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Genome-wide cell-free DNA fragmentation in patients with cancer

ABSTRACT: Genome-wide cell-free DNA fragmentation in patients with cancer

PROVIDER: PRJNA543357 | ENA |

REPOSITORIES: ENA

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Genome-wide cell-free DNA fragmentation in patients with cancer

Project description:Genome-wide cell-free DNA fragmentation in patients with cancer

| PRJNA543358 | ENA

Genome-wide cell-free DNA fragmentation in patients with cancer

Project description:Cell-free DNA (cfDNA) in the blood provides a noninvasive diagnostic avenue for patients with cancer. However, characteristics of the origins and molecular features of cfDNA are poorly understood. We developed an approach to evaluate fragmentation patterns of cfDNA across the genome and found that cfDNA profiles of healthy individuals reflected nucleosomal patterns of white blood cells, while patients with cancer had altered fragmentation profiles. We applied this method to analyze fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric, or bile duct cancers and 245 healthy individuals. A machine learning model incorporating genome-wide fragmentation features had sensitivities of detection ranging from 57% to >99% among the seven cancer types at 98% specificity, with an overall AUC of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation based cfDNA analyses detected 91% of cancer patients. The results of these analyses highlight important properties of cfDNA and provide a proof of principle approach for screening, early detection, and monitoring of human cancer.

| EGAS00001003611 | EGA

De novo Characterization of Cell-free DNA Fragmentation Hotspots in Plasma Whole-genome Sequencing.

Project description:De novo Characterization of Cell-free DNA Fragmentation Hotspots in Plasma Whole-genome Sequencing.

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De novo Characterization of Cell-free DNA Fragmentation Hotspots in Plasma Whole-genome Sequencing.

Project description:De novo Characterization of Cell-free DNA Fragmentation Hotspots in Plasma Whole-genome Sequencing.

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FinaleMe: Predicting DNA Methylation by the Fragmentation Patterns of Plasma Cell-free DNA

Project description:FinaleMe: Predicting DNA Methylation by the Fragmentation Patterns of Plasma Cell-free DNA

| PRJNA965896 | ENA

FinaleMe: Predicting DNA Methylation by the Fragmentation Patterns of Plasma Cell-free DNA

Project description:FinaleMe: Predicting DNA Methylation by the Fragmentation Patterns of Plasma Cell-free DNA

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Genome-wide plasma cell-free DNA methylation profiling in lung cancer patients using MeDIP-seq

Project description:Genome-wide plasma cell-free DNA methylation profiling in lung cancer patients using MeDIP-seq

| PRJEB28329 | ENA

Genome-wide plasma cell-free DNA methylation profiling in pancreatic cancer patients using MeDIP-seq

Project description:Genome-wide plasma cell-free DNA methylation profiling in pancreatic cancer patients using MeDIP-seq

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DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation.

Project description: Not available

| S-EPMC11303779 | biostudies-literature

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

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