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PXD016318

PXD016318 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleProfiling of Subclass-Specific IgG Glycosylation in Colorectal Cancer
DescriptionChanges in IgG glycosylation have been reported to be associated with colorectal cancer (CRC), but the alteration in specific subclass of IgG is unknown. Herein, we optimized five common IgG glycopeptides enrichment methods to acquire comprehensive profiling of IgG glycoproteomics in CRC. Notably, incomplete tryptic digestion of IgG occurred when using ordinary ratio of protease to protein, which significantly impacted the final statistical analysis of association between IgG glycosylation and CRC. We introduced a method based on two-step enzymatic digestion, enabling the complete digestion of IgG glycopeptides and further improving the detection intensity of the target glycopeptides. By this approach, total 47 IgG glycopeptides can be identified by nanoLC-ESI-MS/MS. Following rapid and automatic data processing through the self-developed program, we observed that IgG1_H3N4F1 and IgG1_H3N4 were substantially increased in CRC, while IgG1_H5N5F1, IgG1_H5N4F1S1and IgG2_H5N4F1 were markedly decreased. Strikingly, these four glycopeptides were continually significantly changed in early and late stages of CRC. Further evaluation of the diagnostic performance showed they all obtained a fair performance in discriminating the patients from the normal. In terms of the glycan features, it demonstrated that CRC progression associates with the increased agalactosylation, and the decreased digalactosylation and galactosylation per antenna on diantennay glycans of IgG1 and IgG2. Concurrently, the decreased sialylation of IgG1 was strongly correlated with CRC. Moreover, tumor-specific glycosylation analysis showed that the alterations of subclass-specific IgG glycosylation were more significant in colon cancer, and no obvious difference between colon and rectal cancer was found. More importantly, all these findings were validated in an independent cohort. This two-step enzymatic approach is crucial to explore the relationship between the disease progression and IgG glycosylation.
HostingRepositoryPRIDE
AnnounceDate2023-11-14
AnnouncementXMLSubmission_2023-11-14_08:19:36.049.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterSi Liu
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationListNo PTMs are included in the dataset
InstrumentTripleTOF 5600
Dataset History
RevisionDatetimeStatusChangeLog Entry
02019-11-18 01:42:25ID requested
12022-10-27 05:22:04announced
22023-11-14 08:19:36announced2023-11-14: Updated project metadata.
Publication List
Liu S, Liu Y, Lin J, Wang Y, Li D, Xie GY, Guo AY, Liu BF, Cheng L, Liu X, Three Major Gastrointestinal Cancers Could Be Distinguished through Subclass-Specific IgG Glycosylation. J Proteome Res, 21(11):2771-2782(2022) [pubmed]
Keyword List
submitter keyword: Human, Serum IgG, Complete Tryptic Digestion, Colorectal, LC-MS/MS
Contact List
Xin Liu
contact affiliationDepartment of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, N0. 1037 Luoyudong Road, Hongshan District, Wuhan 430074
contact emailxliu@mail.hust.edu.cn
lab head
Si Liu
contact affiliationHuazhong University of Science and Technology
contact emailsiliu2019@163.com
dataset submitter
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Dataset FTP location
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