# Identifying lethal prostate cancer at diagnosis with advanced proteoglycomic, radiomic, and genomic approaches

> **NIH NIH R01** · WASHINGTON UNIVERSITY · 2024 · $592,860

## Abstract

PROJECT SUMMARY
Conventional prostate adenocarcinoma (PCa) is the second leading cause of cancer death in American men.
Patients with organ-confined disease are candidates for potentially curative treatment by either radical
prostatectomy or radiation therapy. However, 20-40% of patients undergoing radical prostatectomy and 30-50%
of patients undergoing radiation therapy can experience biochemical recurrence within 10 years. These findings
indicate that there is suboptimal identification of lethal PCa at the time of diagnosis. Therefore, identification of
aggressive disease at the time of diagnosis could stratify patients, develop more effective therapy options, and
extend survival. In the clinical setting, noninvasive imaging biomarkers are routinely measured with
multiparametric magnetic resonance imaging (mpMRI). However, mpMRI has multiple limitations that result in
reduced sensitivity and specificity for PCa, in part from obscuration from inflammatory or stromal cells in the
prostate. This proposal advances the use of a clinical magnetic resonance imaging (MRI) sequence, diffusion
basis spectral imaging (DBSI), that has the ability to detect structural and cellular changes in the PCa
microenvironment (e.g., stroma, inflammation, tumor), that cannot otherwise be determined with conventional
mpMRI, a significant advancement. In parallel, our team has discovered a panel of extracellular proteoglycomic
biomarkers in lethal forms of PCa (i.e., fucosylated glycans and modified collagens—“FuCol” biomarkers) with
Matrix Assisted Laser Desorption Ionization (MALDI) mass spectrometry imaging of histologic specimens. These
molecular markers provide insight into the structural derangements of lethal PCa and because structural changes
affect water diffusion, it suggests that these structural changes may actually be detectable with DBSI. We
hypothesize that MALDI-detected proteoglycomic markers, expressed as the FuCol score, are associated with
structural and metabolic changes in lethal PCa that can be visualized with DBSI to better identify aggressive,
potentially lethal PCa at the time of diagnosis. In the first Aim, we will continue to validate our FuCol score as a
predictor of disease recurrence and metastasis in a large institutional biorepository. In this Aim, we will
investigate the effects of race and diet on the FuCol score and its ability to predict poor outcomes. We will also
establish the ability to measure a FuCol score as part of a “noninvasive liquid biopsy” to predict outcomes. In
Aim 2, we will enroll a prospective cohort of prostatectomy patients to develop “Diffusion Molecular Imaging
(DMI)”; an AI-driven tool that generates in vivo FuCol scores using in vivo DBSI as its input prior to prostatectomy,
hence a non-invasive imaging readout of lethal disease. In Aim 3, we will develop an augmented risk prediction
model that incorporates novel DBSI imaging, the clinical Decipher genomics platform, and conventional clinical
metrics (grade, st...

## Key facts

- **NIH application ID:** 10884411
- **Project number:** 5R01CA282022-02
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Joseph Edward Ippolito
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $592,860
- **Award type:** 5
- **Project period:** 2023-07-07 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10884411

## Citation

> US National Institutes of Health, RePORTER application 10884411, Identifying lethal prostate cancer at diagnosis with advanced proteoglycomic, radiomic, and genomic approaches (5R01CA282022-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10884411. Licensed CC0.

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