Library-based virtual match-between-runs quantification in GlyPep-Quant improves site-specific glycan identification Article Swipe
He Zhu
,
Zheng Fang
,
Lei Liu
,
Yan Wang
,
Hongqiang Qin
,
Yongzhan Nie
,
Mingming Dong
,
Mingliang Ye
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41467-025-61673-6
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41467-025-61673-6
Glycosylation changes are closely related to various diseases, including cancer. The quantitative analysis of site-specific glycans at proteomics scale remains challenging due to low glycopeptide spectra interpretation. Here, we present GlyPep-Quant, a tool for sensitive quantification and identification of site-specific glycans. Using a well-trained machine learning model, GlyPep-Quant quantified 25.1%-178.9% more site-specific glycans without missing values than pGlycoQuant, MSFragger-Glyco, and Skyline. To utilize identified information from previous large-scale dataset, an MS1 feature library-based "virtual match-between-runs" quantification scheme was developed, enabling over eightfold more site-specific glycan identification/quantification than conventional MS2-based methods. Enhanced coverage prompted the development of a glycoproteomic biomarker discovery method, involving calculation of site-specific glycan abundances ratios at the same glycosylation site, minimizing individual expression and experimental condition variability. Two pairs of site-specific glycan ratios on sites P01011-N127 and P08185-N96, were selected as high-performance biomarkers to classify gastric cancer (GC) from healthy controls (AUC > 0.95). Moreover, the two ratios performed well in distinguishing GC using an independent cohort by the library-based quantification strategy with diagnostic accuracy up to 85%. GlyPep-Quant is poised for broader glycoproteomic applications.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41467-025-61673-6
- https://www.nature.com/articles/s41467-025-61673-6.pdf
- OA Status
- gold
- Cited By
- 1
- References
- 59
- Related Works
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- OpenAlex ID
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https://openalex.org/W4412395621Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1038/s41467-025-61673-6Digital Object Identifier
- Title
-
Library-based virtual match-between-runs quantification in GlyPep-Quant improves site-specific glycan identificationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-07-14Full publication date if available
- Authors
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He Zhu, Zheng Fang, Lei Liu, Yan Wang, Hongqiang Qin, Yongzhan Nie, Mingming Dong, Mingliang YeList of authors in order
- Landing page
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https://doi.org/10.1038/s41467-025-61673-6Publisher landing page
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https://www.nature.com/articles/s41467-025-61673-6.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.nature.com/articles/s41467-025-61673-6.pdfDirect OA link when available
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Glycan, Identification (biology), Computational biology, Computer science, Biology, Genetics, Glycoprotein, BotanyTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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59Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.methods. | 89 |
| abstract_inverted_index.previous | 66 |
| abstract_inverted_index.prompted | 92 |
| abstract_inverted_index.selected | 132 |
| abstract_inverted_index.strategy | 164 |
| abstract_inverted_index.MS2-based | 88 |
| abstract_inverted_index.Moreover, | 147 |
| abstract_inverted_index.biomarker | 98 |
| abstract_inverted_index.condition | 118 |
| abstract_inverted_index.discovery | 99 |
| abstract_inverted_index.diseases, | 7 |
| abstract_inverted_index.eightfold | 81 |
| abstract_inverted_index.including | 8 |
| abstract_inverted_index.involving | 101 |
| abstract_inverted_index.performed | 151 |
| abstract_inverted_index.sensitive | 34 |
| abstract_inverted_index.abundances | 106 |
| abstract_inverted_index.biomarkers | 135 |
| abstract_inverted_index.developed, | 78 |
| abstract_inverted_index.diagnostic | 166 |
| abstract_inverted_index.expression | 115 |
| abstract_inverted_index.identified | 63 |
| abstract_inverted_index.individual | 114 |
| abstract_inverted_index.minimizing | 113 |
| abstract_inverted_index.proteomics | 17 |
| abstract_inverted_index.quantified | 48 |
| abstract_inverted_index.P01011-N127 | 128 |
| abstract_inverted_index.P08185-N96, | 130 |
| abstract_inverted_index.calculation | 102 |
| abstract_inverted_index.challenging | 20 |
| abstract_inverted_index.development | 94 |
| abstract_inverted_index.independent | 158 |
| abstract_inverted_index.information | 64 |
| abstract_inverted_index.large-scale | 67 |
| abstract_inverted_index.25.1%-178.9% | 49 |
| abstract_inverted_index.GlyPep-Quant | 47, 171 |
| abstract_inverted_index.conventional | 87 |
| abstract_inverted_index.experimental | 117 |
| abstract_inverted_index.glycopeptide | 24 |
| abstract_inverted_index.pGlycoQuant, | 57 |
| abstract_inverted_index.quantitative | 11 |
| abstract_inverted_index.variability. | 119 |
| abstract_inverted_index.well-trained | 43 |
| abstract_inverted_index.GlyPep-Quant, | 30 |
| abstract_inverted_index.Glycosylation | 0 |
| abstract_inverted_index.applications. | 177 |
| abstract_inverted_index.glycosylation | 111 |
| abstract_inverted_index.library-based | 72, 162 |
| abstract_inverted_index.site-specific | 14, 39, 51, 83, 104, 123 |
| abstract_inverted_index.distinguishing | 154 |
| abstract_inverted_index.glycoproteomic | 97, 176 |
| abstract_inverted_index.identification | 37 |
| abstract_inverted_index.quantification | 35, 75, 163 |
| abstract_inverted_index.interpretation. | 26 |
| abstract_inverted_index.MSFragger-Glyco, | 58 |
| abstract_inverted_index.high-performance | 134 |
| abstract_inverted_index.match-between-runs" | 74 |
| abstract_inverted_index.identification/quantification | 85 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.82790947 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |