Nucleosome footprinting in plasma cell-free DNA for diagnosis of ovarian cancer
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ABSTRACT:
PROVIDER: EGAS00001005361 | EGA |
REPOSITORIES: EGA
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Project description:Nucleosomes are the basic unit of packaging of eukaryotic chromatin, and nucleosome positioning can differ substantially between cell types. Here, we sequence 14.5 billion plasma-borne cell-free DNA (cfDNA) fragments (700-fold coverage) to generate genome-wide maps of in vivo nucleosome occupancy. We identify 13 million local maxima of nucleosome protection, spanning 2.53 gigabases (Gb) of the human genome, whose positions and spacings correlate with nuclear architecture, gene structure and gene expression. We further show that short cfDNA fragments - poorly recovered by standard protocols - directly footprint the in vivo occupancy of DNA-bound transcription factors such as CTCF. The sequence composition of cfDNA has previously been used to noninvasively monitor cancer, pregnancy and organ transplantation, but a key limitation of this paradigm is its dependence on genotypic differences to distinguish between contributing tissues. We show that nucleosome spacing in gene bodies and cis-regulatory elements, inferred from cfDNA in healthy individuals, correlates most strongly with transcriptional and epigenetic features of lymphoid and myeloid cells, consistent with hematopoietic cell death as the normal source of cfDNA. We build on this observation to show how in vivo nucleosome footprints can be used to infer the cell types that contribute to circulating cfDNA in pathological states such as cancer. Because it does not rely on genotypic differences, this strategy may enable the noninvasive cfDNA-based monitoring of a much broader set of clinical conditions than is currently possible. Sequencing of cfDNA libraries from healthy individuals, pooled healthy individuals and individuals with disease for the identification of nucleosomes and protection from other DNA binding proteins.
2015-11-04 | E-GEOD-71378 | biostudies-arrayexpress
Project description:The genome-wide analysis of cfDNA fragmentation patterns in DENQCMs and maternal plasma was performed by deep sequencing using Illumina Novaseq to confirm their biological characteristics. We first performed deep whole genome sequencing of the cfDNA extracted from DENQCMs and maternal plasma cfDNA. Then we analyzed the sequencing data and compared various characteristics of cfDNA fragmentation patterns, such as dinucleotide composition, nucleosome protection length, and nucleosome occupancy based on a windowed protection score (WPS), to the submitter-provided processed data from a healthy individual IH01 (GEO accession GSM1833276).
2019-01-05 | GSE124686 | GEO
Project description:Nucleosomes are the basic unit of packaging of eukaryotic chromatin, and nucleosome positioning can differ substantially between cell types. Here, we sequence 14.5 billion plasma-borne cell-free DNA (cfDNA) fragments (700-fold coverage) to generate genome-wide maps of in vivo nucleosome occupancy. We identify 13 million local maxima of nucleosome protection, spanning 2.53 gigabases (Gb) of the human genome, whose positions and spacings correlate with nuclear architecture, gene structure and gene expression. We further show that short cfDNA fragments - poorly recovered by standard protocols - directly footprint the in vivo occupancy of DNA-bound transcription factors such as CTCF. The sequence composition of cfDNA has previously been used to noninvasively monitor cancer, pregnancy and organ transplantation, but a key limitation of this paradigm is its dependence on genotypic differences to distinguish between contributing tissues. We show that nucleosome spacing in gene bodies and cis-regulatory elements, inferred from cfDNA in healthy individuals, correlates most strongly with transcriptional and epigenetic features of lymphoid and myeloid cells, consistent with hematopoietic cell death as the normal source of cfDNA. We build on this observation to show how in vivo nucleosome footprints can be used to infer the cell types that contribute to circulating cfDNA in pathological states such as cancer. Because it does not rely on genotypic differences, this strategy may enable the noninvasive cfDNA-based monitoring of a much broader set of clinical conditions than is currently possible.
2015-11-04 | GSE71378 | GEO
Project description:To identify diagnostic and prognostic biomarkers, we compared methylation profiles of COAD tissues and normal blood at 485,000 CpG markers and identified a marker panel differently methylated in COAD. We developed diagnostic and prognostic prediction models with the selected panel and compared their efficacy in ctDNA to current available approaches. Our data indicate that cfDNA methylation patterns provide reliable biomarkers in the diagnosis, surveillance, and prognosis of COAD.
2020-01-01 | GSE97923 | GEO
Project description:To identify diagnostic and prognostic biomarkers, we compared methylation profiles of LUNC tissues and normal blood at 485,000 CpG markers and identified a marker panel differently methylated in LUNC. We developed diagnostic and prognostic prediction models with the selected panel and compared their efficacy in ctDNA to current available approaches. Our data indicate that cfDNA methylation patterns provide reliable biomarkers in the diagnosis, surveillance, and prognosis of LUNC.
2020-01-01 | GSE97932 | GEO
Project description:We report nucleosome positions by using native Mnase-seq. The results strongly suggest that nucleosome positions don't change at the heterochromatic locus HMR upon removal of adjacent nucleosomes via deletion of nucleosomal DNA. Positions of nucleosomes at HML are also quantified.
2019-09-06 | GSE136897 | 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:The early detection of tissue and organ damage associated with autoimmune diseases (AID) has been identified as key to improve long-term survival, but non-invasive biomarkers are lacking. Elevated cell-free DNA (cfDNA) levels have been observed in AID and inflammatory bowel disease (IBD), prompting interest to use cfDNA as a potential non-invasive diagnostic and prognostic biomarker. Despite these known disease-related changes in concentration, it remains impossible to identify AID and IBD patients through cfDNA analysis alone. By using unsupervised clustering on large sets of shallow whole-genome sequencing (sWGS) cfDNA data, we uncover AID- and IBD-specific genome-wide patterns in plasma cfDNA in both the obstetric and general AID and IBD populations. Supervised learning of the genome-wide patterns allows AID prediction with 50% sensitivity at 95% specificity. Importantly, the method can identify pregnant women with AID during routine non-invasive prenatal screening. Since AID pregnancies have an increased risk of severe complications, early recognition or detection of new onset AID can redirect pregnancy management and limit potential adverse events. This method opens up new avenues for screening, diagnosis and monitoring of AID and IBD.
2022-09-14 | E-MTAB-11607 | biostudies-arrayexpress
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: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