, colorectal, kidney, lung, or prostate cancer and 221 controls. We used machine learning and developed plasma cfDNA 5hmC signatures that are highly sensitive for cancer detection and cancer origin determination. We also identified genes and signaling pathways with aberrant DNA hydroxymethylation in six cancers.

2022-09-23 | GSE202988 | GEO

A genome-wide cell-free DNA methylation analysis identifies an episignature associated with metastatic luminal B breast cancer.

Project description:Breast cancers of the luminal B subtype are frequent tumors with high proliferation and poor prognosis. Epigenetic alterations have been found in breast tumors and in biological fluids. We aimed to profile the cell-free DNA (cfDNA) methylome of metastatic luminal B breast cancer (LBBC) patients using an epigenomic approach to discover potential noninvasive biomarkers. Plasma cfDNA was analyzed using the Infinium MethylationEpic array (EPIC array) in a cohort of 14 women, including metastatic LBBC patients and healthy controls.

2022-11-16 | GSE214344 | GEO

Human cholangiocarcinoma (CC), ECC (extrahepatic CC) and ICC (intrahepatic CC) cases versus control

Project description:CpG island methylation profiling of human cholangiocarcinoma, ECC and ICC, cases compared to matched normal controls or to pools of corresponding normal controls. Goal was to identify cholangiocarcinoma-specific differentially methylated regions (DMRs). Highly methylated DNA from cases and controls was enriched by methyl CpG-immunoprecipitation (MCIp) and co-hybridized. DMRs were defined by stepwise stringent criteria such as selecting top 5% vicinal array probes only. ECC- and ICC-specific and common DMRs were identified.

2016-02-26 | E-GEOD-44965 | biostudies-arrayexpress

Enhanced epigenetic profiling of classical human monocytes reveals a specific signature of healthy aging in the DNA methylome

Project description:The impact of healthy aging on molecular programming of immune cells is poorly understood. Here, we report comprehensive characterization of healthy aging in human classical monocytes, with a focus on epigenomic, transcriptomic, and proteomic alterations, as well as the corresponding proteomic and metabolomic data for plasma, using healthy cohorts of 20 young and 20 older males (~27 and ~64 years old on average). For each individual, we performed eRRBS-based DNA methylation profiling, which allowed us to identify a set of age-associated differentially methylated regions (DMRs) – a novel, cell-type specific signature of aging in DNA methylome. Hypermethylation events were associated with H3K27me3 in the CpG islands near promoters of lowly-expressed genes, while hypomethylated DMRs were enriched in H3K4me1 marked regions and associated with age-related increase of expression of the corresponding genes, providing a link between DNA methylation and age-associated transcriptional changes in primary human cells.

2022-02-16 | PXD021821 | Pride

1895b204-aae7-4786-87b9-75d328bc213c - samples

Project description:Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination.

| EGAD00001008696 | EGA

Cell free DNA 5-hydroxymethylcytosine as an emerging marker of acute myeloid leukemia

Project description:Aberrant changes in 5-hydroxymethylcytosine (5hmC) are a unique epigenetic feature in many cancers including acute myeloid leukemia (AML). However, genome-wide analysis of 5hmC in plasma cell-free DNA (cfDNA) remains unexploited in AML patients. We used a highly sensitive and robust nano-5hmC-Seal technology and profiled genome-wide 5hmC distribution in 239 plasma cfDNA samples from 103 AML patients and 81 non-cancer controls. We developed a 5hmC diagnostic model that precisely differentiates AML patients from controls with high sensitivity and specificity. We also developed a 5hmC prognostic model that accurately predicts prognosis in AML patients. High weighted prognostic scores (wp-scores) in AML patients were significantly associated with adverse overall survival (OS) in both training (P = 3.31e-05) and validation (P = .000464) sets. The wp-score was also significantly associated with genetic risk stratification and displayed dynamic changes with varied disease burden. Moreover, we found that high wp-scores in a single gene, BMS1 and GEMIN5 predicted OS in AML patients in both the training set (P =.023 and .031, respectively) and validation set (P = 9.66e-05 and 0.011, respectively). Lastly, our study demonstrated the genome-wide landscape of DNA hydroxymethylation in AML and revealed critical genes and pathways related to AML diagnosis and prognosis. Our data reveal plasma cfDNA 5hmC signatures as sensitive and accurate markers for AML diagnosis and prognosis. Plasma cfDNA 5hmC analysis will be an effective and minimally invasive tool for AML management.

2022-06-15 | GSE163846 | GEO

Multiplex 5mC Marker Barcode Counting (MMBC-seq): A sensitive detection method for cell-free DNA methylation

Project description:The detection of hypermethylation markers on cell-free DNA (cfDNA) in biological fluids is a promising and non-invasive approach for early diagnosis and monitoring of human diseases. However, it is challenging to detect hypermethylation markers in a high-throughput, sensitive, and cost-effective manner. Here we presented a multiplex 5-methylcytosine marker barcode counting (MMBC-seq) technique and reported its clinical application for cfDNA from peripheral plasma samples. We identified an MMBC cancer detection panel and developed a scoring system to differentiate cancer versus healthy controls. In a multiple-cancer case-control study, the panel achieved a sensitivity and specificity of 80.2% and 95.7% respectively (AUC 0.906, 95% CI 0.846-0.948). The results suggest that MMBC-seq has great potential to realize non-invasive, flexible and clinically applicable cancer detection.

2022-01-07 | GSE124775 | GEO

An integrative analysis of genome-wide 5-hydroxymethylcytosines in circulating cell-free DNA detects non-invasive diagnostic markers for gliomas

Project description:Background. Gliomas, especially the high-grade glioblastomas (GBM), are highly aggressive tumors in the central nervous system (CNS) with dismal clinical outcomes. Effective biomarkers, which are not currently available, may improve clinical outcomes through early detection. We sought to develop a non-invasive diagnostic approach for gliomas based on 5-hydroxymethylcytosines (5hmC) in circulating cell-free DNA (cfDNA). Methods. We obtained genome-wide 5hmC profiles using the 5hmC-Seal technique in cfDNA samples from 111 prospectively enrolled patients with gliomas and 111 age-, gender-matched healthy individuals, which were split into a training set and a validation set. Integrated models comprised of 5hmC levels summarized for gene bodies, long non-coding RNAs (lncRNAs), cis-regulatory elements, and repetitive elements were developed using the elastic net regularization under a case-control design. Results. The integrated 5hmC-based models differentiated healthy individuals from gliomas (AUC [area under the curve] = 84%; 95% confidence interval [CI], 74-93%), GBM patients (AUC = 84%; 95% CI, 74-94%), WHO II-III glioma patients (AUC = 86%; 95% CI, 76-96%), regardless of IDH1 (encoding isocitrate dehydrogenase) mutation status or other glioma-related pathological features such as TERT, TP53 in the validation set. Furthermore, the 5hmC biomarkers in cfDNA showed the potential as an independent indicator from IDH1 mutation status and worked in synergy with IDH1 mutation to distinguish GBM from WHO II-III gliomas. Exploration of the 5hmC biomarkers for gliomas revealed relevance to glioma biology. Conclusions. The 5hmC-Seal in cfDNA offers the promise as a non-invasive approach for effective detection of gliomas in a screening program.

2021-05-30 | GSE132118 | GEO

Mapping Transcription Factor Nucleosome Dynamics in Plasma

Project description:Cell-free DNA (cfDNA) contains a composite map of the epigenomes of its cells-of-origin. Tissue-specific TF binding inferred from cfDNA could enable us to track disease states in humans in a non-invasive manner. Here, we present a method to identify the subset of genome-wide transcription factor binding sites that are protected in plasma. We map binding at tissue-specific sites of constitutive factor CTCF and tissue-specific factors PU.1, LYL1, ER, and FOXA1 in plasma cfDNA. Our method also captures the chromatin structure around the factor-bound sites in their cells-of-origin. We define pure tumor TF signatures in an in vivo model by applying our method to estrogen receptor-positive (ER+) breast cancer xenografts. The tumor-specific cfDNA protections of ER-α and FOXA1 reflect TF-specific accessibility across human breast tumors, demonstrating our ability to capture tumor TF binding in plasma. By modeling cfDNA from cancer donors as a mixture of healthy plasma and pure tumor signatures, we can identify tumor TF binding in humans. Thus, our method enables non-invasive mapping of the regulatory phenotype of cancer in humans.

2021-05-24 | GSE171434 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data