MONOD:Background: Difference between revisions
>Shicheng (Created page with "Circulating cell-free DNA methylation in plasma have been demonstrated to be powerful potential in non-invasive cancer early diagnosis. However, the genome-wide profile of DNA...") |
>Shicheng No edit summary |
||
Line 1: | Line 1: | ||
Circulating cell-free DNA methylation in plasma have been demonstrated to be powerful potential in non-invasive cancer early diagnosis. However, the genome-wide profile of DNA methylation for the free circulating DNA methylation has not been depicted in a signal base resolution. [Method] In the present study, we carried out a genome-wide survey of single-base resolution methylome across 45 plasma from cancer patients, 30 normal plasma and solid cancer tissues with RRBS, SeqCap and BSPP assays. [Result] In the discovery stage, both RRBS and SeqCap dataset identified large number classification potential biomarkers (N=1592 and 516, respectively) and high level prediction ability with Random Forest model (accuracy=100% and 98.18%, respectively). The above biomarkers were validated in the BSPP dataset and we found the methylation status of 30 derived regions in plasma could explain 93.75% cancers incidence and the specificity is 100%. What’s more, the pattern of the DNA methylation fragment transferring were depicted with paired tissue-plasma methylation dataset. We identified 1590 fragments significantly prefer-selected in the releasing process of the DNA methylation fragment from solid tissues to plasma (P<1.98*10-6, binomial test, Bonferroni correction). These fragments were located in the regions of 1190 genes. Function enrichment analysis showed these genes were significantly associated with cancer relevant biological functions, including embryonic morphogenesis, regulation of transcription, neuron differentiation, regionalization, tissue morphogenesis, transcription factor activity, sequence-specific DNA binding, transcription regulator activity. [Conclusion] Methylation haplotype loading based DNA methylation biomarker would be potential cancer diagnosis biomarker and DNA methylation fragment releasing process were regulated rather than a random event. | Circulating cell-free DNA methylation in plasma have been demonstrated to be powerful potential in non-invasive cancer early diagnosis. However, the genome-wide profile of DNA methylation for the free circulating DNA methylation has not been depicted in a signal base resolution. [Method] In the present study, we carried out a genome-wide survey of single-base resolution methylome across 45 plasma from cancer patients, 30 normal plasma and solid cancer tissues with RRBS, SeqCap and BSPP assays. [Result] In the discovery stage, both RRBS and SeqCap dataset identified large number classification potential biomarkers (N=1592 and 516, respectively) and high level prediction ability with Random Forest model (accuracy=100% and 98.18%, respectively). The above biomarkers were validated in the BSPP dataset and we found the methylation status of 30 derived regions in plasma could explain 93.75% cancers incidence and the specificity is 100%. What’s more, the pattern of the DNA methylation fragment transferring were depicted with paired tissue-plasma methylation dataset. We identified 1590 fragments significantly prefer-selected in the releasing process of the DNA methylation fragment from solid tissues to plasma (P<1.98*10-6, binomial test, Bonferroni correction). These fragments were located in the regions of 1190 genes. Function enrichment analysis showed these genes were significantly associated with cancer relevant biological functions, including embryonic morphogenesis, regulation of transcription, neuron differentiation, regionalization, tissue morphogenesis, transcription factor activity, sequence-specific DNA binding, transcription regulator activity. [Conclusion] Methylation haplotype loading based DNA methylation biomarker would be potential cancer diagnosis biomarker and DNA methylation fragment releasing process were regulated rather than a random event. | ||
==Background== | |||
DNA methylation is one of most important inherited epigenetic modification in the human genome. It is involved in most human biological and cellular, physiological, pathological changes. Current evidence shows DNA methylation could be powerful tag for cell differentiation, aging estimation, forensic identification and disease status, especially in cancer. DNA methylation can be used as the sensitive biomarker for diagnosis, prognosis surveillance and chemo-response tracking. More and more genome-wide DNA methylation profile for cancers has been completed with different strategies (1). Most of the current method is preferred to microarray or capture-based sequencing technology. However, the coverage is limited and the signal is a fuzzy evaluation of DNA methylation for the population of a specific tissue. Although capture-based DNA methylation sequencing technology, such as MBD-seq and MeDIP-seq have low cost, they cannot obtain single-based methylation status, to decrease the cost of the design. In addition, majority of these profiles are based on solid tissues rather than circulating free-cell DNA, which is considered as the most powerful media for non-invasive diagnosis. | |||
The survival time is highly dependent on the stage of the cancer in which the patient were diagnosed, especially for NSCLC, pancreatic cancer and colon cancer(2). For example, while the overall 5-year survival rates for late stage III and IV of NSCLC patients were just 5%-14% and 1% respectively, the rate could come up to 50% for the early stage of the NSCLC patients who are typically treated with surgery (3). However, early diagnosis of cancer also require another 3 prerequisites, including early biomarkers, non-invasive detection and high specificity. The methylation detection in circulating cell-free DNA do provide such platform for cancer non-invasive early diagnosis. | |||
Human peripheral blood contains low levels of DNA molecules from other tissues or cell types, such as circulating cancer stem cells or cell-free DNA (cf-DNA) from apoptotic cancer cells in cancer patients. Analysis of DNA epigenetic mutations in the circulating cell-free DNA is becoming to a prospective trend for creation of noninvasive methods for the diagnosis and treatment efficiency monitoring in cancer. In the past few year, the basic characteristics of cfDNA has been depicted. Plasma rather than serum was considered to be the perfect media to collect the cfDNA within 8 hours of the storage (4). Two main fragment components of cfDNA, 180bp and 350bp, could be found in non-white-cell contaminated plasma. The yield of cf-DNA in the plasma of cancer patients is a very low concentration which ranged from 1.0-100 ng/ml while it ranges from 1.0-10 ng/ml in healthy individuals. To detect and quantify such low abundance DNA molecules, some significant regions, hyper-methylated in the circulating DNAs derived from cancer cell while non-methylated in white blood cell (WBC), should be identified. | |||
In the present study, we carried out a comprehensive genome-wide DNA methylation analysis across 45 plasma from cancer patients, 30 normal plasma and ** solid cancer tissues with RRBS, SeqCap and umi-BSPP assays. 68 cancer and 25 normal samples were enrolled in RRBS assay. 40 cancer and 25 normal samples were enrolled in SeqCap assay. 16 cancer plasma and 16 normal plasma samples were enrolled in umi-BSPP assay. Methylation haplotype was constructed as our previous method and Methylation haplotype loading (MHL) was proposed to assess the level or the proportion of the DNA methylation. Diagnostic biomarker based on MHL were identified and validated by RRBS, SeqCap and umi-BSPP dataset. In addition, 15 solid cancer tissues and corresponding plasma samples were collected and then the methylome were detected by RRBS assay to evaluate the difference of the genome-wide DNA methylation between solid tissues and circulating cell free DNA. |
Revision as of 18:33, 10 March 2016
Circulating cell-free DNA methylation in plasma have been demonstrated to be powerful potential in non-invasive cancer early diagnosis. However, the genome-wide profile of DNA methylation for the free circulating DNA methylation has not been depicted in a signal base resolution. [Method] In the present study, we carried out a genome-wide survey of single-base resolution methylome across 45 plasma from cancer patients, 30 normal plasma and solid cancer tissues with RRBS, SeqCap and BSPP assays. [Result] In the discovery stage, both RRBS and SeqCap dataset identified large number classification potential biomarkers (N=1592 and 516, respectively) and high level prediction ability with Random Forest model (accuracy=100% and 98.18%, respectively). The above biomarkers were validated in the BSPP dataset and we found the methylation status of 30 derived regions in plasma could explain 93.75% cancers incidence and the specificity is 100%. What’s more, the pattern of the DNA methylation fragment transferring were depicted with paired tissue-plasma methylation dataset. We identified 1590 fragments significantly prefer-selected in the releasing process of the DNA methylation fragment from solid tissues to plasma (P<1.98*10-6, binomial test, Bonferroni correction). These fragments were located in the regions of 1190 genes. Function enrichment analysis showed these genes were significantly associated with cancer relevant biological functions, including embryonic morphogenesis, regulation of transcription, neuron differentiation, regionalization, tissue morphogenesis, transcription factor activity, sequence-specific DNA binding, transcription regulator activity. [Conclusion] Methylation haplotype loading based DNA methylation biomarker would be potential cancer diagnosis biomarker and DNA methylation fragment releasing process were regulated rather than a random event.
Background
DNA methylation is one of most important inherited epigenetic modification in the human genome. It is involved in most human biological and cellular, physiological, pathological changes. Current evidence shows DNA methylation could be powerful tag for cell differentiation, aging estimation, forensic identification and disease status, especially in cancer. DNA methylation can be used as the sensitive biomarker for diagnosis, prognosis surveillance and chemo-response tracking. More and more genome-wide DNA methylation profile for cancers has been completed with different strategies (1). Most of the current method is preferred to microarray or capture-based sequencing technology. However, the coverage is limited and the signal is a fuzzy evaluation of DNA methylation for the population of a specific tissue. Although capture-based DNA methylation sequencing technology, such as MBD-seq and MeDIP-seq have low cost, they cannot obtain single-based methylation status, to decrease the cost of the design. In addition, majority of these profiles are based on solid tissues rather than circulating free-cell DNA, which is considered as the most powerful media for non-invasive diagnosis.
The survival time is highly dependent on the stage of the cancer in which the patient were diagnosed, especially for NSCLC, pancreatic cancer and colon cancer(2). For example, while the overall 5-year survival rates for late stage III and IV of NSCLC patients were just 5%-14% and 1% respectively, the rate could come up to 50% for the early stage of the NSCLC patients who are typically treated with surgery (3). However, early diagnosis of cancer also require another 3 prerequisites, including early biomarkers, non-invasive detection and high specificity. The methylation detection in circulating cell-free DNA do provide such platform for cancer non-invasive early diagnosis.
Human peripheral blood contains low levels of DNA molecules from other tissues or cell types, such as circulating cancer stem cells or cell-free DNA (cf-DNA) from apoptotic cancer cells in cancer patients. Analysis of DNA epigenetic mutations in the circulating cell-free DNA is becoming to a prospective trend for creation of noninvasive methods for the diagnosis and treatment efficiency monitoring in cancer. In the past few year, the basic characteristics of cfDNA has been depicted. Plasma rather than serum was considered to be the perfect media to collect the cfDNA within 8 hours of the storage (4). Two main fragment components of cfDNA, 180bp and 350bp, could be found in non-white-cell contaminated plasma. The yield of cf-DNA in the plasma of cancer patients is a very low concentration which ranged from 1.0-100 ng/ml while it ranges from 1.0-10 ng/ml in healthy individuals. To detect and quantify such low abundance DNA molecules, some significant regions, hyper-methylated in the circulating DNAs derived from cancer cell while non-methylated in white blood cell (WBC), should be identified.
In the present study, we carried out a comprehensive genome-wide DNA methylation analysis across 45 plasma from cancer patients, 30 normal plasma and ** solid cancer tissues with RRBS, SeqCap and umi-BSPP assays. 68 cancer and 25 normal samples were enrolled in RRBS assay. 40 cancer and 25 normal samples were enrolled in SeqCap assay. 16 cancer plasma and 16 normal plasma samples were enrolled in umi-BSPP assay. Methylation haplotype was constructed as our previous method and Methylation haplotype loading (MHL) was proposed to assess the level or the proportion of the DNA methylation. Diagnostic biomarker based on MHL were identified and validated by RRBS, SeqCap and umi-BSPP dataset. In addition, 15 solid cancer tissues and corresponding plasma samples were collected and then the methylome were detected by RRBS assay to evaluate the difference of the genome-wide DNA methylation between solid tissues and circulating cell free DNA.