Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Cell-free DNA 5-hydroxymethylcytosine for immunotherapy response prediction in lung cancer

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE237087 | GEO | 2024/02/28

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Prognostic implications of 5-hydroxymethylcytosines from circulating cell-free DNA in diffuse large B-cell lymphoma

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

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

Shotgun sequencing of 5-hydroxymethylcysotine circulating cell-free DNA from the blood distinguishes solid tumor tissues of origin

Project description:5-Hydroxymethylcytosine (5hmC) is an important mammalian DNA epigenetic modification that has been linked to gene regulation and cancer pathogenesis. Here we explored the diagnostic potential of 5hmC in cell-free DNA (cfDNA), the circulating DNA found in human plasma which represents a noninvasive window into the health status of the body. We showed that the genome-wide 5hmC distribution in cfDNA can be reliably sequenced by chemical labeling-based 5hmC enrichment. We sequenced cell-free 5hmC from 49 patients of seven different cancer types and found distinct features that can be used for monitoring disease status and progression. Specifically, we discovered that lung cancer leads to a stage-dependent hypohydroxymethlation in cfDNA, whereas hepatocellular carcinoma (HCC) and pancreatic cancer lead to disease-specific changes in the cell-free hydroxymethylome. Our results demonstrate that cell-free 5hmC can be used not only to track the stage of cancer but also to identify tissue of origin in some solid tumors.

2017-07-13 | GSE81314 | GEO

5-Hydroxymethylcytosine signals in serum are a predictor of chemoresistance in high-grade serous ovarian cancer

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

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

DNA 5-hydroxymethylcytosines from cell-free circulating DNA as diagnostic biomarkers for human cancers

Project description:DNA modifications such as 5-methylcytosines (5mC) and 5-hydroxymethylcytosines (5hmC) are epigenetic marks known to affect global gene expression in mammals. Given their prevalence in the human genome, close correlation with gene expression, and high chemical stability, these DNA epigenetic marks could serve as ideal biomarkers for cancer diagnosis. Taking advantage of a highly sensitive and selective chemical labeling technology, we report here genome-wide 5hmC profiling in circulating cell-free DNA (cfDNA) and paired tumor/adjacent tissues collected from a cohort of 90 healthy individuals and 260 patients recently diagnosed with colorectal, gastric, pancreatic, liver, or thyroid cancer. 5hmC was mainly distributed in transcriptionally active regions coincident with open chromatin and permissive histone modifications. Robust cancer-specific epigenetic signatures in cfDNA were identified in different cancers. 5hmC-based biomarkers demonstrated highly accurate predictive value for patients with colorectal and gastric cancers versus healthy controls, superior to conventional biomarkers, and comparable to epigenetic biomarkers from tissue biopsies. This new strategy could lead to the development of an effective blood-based, minimally-invasive cancer diagnosis and prognosis approach.

2017-09-05 | GSE89570 | GEO

Targeted next generation sequencing of cfDNA from lung cancer patients enrolled in the GALAXY-1 trial (NCT01348126)

Project description:We evaluated whether targeted next-generation sequencing (NGS) using the Ion Torrent Personal Genome Sequencer of cfDNA could identify prognostic or predictive factors for overall survival (OS) or progression free survival (PFS) within a large cohort of patients with advanced lung adenocarcinoma enrolled in the GALAXY-1 trial.

2018-01-10 | E-MTAB-5749 | biostudies-arrayexpress

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

Comparative cardiac transcriptomics of immune checkpoint inhibitor induced myocarditis

Project description:Immune checkpoint inhibitors (ICIs) are improving cancer treatments strikingly. The raising use leads to the augmented occurrence of immune related events. Myocarditis is a rare, but severe form of these adverse events. Nine patients with proven ICI induced myocarditis were subjected to myocardial biopsy. The tissue was used for RNA-seq analyses.

2020-11-01 | E-MTAB-8867 | biostudies-arrayexpress

Host-specific differences in top-expanded TCR clonotypes correlate with divergent outcomes of anti-PD-L1 treatment in responders versus non-responders

Project description:Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment; however, the responses to ICI treatment are highly variable in different individuals and the underlying mechanisms remain poorly understood.

2023-03-17 | GSE227404 | 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