1
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Hong G, Luo F, Chen Z, Ma L, Lin G, Wu T, Li N, Cai H, Hu T, Zhong H, Guo Y, Li H. Predict ovarian cancer by pairing serum miRNAs: Construct of single sample classifiers. Front Med (Lausanne) 2022; 9:923275. [PMID: 35983098 PMCID: PMC9378834 DOI: 10.3389/fmed.2022.923275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 07/15/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveThe accuracy of CA125 or clinical examination in ovarian cancer (OVC) screening is still facing challenges. Serum miRNAs have been considered as promising biomarkers for clinical applications. Here, we propose a single sample classifier (SSC) method based on within-sample relative expression orderings (REOs) of serum miRNAs for OVC diagnosis.MethodsBased on the stable REOs within 4,965 non-cancer serum samples, we developed the SSC for OVC in the training cohort (GSE106817: OVC = 200, non-cancer = 2,000) by focusing on highly reversed REOs within OVC. The best diagnosis is achieved using a combination of reversed miRNA pairs, considering the largest evaluation index and the lowest number of miRNA pairs possessed according to the voting rule. The SSC was then validated in internal data (GSE106817: OVC = 120, non-cancer = 759) and external data (GSE113486: OVC = 40, non-cancer = 100).ResultsThe obtained 13-miRPairs classifier showed high diagnostic accuracy on distinguishing OVC from non-cancer controls in the training set (sensitivity = 98.00%, specificity = 99.60%), which was reproducible in internal data (sensitivity = 98.33%, specificity = 99.21%) and external data (sensitivity = 97.50%, specificity = 100%). Compared with the published models, it stood out in terms of correct positive predictive value (PPV) and negative predictive value (NPV) (PPV = 96.08% and NPV=95.16% in training set, and both above 99% in validation set). In addition, 13-miRPairs demonstrated a classification accuracy of over 97.5% for stage I OVC samples. By integrating other non-OVC serum samples as a control, the obtained 17-miRPairs classifier could distinguish OVC from other cancers (AUC>92% in training and validation set).ConclusionThe REO-based SSCs performed well in predicting OVC (including early samples) and distinguishing OVC from other cancer types, proving that REOs of serum miRNAs represent a robust and non-invasive biomarker.
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Affiliation(s)
- Guini Hong
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Fengyuan Luo
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Zhihong Chen
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Liyuan Ma
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Guiyang Lin
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Tong Wu
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Na Li
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Hao Cai
- Medical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China
| | - Tao Hu
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Haijian Zhong
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - You Guo
- Medical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China
- You Guo
| | - Hongdong Li
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
- *Correspondence: Hongdong Li
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2
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Li H, Jiang F, Du Y, Li N, Chen Z, Cai H, Guo Y, Hong G. Identification of differential DNA methylation alterations of ovarian cancer in peripheral whole blood based on within-sample relative methylation orderings. Epigenetics 2021; 17:314-326. [PMID: 33749504 DOI: 10.1080/15592294.2021.1900029] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Abstract
Leukocyte cell proportion changes affect the detection of cancer-associated aberrant DNA methylation alterations in peripheral blood samples. We aimed to detect cellular DNA methylation changes in ovarian cancer (OVC) blood samples avoiding the above-mentioned cell-composition effects. Based on the within-sample relative methylation orderings (RMOs) of CpG loci in leukocyte subtypes, we developed the Ref-RMO method to detect aberrant methylation alterations from OVC blood samples. Stable CpG pairs with consistent RMOs in different leukocyte subtypes were determined, more than 99% of which retained their RMO patterns in peripheral whole blood (PWB) in independent datasets. Based on the stable CpG pairs, significantly reversed CpG pairs were detected from OVC PWB samples, which were relative to clinical information such as age, subtype, grade, stage, or CA125 level. Results showed 439 CpG loci were determined to be significant differential DNA methylations between OVC and healthy blood samples. They were mainly enriched in KEGG pathways, such as cytokine-cytokine receptor interaction, apoptosis, proteoglycans in cancer, and immune-associated Gene Ontology terms. STRING analysis showed that they tended to have functional interactions with cancer-associated genes recorded in the COSMIC database. Leukocyte cellular differential DNA methylations could be identified by the proposed RMO-based method from OVC PWB samples, which were cancer-associated aberrant signals against cell-composition effects.
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Affiliation(s)
- Hongdong Li
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Fengle Jiang
- Department of Bioinformatics, Fujian Medical University, Fuzhou, China
| | - Yuhui Du
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Na Li
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Zhihong Chen
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China
| | - Hao Cai
- Medical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China
| | - You Guo
- Medical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, China
| | - Guini Hong
- School of Medical Information Engineering, Gannan Medical University, Ganzhou, China.,Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases, Ministry of Education, Gannan Medical University, Ganzhou, PR China
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3
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Johnson ND, Huang L, Li R, Li Y, Yang Y, Kim HR, Grant C, Wu H, Whitsel EA, Kiel DP, Baccarelli AA, Jin P, Murabito JM, Conneely KN. Age-related DNA hydroxymethylation is enriched for gene expression and immune system processes in human peripheral blood. Epigenetics 2019; 15:294-306. [PMID: 31506003 DOI: 10.1080/15592294.2019.1666651] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
DNA methylation (DNAm) has a well-established association with age in many tissues, including peripheral blood mononuclear cells (PBMCs). Compared to DNAm, the closely related epigenetic modification known as DNA hydroxymethylation (DNAhm) was much more recently discovered in mammals. Preliminary investigations have observed a positive correlation between gene body DNAhm and cis-gene expression. While some of these studies have observed an association between age and global DNAhm, none have investigated region-specific age-related DNAhm in human blood samples. In this study, we investigated DNAhm and gene expression in PBMCs of 10 young and 10 old, healthy female volunteers. Thousands of regions were differentially hydroxymethylated in the old vs. young individuals in gene bodies, exonic regions, enhancers, and promoters. Consistent with previous work, we observed directional consistency between age-related differences in DNAhm and gene expression. Further, age-related DNAhm and genes with high levels of DNAhm were enriched for immune system processes which may support a role of age-related DNAhm in immunosenescence.
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Affiliation(s)
- Nicholas D Johnson
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA, USA
| | - Luoxiu Huang
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Ronghua Li
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.,Department of Biostatistics, Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Yuchen Yang
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Hye Rim Kim
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Cancer Biology Graduate Program, Emory University, Atlanta, GA, USA
| | - Crystal Grant
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Genetics and Molecular Biology Graduate Program, Emory University, Atlanta, GA, USA
| | - Hao Wu
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.,Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Douglas P Kiel
- Hebrew SeniorLife, Department of Medicine Beth Israel Deaconess Medical Center and Harvard Medical School, Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Peng Jin
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Joanne M Murabito
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA.,Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA, USA
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4
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The role of DNA methylation and hydroxymethylation in immunosenescence. Ageing Res Rev 2019; 51:11-23. [PMID: 30769150 DOI: 10.1016/j.arr.2019.01.011] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 01/23/2019] [Accepted: 01/24/2019] [Indexed: 12/12/2022]
Abstract
A healthy functioning immune system is critical to stave off infectious diseases, but as humans and other organisms age, their immune systems decline. As a result, diseases that were readily thwarted in early life pose nontrivial harm and can even be deadly in late life. Immunosenescence is defined as the general deterioration of the immune system with age, and it is characterized by functional changes in hematopoietic stem cells (HSCs) and specific blood cell types as well as changes in levels of numerous factors, particularly those involved in inflammation. Potential mechanisms underlying immunosenescence include epigenetic changes such as changes in DNA methylation (DNAm) and DNA hydroxymethylation (DNAhm) that occur with age. The purpose of this review is to describe what is currently known about the relationship between immunosenescence and the age-related changes to DNAm and DNAhm, and to discuss experimental approaches best suited to fill gaps in our understanding.
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5
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Common DNA methylation alterations of Alzheimer's disease and aging in peripheral whole blood. Oncotarget 2017; 7:19089-98. [PMID: 26943045 PMCID: PMC4991367 DOI: 10.18632/oncotarget.7862] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2016] [Accepted: 02/23/2016] [Indexed: 12/23/2022] Open
Abstract
Alzheimer's disease (AD) is a common aging-related neurodegenerative illness. Recently, many studies have tried to identify AD- or aging-related DNA methylation (DNAm) biomarkers from peripheral whole blood (PWB). However, the origin of PWB biomarkers is still controversial. In this study, by analyzing 2565 DNAm profiles for PWB and brain tissue, we showed that aging-related DNAm CpGs (Age-CpGs) and AD-related DNAm CpGs (AD-CpGs) observable in PWB both mainly reflected DNAm alterations intrinsic in leukocyte subtypes rather than methylation differences introduced by the increased ratio of myeloid to lymphoid cells during aging or AD progression. The PWB Age-CpGs and AD-CpGs significantly overlapped 107 sites (P-value = 2.61×10−12) and 97 had significantly concordant methylation alterations in AD and aging (P-value < 2.2×10−16), which were significantly enriched in nervous system development, neuron differentiation and neurogenesis. More than 60.8% of these 97 concordant sites were found to be significantly correlated with age in normal peripheral CD4+ T cells and CD14+ monocytes as well as in four brain regions, and 44 sites were also significantly differentially methylated in different regions of AD brain tissue. Taken together, the PWB DNAm alterations related to both aging and AD could be exploited for identification of AD biomarkers.
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6
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Breeze CE, Paul DS, van Dongen J, Butcher LM, Ambrose JC, Barrett JE, Lowe R, Rakyan VK, Iotchkova V, Frontini M, Downes K, Ouwehand WH, Laperle J, Jacques PÉ, Bourque G, Bergmann AK, Siebert R, Vellenga E, Saeed S, Matarese F, Martens JHA, Stunnenberg HG, Teschendorff AE, Herrero J, Birney E, Dunham I, Beck S. eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data. Cell Rep 2017; 17:2137-2150. [PMID: 27851974 PMCID: PMC5120369 DOI: 10.1016/j.celrep.2016.10.059] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2016] [Revised: 08/25/2016] [Accepted: 09/30/2016] [Indexed: 12/14/2022] Open
Abstract
Epigenome-wide association studies (EWAS) provide an alternative approach for studying human disease through consideration of non-genetic variants such as altered DNA methylation. To advance the complex interpretation of EWAS, we developed eFORGE (http://eforge.cs.ucl.ac.uk/), a new standalone and web-based tool for the analysis and interpretation of EWAS data. eFORGE determines the cell type-specific regulatory component of a set of EWAS-identified differentially methylated positions. This is achieved by detecting enrichment of overlap with DNase I hypersensitive sites across 454 samples (tissues, primary cell types, and cell lines) from the ENCODE, Roadmap Epigenomics, and BLUEPRINT projects. Application of eFORGE to 20 publicly available EWAS datasets identified disease-relevant cell types for several common diseases, a stem cell-like signature in cancer, and demonstrated the ability to detect cell-composition effects for EWAS performed on heterogeneous tissues. Our approach bridges the gap between large-scale epigenomics data and EWAS-derived target selection to yield insight into disease etiology.
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Affiliation(s)
- Charles E Breeze
- UCL Cancer Institute, University College London, London WC1E 6BT, UK.
| | - Dirk S Paul
- UCL Cancer Institute, University College London, London WC1E 6BT, UK
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081BT Amsterdam, the Netherlands
| | - Lee M Butcher
- UCL Cancer Institute, University College London, London WC1E 6BT, UK; Department of Surgery and Cancer, Imperial College London, London W12 0NN, UK
| | - John C Ambrose
- UCL Cancer Institute, University College London, London WC1E 6BT, UK
| | - James E Barrett
- UCL Cancer Institute, University College London, London WC1E 6BT, UK
| | - Robert Lowe
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, E1 2AT London, UK
| | - Vardhman K Rakyan
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, E1 2AT London, UK
| | - Valentina Iotchkova
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0QQ, UK
| | - Kate Downes
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Willem H Ouwehand
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1HH, UK; Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0QQ, UK
| | - Jonathan Laperle
- Département d'Informatique, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
| | - Pierre-Étienne Jacques
- Département d'Informatique, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada; Département de Biologie, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada; Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
| | - Guillaume Bourque
- Department of Human Genetics, McGill University, Montréal, QC H3G 1Y6, Canada; Génome Québec Innovation Center, Montréal, QC H3A 0G1, Canada
| | - Anke K Bergmann
- Institute of Human Genetics, Christian Albrechts University, 24105 Kiel, Germany; Department of Pediatrics, Christian-Albrechts-University Kiel & University Hospital Schleswig-Holstein, 24105 Kiel, Germany
| | - Reiner Siebert
- Institute of Human Genetics, Christian Albrechts University, 24105 Kiel, Germany; Institute of Human Genetics, University of Ulm, Albert-Einstein-Allee 11, 89081 Ulm, Germany
| | - Edo Vellenga
- Department of Hematology, University of Groningen and University Medical Center Groningen, PO Box 30001, 9700 RB Groningen, the Netherlands
| | - Sadia Saeed
- Department of Biochemistry, PMAS Arid Agriculture University Rawalpindi, 46300 Rawalpindi, Pakistan; Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, 6500 HB Nijmegen, the Netherlands
| | - Filomena Matarese
- Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, 6500 HB Nijmegen, the Netherlands
| | - Joost H A Martens
- Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, 6500 HB Nijmegen, the Netherlands
| | - Hendrik G Stunnenberg
- Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, 6500 HB Nijmegen, the Netherlands
| | | | - Javier Herrero
- UCL Cancer Institute, University College London, London WC1E 6BT, UK
| | - Ewan Birney
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ian Dunham
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Stephan Beck
- UCL Cancer Institute, University College London, London WC1E 6BT, UK.
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7
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Li H, Hong G, Lin M, Shi Y, Wang L, Jiang F, Zhang F, Wang Y, Guo Z. Identification of molecular alterations in leukocytes from gene expression profiles of peripheral whole blood of Alzheimer's disease. Sci Rep 2017; 7:14027. [PMID: 29070791 PMCID: PMC5656592 DOI: 10.1038/s41598-017-13700-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Accepted: 09/27/2017] [Indexed: 11/08/2022] Open
Abstract
Blood-based test has been considered as a promising way to diagnose and study Alzheimer's disease (AD). However, the changed proportions of the leukocytes under disease states could confound the aberrant expression signals observed in mixed-cell blood samples. We have previously proposed a method, Ref-REO, to detect the leukocyte specific expression alterations from mixed-cell blood samples. In this study, by applying Ref-REO, we detect 42 and 45 differentially expressed genes (DEGs) between AD and normal peripheral whole blood (PWB) samples in two datasets, respectively. These DEGs are mainly associated with AD-associated functions such as Wnt signaling pathways and mitochondrion dysfunctions. They are also reproducible in AD brain tissue, and tend to interact with the reported AD-associated biomarkers and overlap with targets of AD-associated PWB miRNAs. Moreover, they are closely associated with aging and have severer expression alterations in the younger adults with AD. Finally, diagnostic signatures are constructed from these leukocyte specific alterations, whose area under the curve (AUC) for predicting AD is higher than 0.73 in the two AD PWB datasets. In conclusion, gene expression alterations in leukocytes could be extracted from AD PWB samples, which are closely associated with AD progression, and used as a diagnostic signature of AD.
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Affiliation(s)
- Hongdong Li
- Department of bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Guini Hong
- Department of bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
| | - Mengna Lin
- Department of bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Yidan Shi
- Department of bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Lili Wang
- Department of bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Fengle Jiang
- Department of bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Fan Zhang
- Department of bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Yuhang Wang
- Department of bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Zheng Guo
- Department of bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China
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8
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Hong G, Li H, Li M, Zheng W, Li J, Chi M, Cheng J, Guo Z. A simple way to detect disease-associated cellular molecular alterations from mixed-cell blood samples. Brief Bioinform 2017; 19:613-621. [DOI: 10.1093/bib/bbx009] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2016] [Indexed: 12/15/2022] Open
Affiliation(s)
- Guini Hong
- Department of Bioinformatics, Fujian Medical University, Fuzhou, China
| | - Hongdong Li
- Department of Bioinformatics, Fujian Medical University, Fuzhou, China
| | - Mengyao Li
- Department of Bioinformatics, Fujian Medical University, Fuzhou, China
| | - Weicheng Zheng
- Department of Bioinformatics, Fujian Medical University, Fuzhou, China
| | - Jing Li
- Department of Bioinformatics, Fujian Medical University, Fuzhou, China
| | - Meirong Chi
- Department of Bioinformatics, Fujian Medical University, Fuzhou, China
| | - Jun Cheng
- Department of Bioinformatics, Fujian Medical University, Fuzhou, China
| | - Zheng Guo
- Department of Bioinformatics, Fujian Medical University, Fuzhou, China
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9
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Bhowmik A, Das S, Bhattacharjee A, Choudhury B, Naiding M, Ghosh SK, Choudhury Y. BRCA1 and MDM2 as independent blood-based biomarkers of head and neck cancer. Tumour Biol 2016; 37:10.1007/s13277-016-5359-5. [PMID: 27714671 DOI: 10.1007/s13277-016-5359-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Accepted: 09/07/2016] [Indexed: 11/27/2022] Open
Abstract
We investigated the role of BRCA1, MDM2, and p53 in the pathogenesis of head and neck cancer (HNC) and evaluated their potential utility as blood-based predictive biomarkers of HNC. Immunostaining of tissue biopsies and whole blood lymphocytes (WBL) of 36 HNC patients were evaluated by immunohistochemistry (IHC) and immunocytochemistry (ICC), respectively. The staining intensities of BRCA1 and MDM2 in matched tissue and blood samples were significantly associated with cancer stage. Furthermore, the cellular levels of BRCA1, MDM2, and p53 were evaluated in peripheral blood lymphocytes (PBL) of 134 HNC patients and 126 controls by slot blotting. Expression levels of all three proteins in PBL of HNC patients varied significantly with respect to those of controls (p < 0.0001) with BRCA1 downregulated to 75 % of control and MDM2 and p53 upregulated to 1.7- and 1.4-fold the control level, respectively. Moreover, positive correlation was observed between expression levels of BRCA1, MDM2, and p53 in matched tissue biopsies-WBL (r s = 0.840, 0.754, and 0.806, respectively), tissue biopsies-PBL (r s = 0.745, 0.736, and 0.776, respectively), and PBL-WBL (r s = 0.709, 0.758, and 0.740, respectively), validating the hypothesis that these proteins may serve as blood-based biomarkers of HNC. Bias-corrected and accelerated (BCa) bootstrap cross-validation estimation of receiver operating characteristics (ROC) analysis established BRCA1 (AUC = 0.726, sensitivity = 89 %, NPV = 82 %) and MDM2 (AUC = 0.827, sensitivity = 85 %, NPV = 81 %) as predictive biomarkers for HNC. In conclusion, this study suggests that BRCA1 and MDM2 play a crucial role in the pathogenesis of HNC and could be used independently as predictive biomarkers for HNC.
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Affiliation(s)
- Aditi Bhowmik
- Department of Biotechnology, Assam University, Silchar, 788011, India
| | - Sambuddha Das
- Department of Biotechnology, Assam University, Silchar, 788011, India
| | | | - Biswadeep Choudhury
- Department of Biochemistry, Silchar Medical College and Hospital, Silchar, 788014, India
| | - Momota Naiding
- Department of Pathology, Silchar Medical College and Hospital, Silchar, -788014, India
| | | | - Yashmin Choudhury
- Department of Biotechnology, Assam University, Silchar, 788011, India.
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10
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Mamrut S, Avidan N, Staun-Ram E, Ginzburg E, Truffault F, Berrih-Aknin S, Miller A. Integrative analysis of methylome and transcriptome in human blood identifies extensive sex- and immune cell-specific differentially methylated regions. Epigenetics 2016; 10:943-57. [PMID: 26291385 DOI: 10.1080/15592294.2015.1084462] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The relationship between DNA methylation and gene expression is complex and elusive. To further elucidate these relations, we performed an integrative analysis of the methylome and transcriptome of 4 circulating immune cell subsets (B cells, monocytes, CD4(+), and CD8(+) T cells) from healthy females. Additionally, in light of the known sex bias in the prevalence of several immune-mediated diseases, the female datasets were compared with similar public available male data sets. Immune cell-specific differentially methylated regions (DMRs) were found to be highly similar between sexes, with an average correlation coefficient of 0.82; however, numerous sex-specific DMRs, shared by the cell subsets, were identified, mainly on autosomal chromosomes. This provides a list of highly interesting candidate genes to be studied in disorders with sexual dimorphism, such as autoimmune diseases. Immune cell-specific DMRs were mainly located in the gene body and intergenic region, distant from CpG islands but overlapping with enhancer elements, indicating that distal regulatory elements are important in immune cell specificity. In contrast, sex-specific DMRs were overrepresented in CpG islands, suggesting that the epigenetic regulatory mechanisms of sex and immune cell specificity may differ. Both positive and, more frequently, negative correlations between subset-specific expression and methylation were observed, and cell-specific DMRs of both interactions were associated with similar biological pathways, while sex-specific DMRs were linked to networks of early development or estrogen receptor and immune-related molecules. Our findings of immune cell- and sex-specific methylome and transcriptome profiles provide novel insight on their complex regulatory interactions and may particularly contribute to research of immune-mediated diseases.
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Affiliation(s)
- Shimrat Mamrut
- a Rappaport Faculty of Medicine; Technion-Israel Institute of Technology ; Haifa , Israel
| | - Nili Avidan
- a Rappaport Faculty of Medicine; Technion-Israel Institute of Technology ; Haifa , Israel
| | - Elsebeth Staun-Ram
- a Rappaport Faculty of Medicine; Technion-Israel Institute of Technology ; Haifa , Israel
| | - Elizabeta Ginzburg
- a Rappaport Faculty of Medicine; Technion-Israel Institute of Technology ; Haifa , Israel
| | - Frederique Truffault
- b INSERM - U974/CNRS UMR7215//UPMC UM76/AIM; Institute of Myology Pitie-Salpetriere ; Paris , France
| | - Sonia Berrih-Aknin
- b INSERM - U974/CNRS UMR7215//UPMC UM76/AIM; Institute of Myology Pitie-Salpetriere ; Paris , France
| | - Ariel Miller
- a Rappaport Faculty of Medicine; Technion-Israel Institute of Technology ; Haifa , Israel.,c Division of Neuroimmunology; Lady Davis Carmel Medical Center ; Haifa , Israel
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Amacher DE. A 2015 survey of established or potential epigenetic biomarkers for the accurate detection of human cancers. Biomarkers 2016; 21:387-403. [PMID: 26983778 DOI: 10.3109/1354750x.2016.1153724] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Context The silencing or activation of cancer-associated genes by epigenetic mechanisms can ultimately lead to the clonal expansion of cancer cells. Objective The aim of this review is to summarize all relevant epigenetic biomarkers that have been proposed to date for the diagnosis of some prevalent human cancers. Methods A Medline search for the terms epigenetic biomarkers, human cancers, DNA methylation, histone modifications and microRNAs was performed. Results One hundred fifty-seven relevant publications were found and reviewed. Conclusion To date, a significant number of potential epigenetic cancer biomarkers of human cancer have been investigated, and some have advanced to clinical implementation.
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Abstract
Lung cancer is the most frequently occurring cancer in the world and continually leads in mortality among cancers. The overall 5-year survival rate for lung cancer has risen only 4% (from 12% to 16%) over the past 4 decades, and late diagnosis is a major obstacle in improving lung cancer prognosis. Survival of patients undergoing lung resection is greater than 80%, suggesting that early detection and diagnosis of cancers before they become inoperable and lethal will greatly improve mortality. Lung cancer biomarkers can be used for screening, detection, diagnosis, prognosis, prediction, stratification, therapy response monitoring, and so on. This review focuses on noninvasive diagnostic and prognostic biomarkers. For that purpose, our discussion in this review will focus on biological fluid-based biomarkers. The body fluids include blood (serum or plasma), sputum, saliva, BAL, pleural effusion, and VOC. Since it is rich in different cellular and molecular elements and is one of the most convenient and routine clinical procedures, serum or plasma is the main source for the development and validation of many noninvasive biomarkers. In terms of molecular aspects, the most widely validated ones are proteins, some of which are used in the clinical sector, though in limited accessory purposes. We will also discuss the lung cancer (protein) biomarkers in clinical trials and currently in the validation phase with hundreds of samples. After proteins, we will discuss microRNAs, methylated DNA, and circulating tumor cells, which are being vigorously developed and validated as potential lung cancer biomarkers. The main aim of this review is to provide researchers and clinicians with an understanding of the potential noninvasive lung cancer biomarkers in biological fluids that have recently been discovered.
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