# Chemical Glycoproteomics

> **NIH NIH R01** · STANFORD UNIVERSITY · 2022 · $326,899

## Abstract

PROJECT SUMMARY
Mucins are densely O-glycosylated proteins with extended regions of clustered Ser/Thr-linked O-glycans, a
structural feature that imparts a rigid and extended conformation. Their range of biological functions include
physical stiffening of the glycocalyx to modulate cell survival in low adhesion settings, and biochemical
interactions with glycan-binding receptors on other cells. Altered mucin expression and glycosylation patterns
have been strongly linked to cancer progression. Crude measurements of these changes are currently used for
cancer diagnosis but are imperfect due to their lack of molecular-level detail. A detailed map of mucin O-glycan
structures and sites has been impossible to obtain, as mucins are recalcitrant to conventional mass
spectrometry-based glycoproteomics methods. As a consequence, the cellular pathways underlying aberrant
mucin structures are not well defined. We are pursuing these questions with the long-term goal of identifying
more accurate cancer biomarkers and new therapeutic targets.
During the previous funding period, we developed new mass spectrometry-based glycoproteomics methods and
used them in fundamental studies of the enzymes that initiate mucin-type O-glycosylation, the polypeptide
GalNAc transferases. Examples of our accomplishments include (i) development of the IsoTaG method for intact
glycoproteomics via isotopic recoding and mass-independent glycopeptide discovery; (ii) identification of an
optimal tandem mass spectrometry method for O-glycosite discovery; and (iii) development of a bump/hole
strategy to identify biological substrates of polypeptide GalNAc transferases that initiate mucin-type O-
glycosylation. In preliminary work for this application, we repurposed mucin-specific proteases (“mucinases”)
from gut-resident microbes as tools for mapping O-glycosites on mucin domains.
In the next funding period, we plan to develop a comprehensive “mucinomics” platform. We will use engineered
mucinases as glycoform-sensitive probes of mucin expression on cells and tissues. We will also develop a
mucinase-based enrichment strategy for mass spectrometry-based discovery of new mucin domain molecules
as well as O-glycosite mapping. Integrated into this workflow will be newly developed ionization methods and
search algorithms for O-glycosite identification. Finally, we will use the mucinomics platform to define pathways
by which prevalent oncogenes drive altered mucin expression and glycosylation in cancer.

## Key facts

- **NIH application ID:** 10378064
- **Project number:** 5R01CA200423-19
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Carolyn Bertozzi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $326,899
- **Award type:** 5
- **Project period:** 2002-08-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10378064

## Citation

> US National Institutes of Health, RePORTER application 10378064, Chemical Glycoproteomics (5R01CA200423-19). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10378064. Licensed CC0.

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