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Pan H, Wu Z, Zhang H, Zhang J, Liu Y, Li Z, Feng W, Wang G, Liu Y, Zhao D, Zhang Z, Liu Y, Zhang Z, Liu X, Tao L, Luo Y, Wang X, Yang X, Zhang F, Li X, Guo X. Identification and validation of IgG N-glycosylation biomarkers of esophageal carcinoma. Front Immunol 2023; 14:981861. [PMID: 36999031 PMCID: PMC10043232 DOI: 10.3389/fimmu.2023.981861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 02/28/2023] [Indexed: 03/16/2023] Open
Abstract
IntroductionAltered Immunoglobulin G (IgG) N-glycosylation is associated with aging, inflammation, and diseases status, while its effect on esophageal squamous cell carcinoma (ESCC) remains unknown. As far as we know, this is the first study to explore and validate the association of IgG N-glycosylation and the carcinogenesis progression of ESCC, providing innovative biomarkers for the predictive identification and targeted prevention of ESCC.MethodsIn total, 496 individuals of ESCC (n=114), precancerosis (n=187) and controls (n=195) from the discovery population (n=348) and validation population (n=148) were recruited in the study. IgG N-glycosylation profile was analyzed and an ESCC-related glycan score was composed by a stepwise ordinal logistic model in the discovery population. The receiver operating characteristic (ROC) curve with the bootstrapping procedure was used to assess the performance of the glycan score.ResultsIn the discovery population, the adjusted OR of GP20 (digalactosylated monosialylated biantennary with core and antennary fucose), IGP33 (the ratio of all fucosylated monosyalilated and disialylated structures), IGP44 (the proportion of high mannose glycan structures in total neutral IgG glycans), IGP58 (the percentage of all fucosylated structures in total neutral IgG glycans), IGP75 (the incidence of bisecting GlcNAc in all fucosylated digalactosylated structures in total neutral IgG glycans), and the glycan score are 4.03 (95% CI: 3.03-5.36, P<0.001), 0.69 (95% CI: 0.55-0.87, P<0.001), 0.56 (95% CI: 0.45-0.69, P<0.001), 0.52 (95% CI: 0.41-0.65, P<0.001), 7.17 (95% CI: 4.77-10.79, P<0.001), and 2.86 (95% CI: 2.33-3.53, P<0.001), respectively. Individuals in the highest tertile of the glycan score own an increased risk (OR: 11.41), compared with those in the lowest. The average multi-class AUC are 0.822 (95% CI: 0.786-0.849). Findings are verified in the validation population, with an average AUC of 0.807 (95% CI: 0.758-0.864).DiscussionOur study demonstrated that IgG N-glycans and the proposed glycan score appear to be promising predictive markers for ESCC, contributing to the early prevention of esophageal cancer. From the perspective of biological mechanism, IgG fucosylation and mannosylation might involve in the carcinogenesis progression of ESCC, and provide potential therapeutic targets for personalized interventions of cancer progression.
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Affiliation(s)
- Huiying Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
- Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Zhiyuan Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
- Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Haiping Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Jie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Yue Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Zhiwei Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Wei Feng
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Guiqi Wang
- Department of Endoscopy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yong Liu
- Department of Endoscopy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Deli Zhao
- Cancer Centre, The Feicheng People’s Hospital, Feicheng, Shandong, China
| | - Zhiyi Zhang
- Department of Gastroenterology, Gansu Wuwei Cancer Hospital, Wuwei, Gansu, China
| | - Yuqin Liu
- Cancer Epidemiology Research Centre, Gansu Province Cancer Hospital, Lanzhou, Gansu, China
| | - Zhe Zhang
- Department of Occupational Health, Wuwei Center for Disease Prevention and Control, Wuwei, Gansu, China
| | - Xiangtong Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Lixin Tao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Yanxia Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Xiaonan Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Xinghua Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Feng Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Xia Li
- Department of Mathematics and Statistics, La Trobe University, Melbourne, VIC, Australia
| | - Xiuhua Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
- Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- *Correspondence: Xiuhua Guo,
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Sha J, Fan J, Zhang R, Gu Y, Xu X, Ren S, Gu J. B-cell-specific ablation of β-1,4-galactosyltransferase 1 prevents aging-related IgG glycans changes and improves aging phenotype in mice. J Proteomics 2022; 268:104717. [PMID: 36084919 DOI: 10.1016/j.jprot.2022.104717] [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: 05/11/2022] [Revised: 08/16/2022] [Accepted: 08/25/2022] [Indexed: 10/14/2022]
Abstract
IgG N-glycans levels change with advancing age, making it a potential biomarker of aging. β-1,4-galactosyltransferase (B4GALT) gene expression levels also increase with aging. Ultra performance liquid chromatography (UPLC) was used to examine changes inserum IgG N-glycans at six time points during the aging process. Most serum IgG N-glycans changed with aging in WT but not in CD19-cre B4GALT1 floxed mice. The relative abundance of fucosylated biantennary glycans with or without Neu5Gc structures changed with aging in heterozygous B4GALT1 floxed mice but not in homozygous B4GALT1 floxed mice. Additionally, the aging phenotype was more apparent in WT mice than in B4GALT1 floxed mice. These results demonstrate that fucosylated biantennary glycans and fucosylated biantennary glycans containing N-glycolylneuraminic acid (Neu5Gc)-linked N-acetyllactosamine (LacNAc) were highly associated with aging and were affected by the B4GALT1 floxed mouse genotype. The changing levels of fucosylated monoantennary glycans observed with aging in WT mice was reversed in B4GALT1 floxed mice and was not sex specific. In summary, B-cell-specific ablation of B4GALT1 from a glycoproteomic perspective prevented age-related changes in IgG N-glycans in mice. SIGNIFICANCE: In this study, serum IgG glycoproteomic data in wild-type (WT) and B-cell-specific ablation of β-1,4-galactosyltransferase 1 mice (B4GALT) were analyzed. Results showed that fucosylated biantennary glycans with or without N-glycolylneuraminic acid (Neu5Gc)-linked N-acetyllactosamine (LacNAc) were highly associated with aging and were also affected by the B4GALT1 floxed mouse genotype. In terms of gender-specific information, the trend towards elevated fucosylated monoantennary glycans in WT mice was not seen in CD19-cre B4GALT1 floxed mice in either sex. B-cell-specific ablation of B4GALT1 plays an important role in age-related glycan changes; its specific functions and mechanisms are worthy of in-depth study. Our data suggest that investigating the relationship between galactosylation and aging may help advance the field of glycoproteomics and aging research.
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Affiliation(s)
- Jichen Sha
- NHC Key Laboratory of Glycoconjugates Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, 130 Dongan Road, Shanghai 200032, China
| | - Jiteng Fan
- NHC Key Laboratory of Glycoconjugates Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, 130 Dongan Road, Shanghai 200032, China
| | - Rongrong Zhang
- NHC Key Laboratory of Glycoconjugates Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, 130 Dongan Road, Shanghai 200032, China
| | - Yong Gu
- NHC Key Laboratory of Glycoconjugates Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, 130 Dongan Road, Shanghai 200032, China
| | - Xiaoyan Xu
- NHC Key Laboratory of Glycoconjugates Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, 130 Dongan Road, Shanghai 200032, China
| | - Shifang Ren
- NHC Key Laboratory of Glycoconjugates Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, 130 Dongan Road, Shanghai 200032, China.
| | - Jianxin Gu
- NHC Key Laboratory of Glycoconjugates Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, 130 Dongan Road, Shanghai 200032, China.
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Özdemir V, Springer S, Yıldırım A, Biçer Ş, Kendirci A, Şardaş S, Kılıç H, Hekim N, Kunej T, Arga KY, Dzobo K, Wang W, Geanta M, Brand A, Bayram M. Thanatechnology and the Living Dead: New Concepts in Digital Transformation and Human-Computer Interaction. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2021; 25:401-407. [PMID: 34191613 DOI: 10.1089/omi.2021.0100] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
In a digital society, shall we be the authors of our own experience, not only during our lifetime but also after we die? We ask this question because dying and bereavement have become even harder, and much less private, in the digital age. New big data-driven digital industries and technologies are on the rise, with promises of interactive 3D avatars and storage of digital memories of the deceased, so they can continue to exist online as the "living dead" in a digital afterlife. Famous rock and roll icons like Roy Orbison, Frank Zappa, Ronnie James Dio, and Amy Winehouse have famously been turned into holograms that can once again give "live" performances on the touring circuit, often pulling in large audiences. Death studies, dying, and grief have become virtual in the 21st century. We live in truly unprecedented times for human-computer interactions. Thanatology is the scientific study of death, dying, loss, and grief. In contrast to the biological study of biological aging (cellular senescence) and programmed cell death (apoptosis), thanatology employs multiple professional lenses, medical, psychological, physical, spiritual, ethical, descriptive, and normative. In 1997, Carla Sofka introduced the term thanatechnology as "technological mechanisms such as interactive videodiscs and computer programs that are used to access information or aid in learning about thanatology topics." Onward to 2021, the advent of social media, the Internet of Things, and sensors that digitize and archive nearly every human movement and experience are taking thanatechnology, and by extension, digital transformation, to new heights. For example, what happens to digital remains of persons once they cease to exist physically? This article offers a critical study and snapshot of this nascent field, and the "un-disciplinary" sociotechnical issues digital thanatechnologies raise in relation to big data. We also discuss how best to critically govern this new frontier in systems science and the digital society. We suggest that new policy narratives such as (1) the right to nonparticipation in relation to information and communication technologies and (2) the planetary public goods deserve further attention to democratize thanatechnology and big data. To the extent that systems science often depends on data from online platforms, for example, in times of pandemics and ecological crises, "critical thanatechnology studies," introduced in this article, is a timely and essential field of scholarship with broad importance for systems science and planetary health.
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Affiliation(s)
- Vural Özdemir
- OMICS: A Journal of Integrative Biology, New Rochelle, New York, USA
| | - Simon Springer
- Centre for Urban and Regional Studies, Discipline of Geography and Environmental Studies, School of Environmental and Life Sciences, Faculty of Science, University of Newcastle, Callaghan, Australia
| | - Arif Yıldırım
- Department of Journalism, Faculty of Communication, Çanakkale On Sekiz Mart University, Çanakkale, Turkey
| | - Şehmus Biçer
- Department of Media and Cultural Studies, School of Graduate Studies, Çanakkale On Sekiz Mart University, Çanakkale, Turkey
| | - Aslıgül Kendirci
- Ascot Science, Pharmaceutical and Clinical Trial Innovation, İstanbul, Turkey
- Faculty of Pharmacy, İstinye University, İstanbul, Turkey
| | - Semra Şardaş
- Faculty of Pharmacy, İstinye University, İstanbul, Turkey
| | - Hakan Kılıç
- Department for Migration and Globalization, Danube-University Krems, Krems, Austria
| | - Nezih Hekim
- Department of Molecular Biology and Genetics, Biruni Üniversity, Istanbul, Turkey
| | - Tanja Kunej
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Kazım Yalçın Arga
- Department of Bioengineering, Faculty of Engineering, Marmara University, İstanbul, Turkey
| | - Kevin Dzobo
- Division of Medical Biochemistry and Institute of Infectious Disease and Molecular Medicine, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Wei Wang
- Key Municipal Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
- Centre for Precision Health, Edith Cowan University, Joondalup, Australia
- School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai'an, China
- The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Marius Geanta
- Centre for Innovation in Medicine, Bucharest, Romania
- KOL Medical Media, Bucharest, Romania
- United Nations University-Maastricht Economic and Social Research Institute on Innovation and Technology, Maastricht, The Netherlands
| | - Angela Brand
- United Nations University-Maastricht Economic and Social Research Institute on Innovation and Technology, Maastricht, The Netherlands
- Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
- Department of Public Health Genomics, and Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India
- Dr. TMA Pai Endowment Chair in Public Health Genomics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India
| | - Mustafa Bayram
- Department of Food Engineering, Faculty of Engineering, Gaziantep University, Gaziantep, Turkey
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