Genome-wide DNA methylation profiling of cell-free DNA in nipple aspirate fluid for breast cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE238014 | GEO | 2023/09/26
REPOSITORIES: GEO
Similar Datasets
Project description:Sampling the live brain is difficult and dangerous, and withdrawing cerebrospinal fluid is uncomfortable and frightening to the subject, so new sources of real-time analysis are constantly sought. Cell-free DNA (cfDNA) derived from glia and neurons offers the potential for wide-ranging neurological disease diagnosis and monitoring. However, new laboratory and bioinformatic strategies are needed. DNA methylation patterns on individual cfDNA fragments can be used to ascribe their cell-of-origin. Here we describe bisulfite sequencing assays and bioinformatic processing methods to identify cfDNA derived from glia and neurons. In proof-of-concept experiments we describe the presence of both glia- and neuron-cfDNA in the blood plasma of human subjects following mild trauma. These detection of glia- and neuron-cfDNA represents a significant step forward in the translation of liquid biopsies for neurological diseases.
2021-02-06 | GSE126663 | GEO
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
Project description:Whole-genome bisulfite sequencing (BS-Seq) measures cytosine methylation changes at single-base resolution and can be used to profile cell-free DNA (cfDNA). In plasma, ultrashort single-stranded cfDNA (uscfDNA, ~50 nt) has been identified together with 167 bp double-stranded mononucleosomal cell-free DNA (mncfDNA). However, the methylation profile of uscfDNA has not been described. Conventional BS-Seq workflows may not be helpful because bisulfite conversion degrades larger DNA into smaller fragments, leading to erroneous categorization as uscfDNA. We describe the “5mCAdpBS-Seq” workflow in which pre-methylated 5mC (5-methylcytosine) single-stranded adapters are ligated to heat-denatured cfDNA before bisulfite conversion. This method retains only DNA fragments that are unaltered by bisulfite treatment, resulting in less biased uscfDNA methylation analysis. Using 5mCAdpBS-Seq, uscfDNA had lower levels of DNA methylation (~15%) and was enriched in promoters and CpG islands. Hypomethylated uscfDNA fragments were enriched in upstream transcription start sites (TSSs), and the intensity of enrichment positively affected gene expression of hemopoietic cells. Using tissue-of-origin deconvolution, we inferred that uscfDNA is derived primarily from eosinophils, neutrophils, and monocytes. As proof-of-principle, we show that characteristics of the methylation profile of uscfDNA can distinguish non-small cell lung carcinoma from non-cancer samples. The 5mCAdpBS-Seq workflow is recommended for any cfDNA methylation-based investigations.
2024-03-28 | GSE252088 | GEO
Project description:Background: Liquid biopsy based on cell free DNA (cfDNA) analysis holds significant promise as a minimally invasive approach for the diagnosis, genotyping and monitoring of solid malignancies. Human tumors release cfDNA in the bloodstream through a combination of events, including cell death, active and passive release. However, the precise mechanisms leading to cfDNA shedding remain to be characterized. Addressing this question in patients is confounded by several factors, such as tumor burden extent, anatomical and vasculature barriers, release of nucleic acids from normal cells. In this work, we exploited cancer models to dissect basic mechanisms of DNA release. Methods: We measured cell loss ratio, doubling time and cfDNA release in the supernatant of a colorectal cancer (CRC) cell line collection (N=76) representative of the molecular subtypes previously identified in cancer patients. Association analyses between quantitative parameters of cfDNA release, cell proliferation and molecular features were evaluated. Functional experiments were performed to test the impact of modulating DNA methylation on cfDNA release. Results: Higher levels of supernatant cfDNA were significantly associated with slower cell cycling and increased cellular crashes. In addition, a higher cfDNA shedding was found in non-CpG Island Methylator Phenotype (CIMP) models. These results indicate a positive correlation between lower methylation and increased cfDNA levels. To explore this further, we exploited methylation microarrays to identify a subset of probes significantly associated with cfDNA shedding and derive a methylation signature capable of discriminating high from low cfDNA releasers. We applied this signature to an independent set of 176 CRC cell lines and patient derived organoids to select 14 models predicted to be low or high releasers. The methylation profile successfully predicted the amount of cfDNA released in the supernatant. At the functional level, genetic ablation of DNA methyl-transferases increased chromatin accessibility and DNA fragmentation, leading to increased cfDNA release in isogenic CRC cell lines. Furthermore, in vitro treatment of five low releaser CRC cells with a demethylating agent was able to induce a significant increase in cfDNA shedding. Conclusion: Methylation status of cancer cell lines contributes to the variability of cfDNA shedding in vitro. Changes in methylation pattern are associated with cfDNA release levels and might be exploited to increase sensitivity of liquid biopsy assays.
2024-09-18 | GSE274189 | GEO
Project description:Molecular biomarkers to monitor changes after liver transplant are essential to reveal mechanisms of injury, guide clinical decision-making and improve patient outcomes. Current approaches have limited scope and are unable to differentiate between host and graft amongst the causes of graft injury. Here, we utilize circulating, cell-free methylated DNA released from dying cells to monitor cellular damages after liver transplant impacting the graft tissue as well as host organs. We expand existing cell-type-specific DNA methylation atlases curated from whole-genome bisulfite sequencing (WGBS) of healthy tissues to characterize liver cell-types relevant to injury progression and tissue repair. Liver cell-type-specific methylation blocks are validated through multi-omic data integration and found to be enriched in open chromatin and regulatory regions functionally important for the respective cell populations. Cell-free DNA (cfDNA) fragments were captured from patient serum by hybridization to CpG-rich DNA panels and mapped to the expanded DNA methylation atlases to inform tissue origins of cell types. We profiled 135 blood samples collected from 44 liver transplant patients at serial time points before and after transplant. We found that liver transplant initially results in multi-tissue cellular damage that subsequently recovers in patients with graft acceptance during the first post-operative week. Further, we show that sustained elevation of hepatocyte and biliary epithelial cfDNA beyond the first week is indicative of early-onset graft injury. Most notably, cfDNA composition can differentiate amongst causes of graft injury. Thus, cell-free methylated DNA can detect cellular damages and prompt early intervention.
2025-03-02 | GSE262273 | GEO
Project description:Genome-wide DNA methylation profiling of cell-free DNA in nipple aspirate fluid for breast cancer
| PRJNA997370 | ENA
Project description:cfDNA (Cell-free DNA) was extracted from serum exosome of gastric cancer patient. We analyzed cfDNA by aCGH (array comparative genomic hybridization).
2018-03-31 | GSE108602 | GEO
Project description:Current methods for mapping the tissue-of-origin of circulating cell-free DNA (cfDNA) are still insufficient. Here, we have extended a previously developed methylated CpG tandems amplification and sequencing (MCTA-Seq) method for quantitative analysis of tissue-of-origin of plasma cfDNA. By comparing paired plasma cfDNA and white blood cell genomic DNA, we have demonstrated that the liver is the major non-hematopoietic tissue contributing to plasma cfDNA in healthy adults, accounting for approximately 2%. Furthermore, we have detected changes in liver-derived DNA in patients with benign liver diseases and increases in pancreas-derived DNA in acute pancreatitis patients. Interestingly, our results suggest that DNA derived from pathological tissues makes a minor contribution to the increased cfDNA in many clinical cases. Finally, we have identified a tissue-specific hypermethylated cfDNA marker located in the intragenic regions of tissue-specifichighlyexpressed genes. This study represents valuable progress in the field of cfDNA and offers promise for clinical research and medical diagnostics using the described method.
2019-07-01 | GSE118690 | GEO
Project description:Blood cell counts often fail to report on immune processes occurring in remote tissues. Here we use 25 immune cell type-specific methylation patterns in circulating cell-free DNA (cfDNA) for studying 26 human immune cell dynamics. We characterized cfDNA released from specific immune cell types in 27 healthy individuals (N=242), cross sectionally and longitudinally. Immune cfDNA levels had no 28 individual steady state as opposed to blood cell counts, suggesting that cfDNA concentration reflects 29 adjustment of cell survival to maintain homeostatic cell numbers. We also observed selective elevation 30 of immune-derived cfDNA upon perturbations of immune homeostasis. Following influenza 31 vaccination (N=92), B-cell-derived cfDNA levels increased prior to elevated B-cell counts and 32 predicted efficacy of antibody production. Patients with Eosinophilic Esophagitis (N=21) and B-cell 33 lymphoma (N=27) showed selective elevation of eosinophil and B-cell cfDNA respectively, which 34 were undetectable by cell counts in blood. Immune-derived cfDNA provides a novel biomarker for 35 monitoring immune responses to physiological and pathological processes that are not accessible using 36 conventional methods.
2021-11-26 | GSE186888 | GEO
Project description:Circulating cell-free DNA (cfDNA) in the bloodstream originates from dying cells and is a promising non-invasive biomarker for cell death. Here, we propose an algorithm, CelFiE, to accurately estimate relative abundances of cell types and tissues contributing to cfDNA from epigenetic cfDNA sequencing. In contrast to previous work, CelFiE accommodates low coverage data, does not rely on CpG site curation, and estimates contributions from multiple unknown cell types that are not available in external reference data. In simulations, CelFiE accurately estimates known and unknown cell type proportions from low coverage and noisy cfDNA mixtures, including from rare cell types composing less than 1% of the total mixture. In a positive control of cfDNA extracted from pregnant and non-pregnant women, CelFiE correctly estimates a large placenta component specifically in pregnant women (p = 4.5x10^-5). In cfDNA from ALS patients and age-matched controls, we observed increased cfDNA concentrations in ALS patients (p = 5.0x10^-3), and CelFiE identified a corresponding increased skeletal muscle component (p = 2.4x10^-3), consistent with muscle impairment characterizing ALS. Together these results show CelFiE may be a useful tool for biomarker discovery and monitoring of degenerative disease progression.
2021-01-12 | GSE164600 | GEO