Methylation profiling

Dataset Information

0

MCTA-Seq for profiling hypermethylated CpG islands in plasma of hepatocellular carcinoma patients


ABSTRACT: Despite advances in DNA methylome analyses of cells and tissues, current techniques for genome-scale profiling of DNA methylation in circulating cell-free DNA (ccfDNA) remain limited. Here we describe a methylated CpG tandems amplification and sequencing (MCTA-Seq) method that can detect thousands of hypermethylated CpG islands simultaneously in ccfDNA. This highly sensitive technique can work with genomic DNA as little as 7.5 pg, which is equivalent to 2.5 copies of the haploid genome. We have analyzed a cohort of tissue and plasma samples (n=151) of hepatocellular carcinoma (HCC) patients and control subjects, identifying dozens of high-performance markers in blood for detecting small HCC (<=3 cm). Among these markers, 4 (RGS10, ST8SIA6, RUNX2 and VIM) are mostly specific for cancer detection, while the other 15, classified as a novel set, are already hypermethylated in the normal liver tissues. Two corresponding classifiers have been established, combination of which achieves a sensitivity of 94% with a specificity of 89% for the plasma samples from HCC patients (n=36) and control subjects including cirrhosis patients (n=17) and normal individuals (n=38). Notably, all 15 alpha-fetoprotein-negative HCC patients were successfully identified. Comparison between matched plasma and tissue samples indicates that both the cancer and noncancerous tissues contribute to elevation of the methylation markers in plasma. MCTA-Seq will facilitate the development of ccfDNA methylation biomarkers and contribute to the improvement of cancer detection in a clinical setting.

ORGANISM(S): Homo sapiens

PROVIDER: GSE63775 | GEO | 2015/11/16

SECONDARY ACCESSION(S): PRJNA270585

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2014-01-30 | GSE54503 | GEO
2014-01-30 | E-GEOD-54503 | biostudies-arrayexpress
2015-02-13 | E-GEOD-56588 | biostudies-arrayexpress
2019-05-31 | GSE124600 | GEO
2024-01-01 | GSE220160 | GEO
2015-05-05 | E-GEOD-59259 | biostudies-arrayexpress
2015-05-05 | E-GEOD-59260 | biostudies-arrayexpress
2019-01-01 | GSE93203 | GEO
2021-01-31 | GSE136380 | GEO
2021-01-31 | GSE136319 | GEO