Dataset Information

Identification of tissue-specific cell death using methylation patterns of circulating DNA.

ABSTRACT: Minimally invasive detection of cell death could prove an invaluable resource in many physiologic and pathologic situations. Cell-free circulating DNA (cfDNA) released from dying cells is emerging as a diagnostic tool for monitoring cancer dynamics and graft failure. However, existing methods rely on differences in DNA sequences in source tissues, so that cell death cannot be identified in tissues with a normal genome. We developed a method of detecting tissue-specific cell death in humans based on tissue-specific methylation patterns in cfDNA. We interrogated tissue-specific methylome databases to identify cell type-specific DNA methylation signatures and developed a method to detect these signatures in mixed DNA samples. We isolated cfDNA from plasma or serum of donors, treated the cfDNA with bisulfite, PCR-amplified the cfDNA, and sequenced it to quantify cfDNA carrying the methylation markers of the cell type of interest. Pancreatic ?-cell DNA was identified in the circulation of patients with recently diagnosed type-1 diabetes and islet-graft recipients; oligodendrocyte DNA was identified in patients with relapsing multiple sclerosis; neuronal/glial DNA was identified in patients after traumatic brain injury or cardiac arrest; and exocrine pancreas DNA was identified in patients with pancreatic cancer or pancreatitis. This proof-of-concept study demonstrates that the tissue origins of cfDNA and thus the rate of death of specific cell types can be determined in humans. The approach can be adapted to identify cfDNA derived from any cell type in the body, offering a minimally invasive window for diagnosing and monitoring a broad spectrum of human pathologies as well as providing a better understanding of normal tissue dynamics.

SUBMITTER: Lehmann-Werman R

PROVIDER: S-EPMC4822610 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Identification of tissue-specific cell death using methylation patterns of circulating DNA.

Lehmann-Werman Roni R Neiman Daniel D Zemmour Hai H Moss Joshua J Magenheim Judith J Vaknin-Dembinsky Adi A Rubertsson Sten S Nellgård Bengt B Blennow Kaj K Zetterberg Henrik H Spalding Kirsty K Haller Michael J MJ Wasserfall Clive H CH Schatz Desmond A DA Greenbaum Carla J CJ Dorrell Craig C Grompe Markus M Zick Aviad A Hubert Ayala A Maoz Myriam M Fendrich Volker V Bartsch Detlef K DK Golan Talia T Ben Sasson Shmuel A SA Zamir Gideon G Razin Aharon A Cedar Howard H Shapiro A M James AM Glaser Benjamin B Shemer Ruth R Dor Yuval Y

Proceedings of the National Academy of Sciences of the United States of America 20160314 13

Minimally invasive detection of cell death could prove an invaluable resource in many physiologic and pathologic situations. Cell-free circulating DNA (cfDNA) released from dying cells is emerging as a diagnostic tool for monitoring cancer dynamics and graft failure. However, existing methods rely on differences in DNA sequences in source tissues, so that cell death cannot be identified in tissues with a normal genome. We developed a method of detecting tissue-specific cell death in humans based ...[more]

PMID: 26976580

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Project description:Many studies have demonstrated that epigenetic mechanisms are important in the regulation of gene expression during embryogenesis, gametogenesis, and other forms of tissue-specific gene regulation. We sought to explore the possible role of epigenetics, specifically DNA methylation, in the establishment and maintenance of cell type-restricted gene expression in the retina. To assess the relationship between DNA methylation status and expression level of retinal genes, bisulfite sequence analysis of the 1000 bp region around the transcription start sites (TSS) of representative rod and cone photoreceptor-specific genes and gene expression analysis were performed in the WERI and Y79 human retinoblastoma cell lines. Next, the homologous genes in mouse were bisulfite sequenced in the retina and in non-expressing tissues. Finally, bisulfite sequencing was performed on isolated photoreceptor and non-photoreceptor retinal cells isolated by laser capture microdissection. Differential methylation of rhodopsin (RHO), retinal binding protein 3 (RBP3, IRBP) cone opsin, short-wave-sensitive (OPN1SW), cone opsin, middle-wave-sensitive (OPN1MW), and cone opsin, long-wave-sensitive (OPN1LW) was found in the retinoblastoma cell lines that inversely correlated with gene expression levels. Similarly, we found tissue-specific hypomethylation of the promoter region of Rho and Rbp3 in mouse retina as compared to non-expressing tissues, and also observed hypomethylation of retinal-expressed microRNAs. The Rho and Rbp3 promoter regions were unmethylated in expressing photoreceptor cells and methylated in non-expressing, non-photoreceptor cells from the inner nuclear layer. A third regional hypomethylation pattern of photoreceptor-specific genes was seen in a subpopulation of non-expressing photoreceptors (Rho in cones from the Nrl -/- mouse and Opn1sw in rods). These results demonstrate that a number of photoreceptor-specific genes have cell-specific differential DNA methylation that correlates inversely with their expression level. Furthermore, these cell-specific patterns suggest that DNA methylation may play an important role in modulating photoreceptor gene expression in the developing mammalian retina.

Project description:Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational analysis of the DNA methylation profiles from The Cancer Genome Atlas (TCGA). Through training (n = 160) and validation set (n = 69), we developed a diagnostic prediction model with 26 markers, which yielded a sensitivity of 89.37% and a specificity of 100% for differentiating malignant disease from normal lesions [AUROC = 0.9816 (95% CI: 96.09-100%), and AUPRC = 0.9704 (95% CI: 94.54-99.46%)]. A simplified 4-marker model including cg23035715, cg16304215, cg20072171, and cg21501525 had a similar diagnostic power [AUROC = 0.9796 (95% CI: 95.56-100%), and AUPRC = 0.9220 (95% CI: 91.02-94.37%)]. We found that a single cfDNA methylation marker, cg23035715, has a high diagnostic power [AUROC = 0.9395 (95% CI: 89.72-99.27%), and AUPRC = 0.9111 (95% CI: 88.45-93.76%)], with a sensitivity of 84.90% and a specificity of 93.88%. In an independent testing dataset (n = 104), the obtained diagnostic prediction model discriminated BC patients from normal controls with high accuracy [AUROC = 0.9449 (95% CI: 90.07-98.91%), and AUPRC = 0.8640 (95% CI: 82.82-89.98%)]. We compared the diagnostic power of cfDNA methylation and mammography. Our model yielded a sensitivity of 94.79% (95% CI: 78.72-97.87%) and a specificity of 98.70% (95% CI: 86.36-100%) for differentiating malignant disease from normal lesions [AUROC = 0.9815 (95% CI: 96.75-99.55%), and AUPRC = 0.9800 (95% CI: 96.6-99.4%)], with better diagnostic power and had better diagnostic power than that of using mammography [AUROC = 0.9315 (95% CI: 89.95-96.34%), and AUPRC = 0.9490 (95% CI: 91.7-98.1%)]. In addition, hypermethylation profiling provided insights into lymph node metastasis stratifications (p < 0.05). In conclusion, we developed and tested a cfDNA methylation model for BC diagnosis with better performance than mammography.

Dataset Information

Identification of tissue-specific cell death using methylation patterns of circulating DNA.

Publications

Identification of tissue-specific cell death using methylation patterns of circulating DNA.

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