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Dogan M, Philibert R. Personalized medicine for cardiovascular diseases: how next generation epigenetic technologies can contribute? Epigenomics 2025:1-6. [PMID: 40515537 DOI: 10.1080/17501911.2025.2518917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2025] [Accepted: 06/02/2025] [Indexed: 06/16/2025] Open
Abstract
Advances in DNA methylation and artificial intelligence have led to new methods for assessing risk and diagnosing coronary heart disease (CHD), the leading cause of death. However, whether these technologies can also be harnessed to generate new pharmacotherapeutic agents or monitor the effectiveness of new or existing CHD therapies is unknown. In this perspective, we review the development of cardiac assessment technologies and the challenges that these older approaches attempted to address. We next describe Precision Epigenetic methods and describe their strengths and limitations, as well as the conceptual framework through which these tools operate. Finally, we discuss their potential application to the development and evaluation of new therapies for CHD and how Precision Epigenetic tools compare to existing testing modalities for CHD. We conclude that the future is bright for the use of Precision Epigenetic methods in cardiovascular medicine and suggest that their routine use could lead to faster, less expensive and more effective healthcare.
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Affiliation(s)
- Meeshanthini Dogan
- Cardio Diagnostics Inc, Chicago, IL, USA
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Robert Philibert
- Cardio Diagnostics Inc, Chicago, IL, USA
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
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Gao N, Li J, Yang F, Yu D, Huo Y, Liu X, Ji Z, Xing Y, Zhang X, Yuan P, Liu J, Yan J. Forensic Age Estimation From Blood Samples by Combining DNA Methylation and MicroRNA Markers Using Droplet Digital PCR. Electrophoresis 2025; 46:424-432. [PMID: 40099741 DOI: 10.1002/elps.8133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/20/2025]
Abstract
Age estimation is important in criminal investigations and forensic practice, and extensive studies have focused on age determination based on DNA methylation (DNAm) and miRNA markers. Interestingly, it has been reported that combining different types of molecular omics data helps build more accurate predictive models. However, few studies have compared the application of combined DNAm and miRNA data to predict age in the same cohort. In this study, a novel multiplex droplet digital PCR (ddPCR) system that allows for the simultaneous detection of age-associated DNAm and miRNA markers, including KLF14, miR-106b-5p, and two reference genes (C-LESS-C1 and RNU6B), was developed. Next, we examined and calculated the methylation levels of KLF14 and relative expression levels of miR-106b-5p in 132 blood samples. The collected data were used to establish age prediction models. Finally, the optimal models were evaluated using bloodstain samples. The results revealed that the random forest (RF) model had a minimum mean absolute deviation (MAD) value of 3.51 years and a maximum R2 of 0.84 for the validation sets in the combined age prediction models. However, the MAD was 5.66 years and the absolute error ranged from 3.16 to 10.54 years for bloodstain samples. Larger sample sizes and validation datasets are required to confirm these results in future studies. Overall, a stable method for the detection of KLF14, miR-106b-5p, C-LESS-C1, and RNU6B by 4-plex ddPCR was successfully established, and our study suggests that combining DNAm and miRNA data can improve the accuracy of age prediction, which has potential applications in forensic science.
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Affiliation(s)
- Niu Gao
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Junli Li
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Fenglong Yang
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Daijing Yu
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Yumei Huo
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Xiaonan Liu
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Zhimin Ji
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Yangfeng Xing
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Xiaomeng Zhang
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Piao Yuan
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Jinding Liu
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
| | - Jiangwei Yan
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Shanxi, China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, Shanxi, China
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Zhao Y, Zhang Z, Qiu JH, Li RY, Sun ZG. Catching cancer signals in the blood: Innovative pathways for early esophageal cancer diagnosis. World J Gastroenterol 2025; 31:101838. [PMID: 40093671 PMCID: PMC11886526 DOI: 10.3748/wjg.v31.i10.101838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2024] [Revised: 01/23/2025] [Accepted: 02/05/2025] [Indexed: 02/26/2025] Open
Abstract
In recent years, significant progress has been made in the application of DNA methylation for the early detection of esophageal cancer (EC). As an epigenetic modification, DNA methylation allows for noninvasive screening by detecting the methylation status of circulating tumor DNA. Studies have shown that the methylation of genes such as SHOX2, SEPTIN9, EPO, and RNF180 significantly improves diagnostic sensitivity and specificity. Currently, SEPTIN9 has been approved by the Food and Drug Administration for colorectal cancer screening, while SHOX2 and EPO show promising results in EC, and RNF180 has potential in gastrointestinal tumors. This editorial reviews the study by Liu et al, which demonstrated the potential of combining the methylation of these four genes for early EC screening. In addition to their roles in early diagnosis, DNA methylation markers are gaining attention because of their roles in predicting recurrence and in postoperative follow-up. By monitoring changes in methylation levels, these markers can provide valuable insights into treatment efficacy and long-term management. As research progresses, liquid biopsy technology is expected to become an essential tool in the precision diagnosis and treatment of EC, benefiting patients significantly.
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Affiliation(s)
- Yue Zhao
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan 250063, Shandong Province, China
| | - Zhan Zhang
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan 250063, Shandong Province, China
| | - Jian-Hao Qiu
- Department of Thoracic Surgery, The First Affiliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Jinan 250063, Shandong Province, China
| | - Rong-Yang Li
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan 250063, Shandong Province, China
| | - Zhen-Guo Sun
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan 250063, Shandong Province, China
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Zhu Q, Xie J, Mei W, Zeng C. Methylated circulating tumor DNA in hepatocellular carcinoma: A comprehensive analysis of biomarker potential and clinical implications. Cancer Treat Rev 2024; 128:102763. [PMID: 38763055 DOI: 10.1016/j.ctrv.2024.102763] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/30/2024] [Accepted: 05/15/2024] [Indexed: 05/21/2024]
Abstract
The intricate epigenetic landscape of hepatocellular carcinoma (HCC) is profoundly influenced by alterations in DNA methylation patterns. Understanding these alterations is crucial for unraveling the molecular mechanisms underlying HCC pathogenesis. Methylated circulating tumor DNA (ctDNA) presents itself as an encouraging avenue for biomarker discovery and holds substantial clinical implications in HCC management. This review comprehensively outlines the studies concerning DNA methylation in HCC and underscores the significance of methylated ctDNA within this context. Moreover, a variety of cfDNA methylation-based methodologies, such as 5hmC profiling, bisulfite-based, restriction enzyme-dependent, and enrichment-based methods, provide in-depth insights into the molecular pathology of HCC. Additionally, the integration of methylated ctDNA analysis into clinical practice represents a significant advancement in personalized HCC management. By facilitating cancer screening, prognosis assessment, and treatment response prediction, the utilization of methylated ctDNA signifies a pivotal stride toward enhancing patient care and outcomes in HCC.
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Affiliation(s)
- Qian Zhu
- Department of Gastroenterology, Shenzhen Longhua District Central Hospital, Shenzhen 518110, China
| | - Jiaqi Xie
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Wuxuan Mei
- Xianning Medical College, Hubei University of Science and Technology, Xianning 437100, China
| | - Changchun Zeng
- Department of Medical Laboratory, Shenzhen Longhua District Central Hospital, Guangdong Medical University, Shenzhen 518110, China.
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Shorey-Kendrick LE, Davis B, Gao L, Park B, Vu A, Morris CD, Breton CV, Fry R, Garcia E, Schmidt RJ, O’Shea TM, Tepper RS, McEvoy CT, Spindel ER, on behalf of program collaborators for Environmental influences on Child Health Outcomes. Development and Validation of a Novel Placental DNA Methylation Biomarker of Maternal Smoking during Pregnancy in the ECHO Program. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:67005. [PMID: 38885141 PMCID: PMC11218700 DOI: 10.1289/ehp13838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 02/27/2024] [Accepted: 05/22/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND Maternal cigarette smoking during pregnancy (MSDP) is associated with numerous adverse health outcomes in infants and children with potential lifelong consequences. Negative effects of MSDP on placental DNA methylation (DNAm), placental structure, and function are well established. OBJECTIVE Our aim was to develop biomarkers of MSDP using DNAm measured in placentas (N = 96 ), collected as part of the Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function double-blind, placebo-controlled randomized clinical trial conducted between 2012 and 2016. We also aimed to develop a digital polymerase chain reaction (PCR) assay for the top ranking cytosine-guanine dinucleotide (CpG) so that large numbers of samples can be screened for exposure at low cost. METHODS We compared the ability of four machine learning methods [logistic least absolute shrinkage and selection operator (LASSO) regression, logistic elastic net regression, random forest, and gradient boosting machine] to classify MSDP based on placental DNAm signatures. We developed separate models using the complete EPIC array dataset and on the subset of probes also found on the 450K array so that models exist for both platforms. For comparison, we developed a model using CpGs previously associated with MSDP in placenta. For each final model, we used model coefficients and normalized beta values to calculate placental smoking index (PSI) scores for each sample. Final models were validated in two external datasets: the Extremely Low Gestational Age Newborn observational study, N = 426 ; and the Rhode Island Children's Health Study, N = 237 . RESULTS Logistic LASSO regression demonstrated the highest performance in cross-validation testing with the lowest number of input CpGs. Accuracy was greatest in external datasets when using models developed for the same platform. PSI scores in smokers only (n = 72 ) were moderately correlated with maternal plasma cotinine levels. One CpG (cg27402634), with the largest coefficient in two models, was measured accurately by digital PCR compared with measurement by EPIC array (R 2 = 0.98 ). DISCUSSION To our knowledge, we have developed the first placental DNAm-based biomarkers of MSDP with broad utility to studies of prenatal disease origins. https://doi.org/10.1289/EHP13838.
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Affiliation(s)
- Lyndsey E. Shorey-Kendrick
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, USA
| | - Brett Davis
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Lina Gao
- Biostatistics Shared Resources, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Bioinformatics & Biostatistics Core, Oregon National Primate Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Byung Park
- Biostatistics Shared Resources, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Bioinformatics & Biostatistics Core, Oregon National Primate Research Center, Oregon Health & Science University, Portland, Oregon, USA
- Oregon Health & Science University–Portland State University School of Public Health, Portland, Oregon, USA
| | - Annette Vu
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
| | - Cynthia D. Morris
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
- Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Carrie V. Breton
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Rebecca Fry
- Department of Environmental Sciences and Engineering, UNC Gillings School of Public Health, Chapel Hill, North Carolina, USA
| | - Erika Garcia
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Rebecca J. Schmidt
- Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, California, USA
- MIND Institute, School of Medicine, University of California Davis, Davis, California, USA
| | - T. Michael O’Shea
- Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Robert S. Tepper
- Department of Pediatrics, Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Cindy T. McEvoy
- Department of Pediatrics, Oregon Health & Science University, Portland, Oregon, USA
| | - Eliot R. Spindel
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, USA
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Dias HC, Manco L. Predicting age from blood by droplet digital PCR using a set of three DNA methylation markers. Forensic Sci Int 2024; 356:111950. [PMID: 38301433 DOI: 10.1016/j.forsciint.2024.111950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 01/02/2024] [Accepted: 01/25/2024] [Indexed: 02/03/2024]
Abstract
Evaluation of DNA methylation (DNAm) patterns is a promising tool for age estimation. The duplex droplet digital PCR (ddPCR) method has been recently investigated for DNAm evaluation, revealing to be a potential methodology for DNAm evaluation and molecular age estimation. In this study, we evaluated DNAm levels of CpGs located at the three age-associated genes ELOVL2, FHL2 and PDE4C using ddPCR to develop an age prediction model. Blood-derived DNA samples from 58 healthy individuals (42 women and 16 men; aged 1-93 years old) were submitted to bisulfite conversion followed by ddPCR using dual-labeled probes targeting methylated and unmethylated DNA sequences. Simple linear regression statistics revealed a strong correlation between DNAm levels and chronological age for FHL2 (R = 0.948; P = 1.472 × 10-29) and PDE4C (R = 0.819; P = 3.917 × 10-15), addressing only one CpG for each gene. For the ELOVL2 gene, evaluating five CpG sites in simultaneous, revealed a strong age correlation (R = 0.887; P = 2.099 × 10-20) in a simple linear regression statistics and very strong age correlation (R = 0.926; P = 2.202 × 10-25) when using quadratic regression statistics. The multivariable regression analysis, using methylation information captured on ELOVL2 (squared), FHL2 and PDE4C genes, revealed a very strong age correlation (R = 0.970; P = 5.356 ×10-33), explaining 93.7 % of age variance, displaying a mean absolute deviation (MAD) between chronological and predicted age of 4.657 years (RMSE = 6.044). We postulate that the ddPCR method should be further investigated for DNAm-based age prediction, because it is a relatively simple and an accurate method that can be routinely used in forensic laboratories for testing a few numbers of markers.
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Affiliation(s)
- Helena Correia Dias
- Research Centre for Anthropology and Health (CIAS), University of Coimbra, 3000-456 Coimbra, Portugal
| | - Licínio Manco
- Research Centre for Anthropology and Health (CIAS), University of Coimbra, 3000-456 Coimbra, Portugal; Department of Life Sciences, University of Coimbra, 3000-456 Coimbra, Portugal.
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Cardoso GC, Ganzella FADO, Miniskiskosky G, da Cunha RS, Ramos EADS. Digital methylation-specific PCR: New applications for liquid biopsy. Biomol Concepts 2024; 15:bmc-2022-0041. [PMID: 38345545 DOI: 10.1515/bmc-2022-0041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 01/23/2024] [Indexed: 02/15/2024] Open
Abstract
Epigenetic analysis is a fundamental part of understanding pathophysiological processes with potential applications in diagnosis, prognosis, and assessment of disease susceptibility. Epigenetic changes have been widely studied in chronic obstructive pulmonary disease (COPD), but currently, there is no molecular marker used to improve the treatment of patients. Furthermore, this progressive disease is a risk factor for the development of more severe COVID-19. Methylation-specific polymerase chain reaction (MSP-PCR) plays an important role in the analysis of DNA methylation profiles, and it is one of the most widely used techniques. In this context, the combination of MSP-PCR with emerging PCR technologies, such as digital PCR (dPCR), results in more accurate analyses of the DNA methylation profile of the genes under study. In this study, we propose the application of the MSP-dPCR technique to evaluate the methylation profile of the ADAM33 gene from saliva samples and lung tissue biopsies of patients with COPD and COVID-19. MSP-dPCR generated a measurable prediction of gene methylation rate, with the potential application of this combined technology for diagnostic and prognostic purposes. It has also proven to be a powerful tool for liquid biopsy applications.
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Affiliation(s)
- Gabriela Casani Cardoso
- Human Pathology Experimental Laboratory, Basic Pathology Department, Federal University of Paraná, Curitiba, 81531-980, Paraná, Brazil
- Post-Graduate Program of Microbiology, Parasitology and Pathology, Federal University of Paraná, Curitiba, 81531-980, Paraná, Brazil
| | | | - Guilherme Miniskiskosky
- Human Pathology Experimental Laboratory, Basic Pathology Department, Federal University of Paraná, Curitiba, 81531-980, Paraná, Brazil
| | - Regiane Stafim da Cunha
- Post-Graduate Program of Microbiology, Parasitology and Pathology, Federal University of Paraná, Curitiba, 81531-980, Paraná, Brazil
| | - Edneia Amancio de Souza Ramos
- Human Pathology Experimental Laboratory, Basic Pathology Department, Federal University of Paraná, Curitiba, 81531-980, Paraná, Brazil
- Post-Graduate Program of Microbiology, Parasitology and Pathology, Federal University of Paraná, Curitiba, 81531-980, Paraná, Brazil
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Yu M, Carter KT, Baker KK, Redman MW, Wang T, Vickers K, Li CI, Cohen SA, Krane M, Ose J, Gigic B, Figueiredo JC, Toriola AT, Siegel EM, Shibata D, Schneider M, Ulrich CM, Dzubinski LA, Schoen RE, Grady WM. Elevated EVL Methylation Level in the Normal Colon Mucosa Is a Potential Risk Biomarker for Developing Recurrent Adenomas. Cancer Epidemiol Biomarkers Prev 2023; 32:1146-1152. [PMID: 37294695 PMCID: PMC10529338 DOI: 10.1158/1055-9965.epi-22-1020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 04/11/2023] [Accepted: 06/07/2023] [Indexed: 06/11/2023] Open
Abstract
BACKGROUND Individuals with adenomatous colorectal polyps undergo repeated colonoscopy surveillance to identify and remove metachronous adenomas. However, many patients with adenomas do not develop recurrent adenomas. Better methods to evaluate who benefits from increased surveillance are needed. We evaluated the use of altered EVL methylation as a potential biomarker for risk of recurrent adenomas. METHODS Patients with ≥1 colonoscopy had EVL methylation (mEVL) measured with an ultra-accurate methylation-specific droplet digital PCR assay on normal colon mucosa. The association between EVL methylation levels and adenoma or colorectal cancer was evaluated using three case/control definitions in three models: unadjusted (model 1), adjusting for baseline characteristics (model 2), and an adjusted model excluding patients with colorectal cancer at baseline (model 3). RESULTS Between 2001 and 2020, 136 patients were included; 74 healthy patients and 62 patients with a history of colorectal cancer. Older age, never smoking, and baseline colorectal cancer were associated with higher levels of mEVL (P ≤ 0.05). Each log base 10 difference in mEVL was associated with an increased risk of adenoma(s) or cancer at/after baseline for model 1 [OR, 2.64; 95% confidence interval (CI), 1.09-6.36], and adenoma(s) or cancer after baseline for models 1 (OR, 2.01; 95% CI, 1.04-3.90) and model 2 (OR, 3.17; 95% CI, 1.30-7.72). CONCLUSIONS Our results suggest that EVL methylation level detected in the normal colon mucosa has the potential to be a biomarker for monitoring the risk for recurrent adenomas. IMPACT These findings support the potential utility of EVL methylation for improving the accuracy for assigning risk for recurrent colorectal adenomas and cancer.
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Affiliation(s)
- Ming Yu
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - Kelly T Carter
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - Kelsey K Baker
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - Mary W. Redman
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - Ting Wang
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - Kathy Vickers
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - Christopher I. Li
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA
- Department of Medicine, University of Washington School of Medicine, Seattle, WA
| | - Stacey A. Cohen
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA
- Department of Medicine, University of Washington School of Medicine, Seattle, WA
| | - Mukta Krane
- Department of Medicine, University of Washington School of Medicine, Seattle, WA
| | - Jennifer Ose
- University of Utah, Salt Lake City, UT
- Huntsman Cancer Institute, Salt Lake City, UT
| | | | - Jane C Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Center, Cedars-Sinai Medical Center, Los Angeles, CA
| | | | - Erin M Siegel
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL
| | - David Shibata
- University of Tennessee Health Science Center, Memphis, TN
| | | | - Cornelia M. Ulrich
- University of Utah, Salt Lake City, UT
- Huntsman Cancer Institute, Salt Lake City, UT
| | - Lynda Ann Dzubinski
- Department of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, PA
| | - Robert E Schoen
- Department of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, PA
| | - William M. Grady
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA
- Department of Medicine, University of Washington School of Medicine, Seattle, WA
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9
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Joo JE, Mahmood K, Walker R, Georgeson P, Candiloro I, Clendenning M, Como J, Joseland S, Preston S, Graversen L, Wilding M, Field M, Lemon M, Wakeling J, Marfan H, Susman R, Isbister J, Edwards E, Bowman M, Kirk J, Ip E, McKay L, Antill Y, Hopper JL, Boussioutas A, Macrae FA, Dobrovic A, Jenkins MA, Rosty C, Winship IM, Buchanan DD. Identifying primary and secondary MLH1 epimutation carriers displaying low-level constitutional MLH1 methylation using droplet digital PCR and genome-wide DNA methylation profiling of colorectal cancers. Clin Epigenetics 2023; 15:95. [PMID: 37270516 PMCID: PMC10239107 DOI: 10.1186/s13148-023-01511-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 05/24/2023] [Indexed: 06/05/2023] Open
Abstract
BACKGROUND MLH1 epimutation is characterised by constitutional monoallelic MLH1 promoter hypermethylation, which can cause colorectal cancer (CRC). Tumour molecular profiles of MLH1 epimutation CRCs were used to classify germline MLH1 promoter variants of uncertain significance and MLH1 methylated early-onset CRCs (EOCRCs). Genome-wide DNA methylation and somatic mutational profiles of tumours from two germline MLH1: c.-11C > T and one MLH1: c.-[28A > G; 7C > T] carriers and three MLH1 methylated EOCRCs (< 45 years) were compared with 38 reference CRCs. Methylation-sensitive droplet digital PCR (ddPCR) was used to detect mosaic MLH1 methylation in blood, normal mucosa and buccal DNA. RESULTS Genome-wide methylation-based Consensus Clustering identified four clusters where the tumour methylation profiles of germline MLH1: c.-11C > T carriers and MLH1 methylated EOCRCs clustered with the constitutional MLH1 epimutation CRCs but not with the sporadic MLH1 methylated CRCs. Furthermore, monoallelic MLH1 methylation and APC promoter hypermethylation in tumour were observed in both MLH1 epimutation and germline MLH1: c.-11C > T carriers and MLH1 methylated EOCRCs. Mosaic constitutional MLH1 methylation in MLH1: c.-11C > T carriers and 1 of 3 MLH1 methylated EOCRCs was identified by methylation-sensitive ddPCR. CONCLUSIONS Mosaic MLH1 epimutation underlies the CRC aetiology in MLH1: c.-11C > T germline carriers and a subset of MLH1 methylated EOCRCs. Tumour profiling and ultra-sensitive ddPCR methylation testing can be used to identify mosaic MLH1 epimutation carriers.
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Affiliation(s)
- Jihoon E Joo
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia.
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia.
| | - Khalid Mahmood
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia
- Melbourne Bioinformatics, The University of Melbourne, Melbourne, VIC, Australia
| | - Romy Walker
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia
| | - Peter Georgeson
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia
| | - Ida Candiloro
- Beacon Biomarkers Lab, Department of Surgery, Austin Health, University of Melbourne, Heidelberg, VIC, Australia
| | - Mark Clendenning
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia
| | - Julia Como
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia
| | - Sharelle Joseland
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia
| | - Susan Preston
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia
| | - Lise Graversen
- Department of Clinical Genetics, Aarhus University Hospital, Aarhus, Denmark
| | - Mathilda Wilding
- Department of Clinical Genetics, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Michael Field
- Department of Clinical Genetics, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Michelle Lemon
- Genetic Health Queensland, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
| | - Janette Wakeling
- Genetic Health Queensland, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
- Tasman Health Care, Southport, QLD, Australia
| | - Helen Marfan
- Genetic Health Queensland, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
| | - Rachel Susman
- Genetic Health Queensland, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
| | - Joanne Isbister
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Melbourne, VIC, Australia
| | - Emma Edwards
- Familial Cancer Service, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, NSW, 2145, Australia
| | - Michelle Bowman
- Familial Cancer Service, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, NSW, 2145, Australia
| | - Judy Kirk
- Familial Cancer Service, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney, NSW, 2145, Australia
| | - Emilia Ip
- Department of Cancer Genetics, Liverpool Hospital, Liverpool, NSW, Australia
| | - Lynne McKay
- The Cabrini Family Cancer Clinic, Cabrini Health, Malvern, VIC, Australia
| | - Yoland Antill
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Melbourne, VIC, Australia
- The Cabrini Family Cancer Clinic, Cabrini Health, Malvern, VIC, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, VIC, Australia
| | - Alex Boussioutas
- Department of Gastroenterology, The Alfred Hospital, Melbourne, Parkville, VIC, 3010, Australia
- Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia
| | - Finlay A Macrae
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Melbourne, VIC, Australia
- Colorectal Medicine and Genetics, The Royal Melbourne Hospital, Parkville, VIC, Australia
- Department of Medicine, The University of Melbourne, Parkville, Australia
| | - Alexander Dobrovic
- Beacon Biomarkers Lab, Department of Surgery, Austin Health, University of Melbourne, Heidelberg, VIC, Australia
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, VIC, Australia
| | - Christophe Rosty
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia
- Envoi Specialist Pathologists, Brisbane, Australia
- University of Queensland, Brisbane, Australia
| | - Ingrid M Winship
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Melbourne, VIC, Australia
- Department of Medicine, The University of Melbourne, Parkville, Australia
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Victorian Comprehensive Cancer Centre, The University of Melbourne, 305 Grattan Street, Parkville, VIC, 3000, Australia
- Victorian Comprehensive Cancer Centre, University of Melbourne Centre for Cancer Research, Parkville, VIC, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Melbourne, VIC, Australia
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10
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Baltrušis P, Höglund J. Digital PCR: modern solution to parasite diagnostics and population trait genetics. Parasit Vectors 2023; 16:143. [PMID: 37098569 PMCID: PMC10131454 DOI: 10.1186/s13071-023-05756-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/23/2023] [Indexed: 04/27/2023] Open
Abstract
The use of polymerase chain reaction (PCR)-based diagnostic approaches has steadily increased in the field of parasitology in recent decades. The most recent large-scale technological modification of the PCR formula, also known as third-generation PCR, came in the form of digital PCR (dPCR). Currently, the most common form of dPCR on the market is digital droplet PCR (ddPCR). Unlike quantitative real-time PCR (qPCR), the digital format allows for highly sensitive, absolute quantification of nucleic acid targets and does not require external standards to be included in the developed assays. Dividing each sample into thousands of compartments and using statistical models also eliminates the need for technical replicates. With unprecedented sensitivity and enforcement of binary endpoint reactions, ddPCR not only allows the use of tiny sample volumes (especially important when working with limited amounts of DNA) but also minimises the impact of variations in amplification efficiency and the presence of inhibitors. As ddPCR is characterised by excellent features such as high throughput, sensitivity and robust quantification, it is widely used as a diagnostic tool in clinical microbiology. Due to recent advances, both the theoretical background and the practical, current applications related to the quantification of nucleic acids of eukaryotic parasites need to be updated. In this review, we present the basics of this technology (particularly useful for new users) and consolidate recent advances in the field with a focus on applications to the study of helminths and protozoan parasites.
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Affiliation(s)
- Paulius Baltrušis
- Department of Biomedical Sciences and Veterinary Public Health, Section for Parasitology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Johan Höglund
- Department of Biomedical Sciences and Veterinary Public Health, Section for Parasitology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
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11
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Dahl E, Villwock S, Habenberger P, Choidas A, Rose M, Klebl BM. White Paper: Mimetics of Class 2 Tumor Suppressor Proteins as Novel Drug Candidates for Personalized Cancer Therapy. Cancers (Basel) 2022; 14:cancers14184386. [PMID: 36139547 PMCID: PMC9496810 DOI: 10.3390/cancers14184386] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/01/2022] [Accepted: 09/07/2022] [Indexed: 11/21/2022] Open
Abstract
Simple Summary A concept is presented for a new therapeutic approach, still in its early stages, which focuses on the phenotypic mimicry (“mimesis”) of proteins encoded by highly disease-relevant class 2 tumor suppressor genes that are silenced by DNA promoter methylation. Proteins derived from tumor suppressor genes are usually considered control systems of cells against oncogenic properties. Thus they represent the brakes in the “car-of-life.” Restoring this “brake function” in tumors by administering mimetic drugs may have a significant therapeutic effect. The proposed approach could thus open up a new, hitherto unexploited area of research for the development of anticancer drugs for difficult-to-treat cancers. Abstract The aim of our proposed concept is to find new target structures for combating cancers with unmet medical needs. This, unfortunately, still applies to the majority of the clinically most relevant tumor entities such as, for example, liver cancer, pancreatic cancer, and many others. Current target structures almost all belong to the class of oncogenic proteins caused by tumor-specific genetic alterations, such as activating mutations, gene fusions, or gene amplifications, often referred to as cancer “driver alterations” or just “drivers.” However, restoring the lost function of tumor suppressor genes (TSGs) could also be a valid approach to treating cancer. TSG-derived proteins are usually considered as control systems of cells against oncogenic properties; thus, they represent the brakes in the “car-of-life.” Restoring these tumor-defective brakes by gene therapy has not been successful so far, with a few exceptions. It can be assumed that most TSGs are not being inactivated by genetic alteration (class 1 TSGs) but rather by epigenetic silencing (class 2 TSGs or short “C2TSGs”). Reactivation of C2TSGs in cancer therapy is being addressed by the use of DNA demethylating agents and histone deacetylase inhibitors which act on the whole cancer cell genome. These epigenetic therapies have neither been particularly successful, probably because they are “shotgun” approaches that, although acting on C2TSGs, may also reactivate epigenetically silenced oncogenic sequences in the genome. Thus, new strategies are needed to exploit the therapeutic potential of C2TSGs, which have also been named DNA methylation cancer driver genes or “DNAme drivers” recently. Here we present a concept for a new translational and therapeutic approach that focuses on the phenotypic imitation (“mimesis”) of proteins encoded by highly disease-relevant C2TSGs/DNAme drivers. Molecular knowledge on C2TSGs is used in two complementary approaches having the translational concept of defining mimetic drugs in common: First, a concept is presented how truncated and/or genetically engineered C2TSG proteins, consisting solely of domains with defined tumor suppressive function can be developed as biologicals. Second, a method is described for identifying small molecules that can mimic the effect of the C2TSG protein lost in the cancer cell. Both approaches should open up a new, previously untapped discovery space for anticancer drugs.
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Affiliation(s)
- Edgar Dahl
- Institute of Pathology, Medical Faculty, RWTH Aachen University, D-52074 Aachen, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), D-52074 Aachen, Germany
- Correspondence:
| | - Sophia Villwock
- Institute of Pathology, Medical Faculty, RWTH Aachen University, D-52074 Aachen, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), D-52074 Aachen, Germany
| | - Peter Habenberger
- Lead Discovery Center GmbH (LDC), Otto-Hahn-Straße 15, D-44227 Dortmund, Germany
| | - Axel Choidas
- Lead Discovery Center GmbH (LDC), Otto-Hahn-Straße 15, D-44227 Dortmund, Germany
| | - Michael Rose
- Institute of Pathology, Medical Faculty, RWTH Aachen University, D-52074 Aachen, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), D-52074 Aachen, Germany
| | - Bert M. Klebl
- Lead Discovery Center GmbH (LDC), Otto-Hahn-Straße 15, D-44227 Dortmund, Germany
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Yu M, Moinova HR, Willbanks A, Canon VK, Wang T, Carter K, Kaz A, Reddi D, Inadomi J, Luebeck G, Iyer PG, Canto MI, Wang JS, Shaheen NJ, Thota PN, Willis JE, LaFramboise T, Chak A, Markowitz SD, Grady WM. Novel DNA Methylation Biomarker Panel for Detection of Esophageal Adenocarcinoma and High-Grade Dysplasia. Clin Cancer Res 2022; 28:3761-3769. [PMID: 35705525 PMCID: PMC9444948 DOI: 10.1158/1078-0432.ccr-22-0445] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/10/2022] [Accepted: 06/13/2022] [Indexed: 11/16/2022]
Abstract
PURPOSE Current endoscopy-based screening and surveillance programs have not been proven effective at decreasing esophageal adenocarcinoma (EAC) mortality, creating an unmet need for effective molecular tests for early detection of this highly lethal cancer. We conducted a genome-wide methylation screen to identify novel methylation markers that distinguish EAC and high-grade dysplasia (HGD) from normal squamous epithelium (SQ) or nondysplastic Barrett's esophagus (NDBE). EXPERIMENTAL DESIGN DNA methylation profiling of samples from SQ, NDBE, HGD, and EAC was performed using HM450 methylation arrays (Illumina) and reduced-representation bisulfate sequencing. Ultrasensitive methylation-specific droplet digital PCR and next-generation sequencing (NGS)-based bisulfite-sequencing assays were developed to detect the methylation level of candidate CpGs in independent esophageal biopsy and endoscopic brushing samples. RESULTS Five candidate methylation markers were significantly hypermethylated in HGD/EAC samples compared with SQ or NDBE (P < 0.01) in both esophageal biopsy and endoscopic brushing samples. In an independent set of brushing samples used to construct biomarker panels, a four-marker panel (model 1) demonstrated sensitivity of 85.0% and 90.8% for HGD and EACs respectively, with 84.2% and 97.9% specificity for NDBE and SQ respectively. In a validation set of brushing samples, the panel achieved sensitivity of 80% and 82.5% for HGD and EAC respectively, at specificity of 67.6% and 96.3% for NDBE and SQ samples. CONCLUSIONS A novel DNA methylation marker panel differentiates HGD/EAC from SQ/NDBE. DNA-methylation-based molecular assays hold promise for the detection of HGD/EAC using esophageal brushing samples.
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Affiliation(s)
- Ming Yu
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Helen R. Moinova
- Department of Medicine, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Amber Willbanks
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Victoria K. Canon
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ting Wang
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Kelly Carter
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Andrew Kaz
- Gastroenterology Section, VA Puget Sound Health Care System, WA, USA,Division of Gastroenterology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
| | - Deepti Reddi
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA
| | - John Inadomi
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA
| | - Georg Luebeck
- Public Heath Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Prasad G. Iyer
- Barrett’s Esophagus Unit, Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
| | - Marcia I. Canto
- Division of Gastroenterology and Hepatology, Department of Medicine, The Johns Hopkins Medical Institutions, Baltimore, MD
| | - Jean S. Wang
- Division of Gastroenterology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
| | - Nicholas J. Shaheen
- Center for Esophageal Diseases and Swallowing, Division of Gastroenterology and Hepatology, University of North Carolina, Chapel Hill, NC
| | | | - Joseph E. Willis
- Department of Pathology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Thomas LaFramboise
- Department of Genetics and Genome Sciences, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH, USA,Case Comprehensive Cancer Center, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Amitabh Chak
- Gastroenterology Division, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Sanford D. Markowitz
- Seidman Cancer Center, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - William M. Grady
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA,Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA
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Li J, Li H, Run ZC, Wang ZL, Jiang T, An Y, Li Z. RASSF1A methylation as a biomarker for detection of colorectal cancer and hepatocellular carcinoma. World J Gastrointest Oncol 2022; 14:1574-1584. [PMID: 36160746 PMCID: PMC9412931 DOI: 10.4251/wjgo.v14.i8.1574] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 07/02/2022] [Accepted: 07/22/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Studies have validated the potential of methylated cell-free DNA as a biomarker in various tumors, and methylated DNA in plasma may be a potential biomarker for cancer.
AIM To evaluate the diagnostic value of RASSF1A methylation in plasma for colorectal cancer (CRC) and hepatocellular carcinoma (HCC).
METHODS A total of 92 CRC patients, 67 colorectal polyp (CRP) patients, 63 HCC patients, and 66 liver cirrhosis (LC) patients were enrolled. The plasma DNA was subjected to DNA extraction, double-strand DNA concentration determination, bisulfite conversion, purification, single-strand DNA concentration determination, and digital polymerase chain reaction (PCR) detection. The methylation rate was calculated. The diagnostic value was evaluated by the area under the curve (AUC).
RESULTS The age and sex in the CRC and CRP groups and the HCC and LC groups were also matched. The DNA methylation rate of RASSF1A in plasma in the CRC group was 2.87 ± 1.80, and that in the CRP group was 1.50 ± 0.64. DNA methylation of RASSF1A in plasma showed a significant difference between the CRC and CRP groups. The AUC of RASSF1A methylation for discriminating the CRC and CRP groups was 0.82 (0.76-0.88). The AUCs of T1, T2, T3 and T4 CRC and CRP were 0.83 (0.72-0.95), 0.87 (0.78-0.95), 0.86 (0.77-0.95), and 0.75 (0.64-0.85), respectively. The DNA methylation rate of RASSF1A in plasma in the HCC group was 4.45 ± 2.93, and that in the LC group was 2.46 ± 2.07. DNA methylation of RASSF1A in plasma for the HCC and LC groups showed a significant difference. The AUC of RASSF1A methylation for discriminating the HCC and LC groups was 0.70 (0.60-0.79). The AUCs of T1, T2, T3 and T4 HCC and LC were 0.80 (0.61, 1.00), 0.74 (0.59-0.88), 0.60 (0.42-0.79), and 0.68 (0.53-0.82), respectively.
CONCLUSION RASSF1A methylation in plasma detected by digital PCR may be a potential biomarker for CRC and HCC.
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Affiliation(s)
- Jian Li
- Department of General Surgery, Affiliated Tumor Hospital of Zhengzhou University, Henan Tumor Hospital, Zhengzhou 450000, Henan Province, China
| | - Huan Li
- Department of Gastroenterology, Sixth Medical Center of Chinese PLA General Hospital, Beijing 100048, China
| | - Zeng-Ci Run
- Department of General Surgery, Affiliated Tumor Hospital of Zhengzhou University, Henan Tumor Hospital, Zhengzhou 450000, Henan Province, China
| | - Zhen-Lei Wang
- Department of General Surgery, Affiliated Tumor Hospital of Zhengzhou University, Henan Tumor Hospital, Zhengzhou 450000, Henan Province, China
| | - Tao Jiang
- Medicine Innovation Research Division of Chinese PLA General Hospital, Beijing 100853, China
| | - Yang An
- Faculty of Hepato-Pancreato-Biliary Surgery, Sixth Medical Center of Chinese PLA General Hospital, Beijing 100048, China
| | - Zhi Li
- Department of General Surgery, Affiliated Tumor Hospital of Zhengzhou University, Henan Tumor Hospital, Zhengzhou 450000, Henan Province, China
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Galimberti S, Balducci S, Guerrini F, Del Re M, Cacciola R. Digital Droplet PCR in Hematologic Malignancies: A New Useful Molecular Tool. Diagnostics (Basel) 2022; 12:1305. [PMID: 35741115 PMCID: PMC9221914 DOI: 10.3390/diagnostics12061305] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 05/21/2022] [Accepted: 05/22/2022] [Indexed: 01/27/2023] Open
Abstract
Digital droplet PCR (ddPCR) is a recent version of quantitative PCR (QT-PCR), useful for measuring gene expression, doing clonality assays and detecting hot spot mutations. In respect of QT-PCR, ddPCR is more sensitive, does not need any reference curve and can quantify one quarter of samples already defined as "positive but not quantifiable". In the IgH and TCR clonality assessment, ddPCR recapitulates the allele-specific oligonucleotide PCR (ASO-PCR), being not adapt for detecting clonal evolution, that, on the contrary, does not represent a pitfall for the next generation sequencing (NGS) technique. Differently from NGS, ddPCR is not able to sequence the whole gene, but it is useful, cheaper, and less time-consuming when hot spot mutations are the targets, such as occurs with IDH1, IDH2, NPM1 in acute leukemias or T315I mutation in Philadelphia-positive leukemias or JAK2 in chronic myeloproliferative neoplasms. Further versions of ddPCR, that combine different primers/probes fluorescences and concentrations, allow measuring up to four targets in the same PCR reaction, sparing material, time, and money. ddPCR is also useful for quantitating BCR-ABL1 fusion gene, WT1 expression, donor chimerism, and minimal residual disease, so helping physicians to realize that "patient-tailored therapy" that is the aim of the modern hematology.
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Affiliation(s)
- Sara Galimberti
- Department of Clinical and Experimental Medicine, Section of Hematology, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.B.); (F.G.); (M.D.R.)
| | - Serena Balducci
- Department of Clinical and Experimental Medicine, Section of Hematology, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.B.); (F.G.); (M.D.R.)
| | - Francesca Guerrini
- Department of Clinical and Experimental Medicine, Section of Hematology, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.B.); (F.G.); (M.D.R.)
| | - Marzia Del Re
- Department of Clinical and Experimental Medicine, Section of Hematology, University of Pisa, 56126 Pisa, Italy; (S.G.); (S.B.); (F.G.); (M.D.R.)
| | - Rossella Cacciola
- Department of Clinical and Experimental Medicine, Section of Hemostasis, University of Catania, 95123 Catania, Italy
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Abdallah R, Zhao S, Garinet S, Hormigos K, Le Corre D, Cros J, Perez Toralla K, Bats AS, Augustin J, Bachet JB, Taly V, Blons H, Taieb J, Laurent-Puig P. BRCA1 and RAD51C promotor methylation in human resectable pancreatic adenocarcinoma. Clin Res Hepatol Gastroenterol 2022; 46:101880. [PMID: 35151910 DOI: 10.1016/j.clinre.2022.101880] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 01/23/2022] [Accepted: 02/04/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND Homozygous Recombination Deficiency (HRD) is associated with sensitivity to PARP-inhibitors (PARPi) in different cancer types. In pancreatic adenocarcinoma (PA) the main cause of HRD is BRCA1/2 germline mutation and patients with mutations in BRCA1/2 may benefit from PARPi. Recently other mechanisms leading to HRD were described in different cancer types, including gene mutations and epigenetic changes such as promoter hypermethylation. In PA, BRCA1 promoter hypermethylation, a known mechanism of gene silencing, was recently described. However, results are discordant between North American studies (0.7% of PA) and Asian ones (up to 60% of PA) and the association with HRD is not clear. METHODS Here, we developed 2 quantifications methods to explore BRCA1 and RAD51C promoter methylation in a series of 121 Formalin Fixed-Paraffin-Embedded (FFPE) specimens from resected PA without neoadjuvant treatment. The methylation-specific PCR was done with 2 different methods after DNA bisulfite conversion: a digital droplet PCR, and a PCR followed by capillary electrophoresis, to score the methylated / non methylated ratios in tumor samples. Methods were validated for specificity and sensibility using 100, 20, 10, 5 and 0% methylated commercial DNA for fragment analysis with a detection cutoff of 5-10%. Limit of blank was defined as 5 dropplets/20µL for RAD51C and 1 dropplet/20µL for BRCA1 for ddPCR. Samples were reviewed by a pathologist, macrodissected before DNA extraction to obtain 50-60% of tumoral cells. DNAs were treated for bisulfite conversion and analyzed using both methods in parallel to known positive and negative controls in each run. RESULTS AND CONCLUSION No methylation at BRCA1 or RAD51C was found in this series of PA suggesting that HRD gene promoter methylation is a rare event in European patients.
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Affiliation(s)
- Raëf Abdallah
- Department of Hepatogastroenterology and GI Oncology, Georges Pompidou European Hospital, Assistance Publique-Hôpitaux de Paris, 75015 Paris, Ile-de-France, France; INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France.
| | - Shulin Zhao
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France; Sorbonne University, Department of Hepatogastroenterology and GI Oncology, La Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, 75013 Paris, Ile-de-France, France
| | - Simon Garinet
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France; Department of Biochemistry, Unit of Pharmacogenetics and Molecular Oncology, Georges Pompidou European Hospital, Assistance Publique-Hôpitaux de Paris, 75015 Paris, France
| | - Katia Hormigos
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France
| | - Delphine Le Corre
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France
| | - Jérôme Cros
- Department of Pathology, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, 92110 Clichy, Ile-de-France, France
| | - Karla Perez Toralla
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France
| | - Anne Sophie Bats
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France
| | - Jérémy Augustin
- Department of Pathology, La Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, 75013 Paris, Ile-de-France, France
| | - Jean-Baptiste Bachet
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France; Sorbonne University, Department of Hepatogastroenterology and GI Oncology, La Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, 75013 Paris, Ile-de-France, France
| | - Valérie Taly
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France
| | - Hélène Blons
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France; Department of Biochemistry, Unit of Pharmacogenetics and Molecular Oncology, Georges Pompidou European Hospital, Assistance Publique-Hôpitaux de Paris, 75015 Paris, France
| | - Julien Taieb
- Department of Hepatogastroenterology and GI Oncology, Georges Pompidou European Hospital, Assistance Publique-Hôpitaux de Paris, 75015 Paris, Ile-de-France, France; INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France
| | - Pierre Laurent-Puig
- INSERM UMRS-1138, Centre des Cordeliers, University of Paris, 75006 Paris, Ile-de-France, France
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Manco L, Dias HC. DNA methylation analysis of ELOVL2 gene using droplet digital PCR for age estimation purposes. Forensic Sci Int 2022; 333:111206. [DOI: 10.1016/j.forsciint.2022.111206] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/20/2022] [Accepted: 01/28/2022] [Indexed: 11/16/2022]
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Tost J. Current and Emerging Technologies for the Analysis of the Genome-Wide and Locus-Specific DNA Methylation Patterns. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1389:395-469. [DOI: 10.1007/978-3-031-11454-0_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Rykov SV, Filippova EA, Loginov VI, Braga EA. Gene Methylation in Circulating Cell-Free DNA from the Blood Plasma as Prognostic and Predictive Factor in Breast Cancer. RUSS J GENET+ 2021. [DOI: 10.1134/s1022795421110120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Ho Lee M, Hee Hwang J, Min Seong K, Jin Ahn J, Jun Kim S, Yong Hwang S, Lim SK. Application of droplet digital PCR method for DNA methylation-based age prediction from saliva. Leg Med (Tokyo) 2021; 54:101992. [PMID: 34814096 DOI: 10.1016/j.legalmed.2021.101992] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 10/12/2021] [Accepted: 11/11/2021] [Indexed: 10/19/2022]
Abstract
The recent studies reported that DNA methylation markers show changes with age, and expected that the DNA methylation markers can be effectively used for estimation of age in forensic genetics. In this study, we applied droplet digital PCR (ddPCR) method to investigate the DNA methylation pattern in the CpG sites, and we constructed an age prediction model based on the ddPCR method. The ddPCR is capable of highly sensitive quantitation of nucleic acid and detection of sequence variations in gene by separating the sample into large number of partitions and clonally amplifying nucleic acids in each partition. We extracted DNA from saliva samples collected from several age groups. The DNA was bisulfite converted and subjected to ddPCR using specifically designed primers and probes. The methylation ratio of each sample was calculated and correlation between the methylation ratio and the chronological age was analyzed. In the results, methylated DNA ratio at the 4 CpG sites (cg14361627, cg14361627, cg08928145 and cg07547549) showed strong correlation with chronological age. Percent-methylation values at 4 CpG markers and chronological ages of the 76 individuals were analyzed by multiple regression analysis, and we constructed an age prediction model. We observed a strong correlation (Spearman's rho = 0.922) between predicted and chronological ages of 76 individuals with a MAD from chronological age of 3.3 years. Collectively, the result in this study showed the potential applicability of ddPCR to predict age from saliva.
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Affiliation(s)
- Min Ho Lee
- Forensic DNA Division, National Forensic Service, Wonju, Gangwon-do, South Korea
| | - Jung Hee Hwang
- DNA Analysis Division, National Forensic Service Daejeon Institute, Daejeon, South Korea
| | - Ki Min Seong
- Forensic DNA Division, National Forensic Service, Wonju, Gangwon-do, South Korea
| | | | | | - Seung Yong Hwang
- Department of Bio-Nanotechnology, Hanyang University, Ansan, Gyeonggi-do, South Korea
| | - Si-Keun Lim
- Department of Forensic Sciences, Graduate School of Sungkyunkwan University, Suwon, Gyeongi-do, South Korea.
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20
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Han Y, Nikolić M, Gobs M, Franzen J, de Haan G, Geiger H, Wagner W. Targeted methods for epigenetic age predictions in mice. Sci Rep 2020; 10:22439. [PMID: 33384442 PMCID: PMC7775437 DOI: 10.1038/s41598-020-79509-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 12/09/2020] [Indexed: 12/14/2022] Open
Abstract
Age-associated DNA methylation reflects aspect of biological aging—therefore epigenetic clocks for mice can elucidate how the aging process in this model organism is affected by specific treatments or genetic background. Initially, age-predictors for mice were trained for genome-wide DNA methylation profiles and we have recently described a targeted assay based on pyrosequencing of DNA methylation at only three age-associated genomic regions. Here, we established alternative approaches using droplet digital PCR (ddPCR) and barcoded bisulfite amplicon sequencing (BBA-seq). At individual CG dinucleotides (CpGs) the correlation of DNA methylation with chronological age was slightly higher for pyrosequencing and ddPCR as compared to BBA-seq. On the other hand, BBA-seq revealed that neighboring CpGs tend to be stochastically modified at murine age-associated regions. Furthermore, the binary sequel of methylated and non-methylated CpGs in individual reads can be used for single-read predictions, which may reflect heterogeneity in epigenetic aging. In comparison to C57BL/6 mice the single-read age-predictions using BBA-seq were also accelerated in the shorter-lived DBA/2 mice, and in C57BL/6 mice with a lifespan quantitative trait locus of DBA/2 mice. Taken together, we describe alternative targeted methods for epigenetic age predictions that provide new perspectives for aging-intervention studies in mice.
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Affiliation(s)
- Yang Han
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany.,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Miloš Nikolić
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany.,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Michael Gobs
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany.,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Julia Franzen
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany.,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Gerald de Haan
- Laboratory of Ageing Biology and Stem Cells, European Research Institute for the Biology of Ageing, University Medical Center Groningen, Groningen, the Netherlands
| | - Hartmut Geiger
- Institute of Molecular Medicine, Ulm University, 89081, Ulm, Germany
| | - Wolfgang Wagner
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Pauwelsstraße 20, 52074, Aachen, Germany. .,Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany.
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21
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Evaluation of droplet digital PCR for quantification of SARS-CoV-2 Virus in discharged COVID-19 patients. Aging (Albany NY) 2020; 12:20997-21003. [PMID: 33136068 PMCID: PMC7695381 DOI: 10.18632/aging.104020] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 08/19/2020] [Indexed: 12/11/2022]
Abstract
The worldwide severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak has led to the rapid spread of coronavirus disease (COVID-19). The quantitative real time PCR (qPCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, more and more infected patients are relapsing after discharge, which suggests qPCR may fail to detect the virus in some cases. In this study, we selected 74 clinical samples from 43 recovering inpatients for qPCR and Droplet Digital PCR (ddPCR) synchronous blind detection, and established a cutoff value for ddPCR diagnosis of COVID-19. The results showed that at a cutoff value of 0.04 copies/μL, the ddPCR sensitivity and specificity are 97.6% and 100%, respectively. In addition, we also analyzed 18 retained samples from 9 discharged patients who relapsed. Although qPCR showed all 18 samples to be negative, ddPCR showed 12 to be positive, and there was only one patient with two negative samples; the other eight patients had at least one positive sample. These results indicate that ddPCR could significantly improve the accuracy of COVID-19 diagnosis, especially for discharged patients with a low viral load, and help to reduce misdiagnosis during recovery.
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22
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Khella HWZ, Yousef GM. Translational research: Empowering the role of pathologists and cytopathologists. Cancer Cytopathol 2018; 126:831-838. [PMID: 30281935 DOI: 10.1002/cncy.22046] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Revised: 07/13/2018] [Accepted: 07/16/2018] [Indexed: 12/17/2022]
Abstract
Research activity is in the core essence of pathology. Advancing our understanding of disease pathogenesis translates into better patient care. Because of their unique position, laboratorians are the best to accurately identify, annotate, and classify research specimens. They also are essential for the accurate interpretation of genomic testing. Currently, cytopathologists are moving to the center of patient care through active communication with clinicians and patients. There are certain research areas in which cytopathologists can be pioneers, such as image analysis, morphology research, and genotype-phenotype association studies integrating morphologic and molecular features. Health service utilization research is another domain in which cytopathologists can excel. Successful research is a journey that necessitates multiple steps. It also involves building expertise in how to overcome obstacles and handle challenges.
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Affiliation(s)
- Heba W Z Khella
- Department of Laboratory Medicine, Keenan Research Center at the Li Ka Shing Knowledge Institute of St. Michael's Hospital, Toronto, Ontario, Canada.,Department of Anatomy, Canadian Memorial Chiropractic College, North York, Ontario, Canada
| | - George M Yousef
- Department of Laboratory Medicine, Keenan Research Center at the Li Ka Shing Knowledge Institute of St. Michael's Hospital, Toronto, Ontario, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
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23
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Recent progress, methods and perspectives in forensic epigenetics. Forensic Sci Int Genet 2018; 37:180-195. [PMID: 30176440 DOI: 10.1016/j.fsigen.2018.08.008] [Citation(s) in RCA: 75] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 08/15/2018] [Indexed: 01/19/2023]
Abstract
Forensic epigenetics, i.e., investigating epigenetics variation to resolve forensically relevant questions unanswerable with standard forensic DNA profiling has been gaining substantial ground over the last few years. Differential DNA methylation among tissues and individuals has been proposed as useful resource for three forensic applications i) determining the tissue type of a human biological trace, ii) estimating the age of an unknown trace donor, and iii) differentiating between monozygotic twins. Thus far, forensic epigenetic investigations have used a wide range of methods for CpG marker discovery, prediction modelling and targeted DNA methylation analysis, all coming with advantages and disadvantages when it comes to forensic trace analysis. In this review, we summarize the most recent literature on these three main topics of current forensic epigenetic investigations and discuss limitations and practical considerations in experimental design and data interpretation, such as technical and biological biases. Moreover, we provide future perspectives with regard to new research questions, new epigenetic markers and recent technological advances that - as we envision - will move the field towards forensic epigenomics in the near future.
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