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Article
epiLiver a novel tumor specific, high throughput and cost-effective blood test for specific detection of liver cancer (HCC)
Moshe Szyf
mcgill university
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3881-8214
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This work is licensed under a CC BY 4.0 License. Read Full License
Robust cost effective and high-throughput tests for early detection of cancer in otherwise healthy people could potentially revolutionize public-health and the heavy personal and public burden of the morbidity and mortality from cancer. Several studies have delineated tumor specific DNA methylation profiles that could serve as biomarkers for early detection of Hepatocellular Carcinoma (HCC) as well as other cancers in liquid biopsies. Several published DNA methylation markers fail to distinguish HCC DNA from DNA from other tissues and other cancers that are potentially present in plasma. We describe a set of DNA methylation signatures in HCC that are “categorically” distinct from normal tissues and blood DNA methylation profiles. We develop a classifier combined of 4 CG sites that is sufficient to detect HCC in TCGA HCC data set at high accuracy. A single CG site at the F12 gene is sufficient to differentiate HCC samples from thousands of other blood samples, normal tissues and 31 tumors in the TCGA and Gene Expression Omnibus (GEO) data repository (n = 11,704). A “next generation sequencing”-targeted-multiplexed high-throughput assay was developed, which was used to examine in a clinical study plasma samples from HCC, chronic hepatitis B (CHB) patients and healthy controls (n = 398). The sensitivity for HCC detection was 84.5% at a specificity of 95% and AUC of 0.94. Applying this assay for routine follow up of people who are at high risk for developing HCC could have a significant impact on reducing the morbidity and mortality from HCC.
Keywords
Hepatocellular carcinoma, liquid biopsy, epigenetics, DNA methylation, early detection, cancer biomarkers, CG island, tissue specific methylation.
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This is a list of supplementary files associated with this preprint. Click to download.
- TableS1.HCCdetectmodelstatistics.xlsx
Table S1. Model statistics for “HCC-detect”.
- TableS2.CancersamplesanalyzedfromTCGA.xlsx
Table S2. List number of samples and acronyms of other cancers analyzed.
- TableS3.HCCspecmodelstatistics.xlsx
Table S3. Model statistics for “HCC-spec”.
- TableS4.xlsx
Table S4. ROCs for “HCC-detect” sum “HCC-spec” + “HCC-detect” sum scores and number of samples with methylation values larger than 0.2.
- FigureS1.jpg
Fig. S1. Differential methylation of “HCC-detect” and “HCC-spec” CGs at different stages of HCC in the Dhaka clinical study. Mean methylation and confidence intervals for the 4 CGs included in the “HCC-detect” set (cg02012576 (CHFR), cg03768777 (VASH2), cg05739190 (CCNJ), cg24804544 (GRID2IP) and “HCC-spec” cg14126493 (F12) (n for each group as indicated in Fig. 5). B. heat map depicting the methylation values for all CGs that were included in the sequenced regions for all 5 genes.
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This preprint is under consideration at a Nature Portfolio Journal. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
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Article
epiLiver a novel tumor specific, high throughput and cost-effective blood test for specific detection of liver cancer (HCC)
Moshe Szyf
mcgill university
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3881-8214
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 23 Feb, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cancer Biology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Robust cost effective and high-throughput tests for early detection of cancer in otherwise healthy people could potentially revolutionize public-health and the heavy personal and public burden of the morbidity and mortality from cancer. Several studies have delineated tumor specific DNA methylation profiles that could serve as biomarkers for early detection of Hepatocellular Carcinoma (HCC) as well as other cancers in liquid biopsies. Several published DNA methylation markers fail to distinguish HCC DNA from DNA from other tissues and other cancers that are potentially present in plasma. We describe a set of DNA methylation signatures in HCC that are “categorically” distinct from normal tissues and blood DNA methylation profiles. We develop a classifier combined of 4 CG sites that is sufficient to detect HCC in TCGA HCC data set at high accuracy. A single CG site at the F12 gene is sufficient to differentiate HCC samples from thousands of other blood samples, normal tissues and 31 tumors in the TCGA and Gene Expression Omnibus (GEO) data repository (n = 11,704). A “next generation sequencing”-targeted-multiplexed high-throughput assay was developed, which was used to examine in a clinical study plasma samples from HCC, chronic hepatitis B (CHB) patients and healthy controls (n = 398). The sensitivity for HCC detection was 84.5% at a specificity of 95% and AUC of 0.94. Applying this assay for routine follow up of people who are at high risk for developing HCC could have a significant impact on reducing the morbidity and mortality from HCC.
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