The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Glycosylation: mechanisms, biological functions and clinical implications
Open accessAbstract
Protein post-translational modification (PTM) is a covalent process that occurs in proteins during or after translation through the addition or removal of one or more functional groups, and has a profound effect on protein function. Glycosylation is one of the most common PTMs, in which polysaccharides are transferred to specific amino acid residues in proteins by glycosyltransferases. A growing body of evidence suggests that glycosylation is essential for the unfolding of various functional activities in organisms, such as playing a key role in the regulation of protein function, cell adhesion and immune escape. Aberrant glycosylation is also closely associated with the development of various diseases. Abnormal glycosylation patterns are closely linked to the emergence of various health conditions, including cancer, inflammation, autoimmune disorders, and several other diseases. However, the underlying composition and structure of the glycosylated residues have not been determined. It is imperative to fully understand the internal structure and differential expression of glycosylation, and to incorporate advanced detection technologies to keep the knowledge advancing. Investigations on the clinical applications of glycosylation focused on sensitive and promising biomarkers, development of more effective small molecule targeted drugs and emerging vaccines. These studies provide a new area for novel therapeutic strategies based on glycosylation.
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Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487
Glycosylation in health and disease
Reily, C., Stewart, T. J., Renfrow, M. B., & Novak, J. (2019) · Nature Reviews Nephrology · doi:10.1038/s41581-019-0129-4 · Cited by 2,075
Roles of N-Linked Glycans in the Endoplasmic Reticulum
Helenius, A., & Aebi, M. (2004) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.73.011303.073752 · Cited by 2,037
Anti-Inflammatory Activity of Immunoglobulin G Resulting from Fc Sialylation
Kaneko, Y., Nimmerjahn, F., & Ravetch, J. V. (2006) · Science · doi:10.1126/science.1129594 · Cited by 1,754
Common variants at 30 loci contribute to polygenic dyslipidemia
Kathiresan, S., Willer, C. J., Peloso, G. M., Demissie, S., Musunuru, K., Schadt, E. E., Kaplan, L., Bennett, D., Li, Y., Tanaka, T., et al. (2009) · Nature Genetics · doi:10.1038/ng.291 · Cited by 1,364
PD-1 and PD-1 ligands: from discovery to clinical application
Okazaki, T., & Honjo, T. (2007) · International Immunology · doi:10.1093/intimm/dxm057 · Cited by 1,310
Siglec-mediated regulation of immune cell function in disease
Macauley, M. S., Crocker, P. R., & Paulson, J. C. (2014) · Nature Reviews Immunology · doi:10.1038/nri3737 · Cited by 1,122
Recapitulation of IVIG anti-inflammatory activity with a recombinant IgG Fc
Anthony, R. M., Nimmerjahn, F., Ashline, D. J., Reinhold, V. N., Paulson, J. C., & Ravetch, J. V. (2008) · Science · doi:10.1126/science.1154315 · Cited by 849
O-GlcNAcylation regulates phosphorylation of tau: A mechanism involved in Alzheimer's disease
Liu, F., Iqbal, K., Grundke-Iqbal, I., Hart, G. W., & Gong, C.-X. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400348101 · Cited by 775
Global variations in lung cancer incidence by histological subtype in 2020: a population-based study
Zhang, Y., Vaccarella, S., Morgan, E., Li, M., Etxeberria, J., Chokunonga, E., Manraj, S. S., Kamate, B., Omonisi, A., & Bray, F. (2023) · The Lancet Oncology · doi:10.1016/s1470-2045(23)00444-8 · Cited by 445
Glucose Conjugation for the Specific Targeting and Treatment of Cancer
Calvaresi, E. C., & Hergenrother, P. J. (2013) · Chemical Science · doi:10.1039/c3sc22205e · Cited by 398
Proteogenomic Characterization of Human Early-Onset Gastric Cancer
Mun, D.-G., Bhin, J., Kim, S., Kim, H., Jung, J. H., Jung, Y., Jang, Y. E., Park, J. M., Kim, H., Jung, Y., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2018.12.003 · Cited by 294
Targeting CDK1 promotes FLT3-activated acute myeloid leukemia differentiation through C/EBPα
Radomska, H. S., Alberich-Jordà, M., Will, B., Gonzalez, D., Delwel, R., & Tenen, D. G. (2012) · Journal of Clinical Investigation · doi:10.1172/jci43354 · Cited by 67
Cited by
Glycosylation in cancer: mechanisms, diagnostic markers, and therapeutic applications
Qusairy, Z., & Rada, M. (2025) · Molecular and Cellular Biochemistry · doi:10.1007/s11010-025-05303-1 · Cited by 16
Mechanistic origin of C - over O -glycosylation in glycosyltransferase GgCGT: a QM/MM study
Terada, D., Inagaki, T., & Hatanaka, M. (2026) · Bulletin of the Chemical Society of Japan · doi:10.1093/bulcsj/uoag026
Metadata
- Authors
- He, M., Zhou, X., & Wang, X.
- Venue
- Signal Transduction and Targeted Therapy
- Published
- 2024-08-05
- Volume
- 9
- Issue
- 1
- Pages
- 194-194
- ISSN
- 2059-3635 (ISSN-L)
- OpenAlex
- W4401349719
- Cited by
- 499
- References
- 13
- FWCI
- 57.98
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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