Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE122126 | GEO | 2018/11/04
REPOSITORIES: GEO
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Project description:Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Here we present one of the largest comprehensive and high-resolution methylation atlas based on Reduced Representative Bisulfite Sequencing (RRBS) data of 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively alidated the methylation signature atlas in independent methylation datasets, orthogonal epigenomic markers, and transcription regulatory elements. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA.
2023-06-15 | GSE233417 | GEO
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Project description:We explored the differential methylation patterns found in cfDNA between healthy controls (individuals with no colorectal findings, NCF) and patients with advanced neoplasia (advanced adenomas and colorectal cancer, AA andCRC) using pooled samples, to determine if pooled serum cfDNA samples can be used to search for non-invasive methylation biomarkers, as an affordable and efficient alternative to tissue biopsy. cfDNA was extracted from serum samples and methylation measurements were assessed with the Infinium MethylationEPIC BeadChip. Data was mainly preprocessed and analyzed with R/Bioconductor packages.
2018-04-17 | GSE110185 | 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
Project description:Elevated level of circulating cell-free DNA (cfDNA) has been associated with poor prognosis and relapse in patients with diffuse large B-cell lymphoma (DLBCL), but the tumor-specific molecular alterations in cfDNA with prognostic significance remain unclear. We investigated the association between 5-hydroxymethylcytosines (5hmC), a mark of active demethylation and gene activation, in cfDNA from blood plasma and prognosis in DLBCL. We used the 5hmC-Seal, a highly sensitive chemical labeling technique, to profile genome-wide 5hmC in plasma cfDNA samples from 48 newly diagnosed patients with DLBCL at the University of Chicago between 2010 and 2012. Patients were followed through December 31, 2017. We found a distinct genomic distribution of 5hmC in cfDNA marking tissue-specific enhancers, consistent with their potential roles in gene regulation. The 5hmC profiles in cfDNA differed by cell-of-origin, and were associated with clinical prognostic features including Ann Arbor stage, serum lactate dehydrogenase (LDH) level, and the International Prognostic Index (IPI). We developed a 29 gene-based weighted prognostic score (wp-score) for predicting event-free survival (EFS) and overall survival (OS), by applying the elastic net regularization on the Cox proportional hazard model. The wp-scores showed significantly improved prognostic accuracy and/or sensitivity/specificity than the established prognostic factors. In multivariate Cox models, patients with high wp-scores were associated with worse event-free survival (Hazard Ratio [HR] = 9.17, 95% confidence interval [CI] = 2.01- 41.89, p = 0.004), compared with those in the low risk group. Our findings suggest that the 5hmC signatures in cfDNA at the time of diagnosis are associated with clinical outcomes in DLBCL and may provide a novel non-invasive prognostic approach for DLBCL.
2019-11-15 | GSE126676 | GEO
Project description:Small-cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, each with unique therapeutic vulnerabilities. Implementing subtyping in the clinic has remained challenging due to limited tissue availability, particularly for longitudinal monitoring. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that there would be subtype-specific patterns of DNA methylation that could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts of totally 179 SCLC patients and machine learning approaches, we developed a highly accurate DNA methylation-based classifier (SCLC-DMC) that could distinguish SCLC subtypes using clinical tumor samples with 95.8% accuracy in the testing set compared to mRNA-based profiling. We further adjusted the classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using the cfDNA classifier (cfDMC) we could demonstrate that SCLC phenotypes can evolve during disease progression, highlighting the need for longitudinal tracking of SCLC during clinical treatment. Furthermore, methylation-based subtyping predicted response to a wide variety of drugs in preclinical models and clinical outcomes were indistinguishable in cohorts of patients subtyped using mRNA or SCLC-DMC. These data establish that tumor and cfDNA methylation can be used to identify SCLC subtypes and guide precision SCLC therapy.
2024-01-22 | GSE241673 | GEO
Project description:Genomic profiles of tumor DNA obtained from biopsies were systematically compared to corresponding samples of circulating cell free tumor DNA. The aim was to investigate correspondance between numerical, segmental and focal aberrations, as well as precision in detection and resolution of oncoscan array performance on cfDNA.
2016-11-30 | GSE85937 | GEO
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 & Aims. Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is growing in incidence but treatment options remain limited, particularly for late stage disease. As liver cirrhosis is the principal risk state for HCC development, markers to detect early HCC within this patient population are urgently needed. Perturbation of epigenetic marks, such as DNA methylation (5mC), is a hallmark of human cancers, including HCC. Identification of regions with consistently altered 5mC levels in circulating cell free DNA (cfDNA) during progression from cirrhosis to HCC could therefore serve as markers for development of minimally-invasive screens of early HCC diagnosis and surveillance. Methods. To discover DNA methylation derived biomarkers of HCC in the background of liver cirrhosis, we profiled genome-wide 5mC landscapes in patient cfDNA using the Infinium HumanMethylation450k BeadChip Array. We further linked these findings to primary tissue data available from TCGA and other public sources. Using biological and statistical frameworks, we selected CpGs that robustly differentiated cirrhosis from HCC in primary tissue and cfDNA followed by validation in an additional independent cohort. Results. We identified CpGs that segregate patients with cirrhosis, from patients with HCC within a cirrhotic liver background, through genome-wide analysis of cfDNA 5mC landscapes. Lasso regression analysis pinpointed a panel of probes in our discovery cohort that were validated in two independent datasets. A panel of five CpGs (cg04645914, cg06215569, cg23663760, cg13781744, and cg07610777) yielded AUROCs of 0.9525, 0.9714, and 0.9528 in cfDNA discovery and tissue validation cohorts 1 and 2, respectively. Conclusions. 5mC markers derived from cfDNA robustly identify HCC within a cirrhotic liver background indicating that further validation is warranted. Our finding that 5mC markers derived from primary tissue did not perform well in cfDNA, compared to those identified directly from cfDNA, reveals potential advantages of starting with cfDNA to discover high performing markers for liquid biopsy development.
2019-08-16 | GSE129374 | GEO