Cell-free DNA 5-hydroxymethylcytosine as a marker for common cancer detection
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE202988 | GEO | 2022/09/23
REPOSITORIES: GEO
Similar Datasets
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
Project description:Background: Elucidating epigenetic mechanisms could provide new biomarkers for disease diagnosis and prognosis. Technological advances allow genome-wide profiling of 5-hydroxymethylcytosines (5hmC) in liquid biopsies. 5hmC-Seal followed by NGS is a highly sensitive technique for 5hmC biomarker discovery in cfDNA. Currently, 5hmC Seal is optimized for EDTA blood collection. We asked whether heparin was compatible with 5hmC Seal as many clinical and biobanked samples are stored in heparin. Methods: We obtained 60 samples in EDTA matched to 60 samples in heparin from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Samples were comprised of 30 controls and 30 individuals who later were diagnosed with colon cancer. We profiled genome-wide 5hmC in cfDNA using 5hmC-Seal assay followed by NGS. The 5hmC profiling data from samples collected in EDTA were systematically compared to those in heparin across various genomic features. Results: cfDNA isolation and library construction appeared comparable in heparin vs. EDTA. Typical genomic distribution patterns of 5hmC, including gene bodies and enhancer markers, were comparable in heparin vs. EDTA. 5hmC analysis of cases and controls yielded highly correlated differential features suggesting that both anticoagulants were compatible with 5hmC Seal assay. Conclusions: While not currently recommended for the 5hmC-Seal protocol, blood samples stored in heparin were successfully used to generate analyzable and biologically relevant genome-wide 5hmC profiling. Our findings are the first to support opportunities to expand the biospecimen resource to heparin samples for 5hmC Seal and perhaps other PCR-based technologies in epigenetic research.
2023-11-14 | GSE230027 | GEO
Project description:Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurate prediction of individual patient responses to ICIs remains a challenge. We performed a genome-wide analysis of 5-hydroxymethylcytosine (5hmC) in plasma cell-free DNA (cfDNA) samples from 83 lung cancer patients. Using machine learning approaches, we developed a 5hmC signature to predict ICI treatment response and calculated a weighted-predictive score (wp-score) based on the 5hmC levels of signature genes in each sample. A low wp-score was significantly correlated with longer progression-free survival across three independent patient sample sets, and demonstrated superior predictive capability to tumor programmed death-ligand 1. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. Our study suggests that cfDNA 5hmC analysis is a minimally invasive, innovative strategy for guiding treatment selection in lung cancer patients.
2024-02-28 | GSE237087 | GEO
Project description:Investigations of 5-hydroxymethylcytosine (5hmC) in biologically and clinically samples and models with low cell numbers have been hampered by the low sensitivity and reproducibility using current 5hmC mapping approaches. Here, we develop a selective 5hmC chemical labeling approach using tagmentation-based library preparation in order to profile nanogram levels of 5hmC isolated from ~1,000 cells (nano-hmC-Seal). Using this technology, we profiled the dynamics of 5hmC across different stages of mouse hematopoietic differentiation. Additionally, applying nano-hmC-Seal to the hematopoietic multipotent progenitor cells in an acute myeloid leukemia (AML) mouse model, we identified leukemia-specific, differentially hydroxymethylated regions that harbor previously reported and as-yet-unidentified functionally relevant factors. The change of 5hmC patterns in AML strongly correlates with the altered gene expression on a global scale. Together, our new approach offers a highly sensitive and robust method to study and detect DNA methylation dynamics from in vivo model and clinical samples. Selective 5hmC chemical labeling approach using tagmentation-based library preparation in order to profile nanogram levels of 5hmC isolated from ~1,000 cells
2016-09-01 | E-GEOD-77967 | biostudies-arrayexpress
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:The genome-wide profiling of 5-hydroxymethylcytosine (5hmC) on circulating cell-free DNA (cfDNA) has revealed promising biomarkers for a variety of diseases. The purpose of our study is to investigate if 5hmC profiles from serum cfDNA are novel predictive biomarkers for the development of chemoresistance in high-grade serous ovarian cancer (HGSOC). We hypothesized that 5-hmC profiles associate with the development of chemoresistance and elucidate pathways that may drive chemoresistance in HGSOC. We developed a novel multivariate model based on clinico-pathologic data and a cfDNA-derived 5hmC-annotated gene that can predict response to platinum-based chemotherapy in intermediate-sensitive HGSOC. These results merit further investigation of our model as a predictive model.
2024-01-25 | GSE240535 | GEO
Project description:Investigations of 5-hydroxymethylcytosine (5hmC) in biologically and clinically samples and models with low cell numbers have been hampered by the low sensitivity and reproducibility using current 5hmC mapping approaches. Here, we develop a selective 5hmC chemical labeling approach using tagmentation-based library preparation in order to profile nanogram levels of 5hmC isolated from ~1,000 cells (nano-hmC-Seal). Using this technology, we profiled the dynamics of 5hmC across different stages of mouse hematopoietic differentiation. Additionally, applying nano-hmC-Seal to the hematopoietic multipotent progenitor cells in an acute myeloid leukemia (AML) mouse model, we identified leukemia-specific, differentially hydroxymethylated regions that harbor previously reported and as-yet-unidentified functionally relevant factors. The change of 5hmC patterns in AML strongly correlates with the altered gene expression on a global scale. Together, our new approach offers a highly sensitive and robust method to study and detect DNA methylation dynamics from in vivo model and clinical samples.
2016-09-01 | GSE77967 | GEO
Project description:Mapping genome-wide 5-hydroxymethylcytosine (5hmC) and 5-formylcytosine (5fC) at single-base resolution is important to understand their biological functions. We present a cost-efficient mapping method that combines 5hmC-specific restriction enzyme PvuRts1I with a 5hmC enrichment method. The sensitive method enables detection of low abundant 5hmC sites, providing a more complete 5hmC landscape than available bisulfite-based methods. This method generated the first genome-wide 5fC map at single-base resolution. Parallel analyses revealed that 5hmC and 5fC existed with lower abundance and more dynamically in non-CpG context than in CpG context. In the genic region, distribution of 5hmCpG and 5fCpG differed from 5hmCH and 5fCH (H=A, T, C). 5hmC and 5fC were distributed distinctly at regulatory protein-DNA binding sites, depleted in permissive transcription factor binding sites, and enriched at active and poised enhancers. This sensitive bisulfite-conversion free method can be applied to biological samples with limited starting material or low abundance of cytosine modifications. Sensitive mapping of genome-wide 5-hydroxymethylcytosine and 5-formylcytosine in mouse embryonic stem cell at single-base resolution by combining 5-hydroxymethylcytosine specific restriction enzyme PvuRts1I and 5-hydroxymethylcytosine enrichment method (selective chemical labeling or SEAL)
2014-12-22 | E-GEOD-64186 | biostudies-arrayexpress
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
Project description:Pancreatic cancers are typically diagnosed at late stage where disease prognosis is poor as exemplified by a 5-year survival rate of 10%. Earlier diagnosis would be beneficial by enabling surgical resection or earlier application of therapeutic regimens. We investigated non-invasive detection of pancreatic ductal adenocarcinoma (PDAC) by interrogating changes in 5-hydroxymethylation cytosines (5hmC) of circulating cell free DNA in the plasma of a PDAC cohort (n=64) in comparison with a non-cancer cohort (n=243). 5hmC density is reduced in promoters and enhancers, whereas it is increased over 3’UTR, intron and TTS regions in PDAC compared to non-cancer cfDNA. Differential hydromethylation is rampant and found in thousands of genes. Stringent filtering by significance reveals genes related to pancreas function or development (GATA4, GATA6, PROX1, ONECUT1, MEIS2), and/or cancer pathogenesis (YAP1, TEAD1, PROX1, ONECUT1, ONECUT2 and IGF1). Furthermore, we observe enrichment for genes that are de-regulated upon activation of KRAS and inactivation of TP53, both of which are commonly observed in PDAC tumors. Regularized regression models, built using 5hmC densities in genes with the most variable 5hmC counts, performed with AUC of 0.92 on discovery dataset and 0.92-0.94 on two independent test sets. Furthermore, investigation of 5hmC occupancy in PDAC tumor tissue revealed that tissue-derived features can be used to accurately classify PDAC cfDNA (AUC=0.88). These findings suggest that 5hmC changes, at least partially derived from tumor tissue, enable classification of PDAC patients with high fidelity and are worth further investigation on larger cohorts of patient samples.
2020-08-26 | GSE152137 | GEO