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Re-analysis of glycoproteomics data with Glyco-Decipher

ABSTRACT: Reanalysis of submissions PXD005411, PXD005413, PXD005412, PXD005553, PXD005555, PXD005565 and PXD019937 using Glyco-Decipher. Identification results of peptide-spectrum matches supporting Glyco-Decipher manuscript (Glyco-Decipher: glycan database-independent peptide matching enables discovery of new glycans and in-depth characterization of site-specific N-glycosylation). Recently, several elegant bioinformatics tools have been developed to identify glycopeptides from tandem mass spectra for site-specific glycoproteomics studies. These glycan database-dependent tools have substantially improved glycoproteomics analysis but fail to identify glycopeptides with unexpected glycans. We present a platform called Glyco-Decipher to interpret the glycoproteomics data of N-linked glycopeptides. It adopts a glycan database-independent peptide matching scheme that allows the unbiased profiling of glycans and the discovery of new glycans linked with modifications. Reanalysis of several large-scale datasets showed that Glyco-Decipher outperformed the open search method in glycan blind searching and the popular glycan database-dependent software tools in glycopeptide identification. Our glycan database-independent search also revealed that modified glycans are responsible for a large fraction of unassigned glycopeptide spectra in shotgun glycoproteomics.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Saccharomyces Cerevisiae (baker's Yeast) Mus Musculus (mouse)

TISSUE(S): Heart, Brain, Lung, Liver, Kidney

SUBMITTER: Zheng Fang

LAB HEAD: Mingliang Ye

PROVIDER: PXD031032 | Pride | 2022-03-04

REPOSITORIES: Pride

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Project description:BACKGROUND: Novel biomarkers are urgently needed to distinguish between benign and malignant thyroid nodules and detect thyroid cancer in the early stage. The associations between serum IgG N-glycosylation and thyroid cancer risk have been revealed. We aimed to explore the potential of IgG N-glycan traits as biomarkers in the differential diagnosis of thyroid cancer.METHODS: Plasma IgG N-glycome analysis was applied to a discovery cohort followed by independent validation. IgG N-glycan profiles were obtained using a robust quantitative strategy based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. IgG N-glycans were relatively quantified, and classification performance was evaluated based on directly detected and derived glycan traits.RESULTS: Four directly detected glycans were significantly changed in thyroid cancer patients compared to that in non-cancer controls. Derived glycan traits and a classification glycol-panel were generated based on the directly detected glycan traits. In the discovery cohort, derived trait BN (bisecting type neutral N-glycans) and the glyco-panel showed potential in distinguishing between thyroid cancer and non-cancer controls with AUCs of 0.920 and 0.917, respectively. The diagnostic potential was further validated. Derived trait BN and the glycol-panel displayed “accurate” performance (AUC>0.8) in discriminating thyroid cancer from benign thyroid nodules and healthy controls in the validation cohort. Meanwhile, derived trait BN and the glycol-panel also showed diagnostic potential in detecting early-stage thyroid cancer.CONCLUSIONS: IgG N-glycome analysis revealed N-glycomic differences that allow classification of thyroid cancer from non-cancer controls. Our results suggested that derived trait BN and the classification glyco-panel rather than single N-glycans may serve as candidate biomarkers for further validation.

Project description:Various cancers such as colorectal cancer (CRC) are associated with alterations in protein glycosylation. CRC cell lines are frequently used to study these (glyco)biological changes and their mechanisms. However, differences between CRC cell lines with regard to their glycosylation have hitherto been largely neglected. Here, we comprehensively characterized the N-glycan profiles of 25 different CRC cell lines, derived from primary tumors and metastatic sites, in order to investigate their potential as glycobiological tumor model systems and to reveal glycans associated with cell line phenotypes. We applied an optimized, high-throughput membrane-based enzymatic glycan release for small sample amounts. Released glycans were derivatized to stabilize and differentiate between a2,3- and a2,6-linked N-acetylneuraminic acids, followed by N-glycosylation analysis by MALDI-TOF(/TOF)-MS. Our results showed pronounced differences between the N-glycosylation patterns of CRC cell lines. CRC cell line profiles differed from tissue-derived N-glycan profiles with regard to their high-mannose N-glycan content but showed a large overlap for complex type N-glycans, supporting their use as a glycobiological cancer model system. Importantly, we could show that the high-mannose N-glycans did not only occur as intracellular precursors but were also present at the cell surface. The obtained CRC cell line N-glycan features were not clearly correlated with mRNA expression levels of glycosyltransferases, demonstrating the usefulness of performing the structural analysis of glycans. Finally, correlation of CRC cell line glycosylation features with cancer cell markers and phenotypes revealed an association between highly fucosylated glycans and CDX1 and/or villin mRNA expression that both correlate with cell differentiation. Together, our findings provide new insights into CRC-associated glycan changes and setting the basis for more in-depth experiments on glycan function and regulation.

Project description:Dysregulation of glyco-gene expression in cancer can lead to aberrant glycans and glycoconjugates, which in turn can promote tumorigenesis. Cervical cancer display augmentation of aberrant sialylated glycans and increase of glyco-genes, which encoded enzymes participate in the sialylation pathways. Besides sialiltranferases, other glyco-genes, analyzed individually are reported as altered in cervical cancer. Here we show a comprehensive analysis of glyco-gene expression in cervical cancer to obtain a wide scenery of global changes in glycosylation pathways. First, we compared glyco-gene expression between normal tissue and cervical cancer. Second, we analyzed the glycogene expression in subtypes of cc to obtain hallmarks of glyco-gene expression in each case. Our results indicate that in cervical cancer the GPI-anchored biosynthesis is increased in cc while the synthesis of chondroitin and dermatan sulfate are decreased. Moreover, data show that adenocarcinoma displayed a homogenous glyco-gene expression pattern, where chondroitin /dermatan sulfate and heparan sulfate glycogenes are decreased, while keratan sulfate genes are increased. Dysregulation of glyco-gene expression in cancer can lead to aberrant glycans and glycoconjugates, which in turn can promote tumorigenesis. Cervical cancer display augmentation of aberrant sialylated glycans and increase of glyco-genes, which encoded enzymes participate in the sialylation pathways. Besides sialiltranferases, other glyco-genes, analyzed individually are reported as altered in cervical cancer. Here we show a comprehensive analysis of glyco-gene expression in cervical cancer to obtain a wide scenery of global changes in glycosylation pathways. First, we compared glyco-gene expression between normal tissue and cervical cancer. Second, we analyzed the glycogene expression in subtypes of cc to obtain hallmarks of glyco-gene expression in each case. Our results indicate that in cervical cancer the GPI-anchored biosynthesis is increased in cc while the synthesis of chondroitin and dermatan sulfate are decreased. Moreover, data show that adenocarcinoma displayed a homogenous glyco-gene expression pattern, where chondroitin /dermatan sulfate and heparan sulfate glycogenes are decreased, while keratan sulfate genes are increased.

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Re-analysis of glycoproteomics data with Glyco-Decipher

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