# Hypoxia-derived molecular MSI signatures to predict breast cancer outcome

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2021 · $266,417

## Abstract

Project Summary
The overall goal of this application is to develop hypoxia-derived prognostic biomarkers to predict breast
cancer progression and patient outcome from human breast cancer tissue samples. In a previous NIH-funded
project, have identified hypoxia-driven signaling networks in the breast tumor microenvironment (TME) through
multimodal imaging combined with omics approaches in preclinical models. The breast TME contains several
spatially heterogeneous hypoxic regions, which induce metastasis and drive angiogenesis, invasion, altered
metabolism, and resistance to radiation and chemotherapy. Hypoxic tumor regions are also known to select for
aggressive cancer phenotypes with the highest capacity for metastatic spread. We have identified significantly
changed molecular signatures in hypoxic tumor regions in human breast tumor xenograft models, with
confirmed lists and networks of metabolites, lipids, and proteins that are significantly altered. We propose to
now build on these studies by developing fast reproducible clinical sample preparation and mass spectrometry
imaging (MSI) protocols that allow for high throughput use in clinical pathology laboratories and seamlessly
integrate with histology and immunohistochemistry. We will test in large cohorts of human breast cancer tissue
samples if hypoxic metabolome, lipidome, and proteome signatures have prognostic clinical value. To this end,
we will employ innovative multi-enzyme on-tissue digestion for proteins and glycans, reactive desorption
electrospray ionization (DESI) for enhanced metabolic marker discovery, and MSI-based Ozonolysis (OzID) for
on-the-fly lipid isomer imaging. In Aim 2, we will use these MSI approaches for analyzing tissue microarrays
with biopsies from the primary tumors of over 1,000 breast cancer patients to test if hypoxic molecular
signatures can predict patient outcome, recurrence, and 5-year-survival. In Aim 3, we will address the most
life-threatening aspect of breast cancer, the formation of metastases, and investigate if hypoxic regions in
primary human breast tumors are driving the development of metastases. The proposed research will identify
key molecular networks through which hypoxia drives breast cancers towards worse outcome and metastasis.
Recent developments in MSI have significantly improved its imaging speed, making it now possible to perform
MSI-based molecular pathology in clinically relevant times. This enables us to translate the results of our
earlier studies on the effect of hypoxia in the breast TME directly to large patient cohorts. We will clinically
evaluate matrix-assisted laser desorption/ionization (MALDI) MSI as diagnostic tool in conjunction with the
routine clinical pathology workup for accurate molecular prognosis of breast cancers. The large-scale
metabolite and lipid signatures obtained in our application will support the emerging use of ambient ionization
MSI applications for accurate intraoperative margin detection during breas...

## Key facts

- **NIH application ID:** 10227792
- **Project number:** 5R01CA213492-05
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Kristine Glunde
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $266,417
- **Award type:** 5
- **Project period:** 2017-08-15 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10227792

## Citation

> US National Institutes of Health, RePORTER application 10227792, Hypoxia-derived molecular MSI signatures to predict breast cancer outcome (5R01CA213492-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10227792. Licensed CC0.

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