# Using microvolumetric cyst fluid proteolysis for early detection of pancreatic cancer

> **NIH NIH U01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $812,450

## Abstract

ABSTRACT
Pancreatic cystic lesions (PCLs) are the only radiographically identifiable precursor to deadly pancreatic
carcinoma and they are detected in a million people annually in the U.S. Most patients with PCLs have
“indeterminate” cysts in which both the type and histologic grade are clinically and radiographically uncertain.
Currently used cyst fluid diagnostics suffer from poor accuracy and they typically require large volumes of
fluid that are unavailable in ~50% of cases, leading to both missed cancers and unnecessary major surgery.
In this proposal, we leverage our novel multiplex substrate profiling by mass spectrometry method combined
with proteomics to refine target proteins and then validate our two-tier classifier for the identification of
mucinous PCLs with high grade dysplasia or invasive carcinoma, together considered advanced neoplasia
(AN). The final clinical assay requires only 5 µL of fluid. A micro-volumetric assay is expected to improve the
diagnostic yield of cyst fluid testing from ~50% to >90% for patients who undergo routine invasive testing. The
Tier-1 classifier identifies mucinous PCLs, which carry variable risk of malignant transformation, thereby
potentially removing ~25% of patients with non-mucinous PCLs from the need for further surveillance or
surgery. We will validate the Tier-1 classifier with PCL samples from the Early Detection Research Network
(EDRN), a histologically diverse, well- annotated biorepository + untested samples from UCSF and UCLA. We
will further test and refine our Tier-2 classifier for the identification of AN using untested banked mucinous
PCLs from UCSF, and then validate it using external samples from the EDRN and prospectively collected
samples from UCSF and UCLA to prioritize detection of AN while minimizing the burdens of overtreatment.
We will also use our radiology search engine, mPower, to improve capture of “missed” patients with incidental
clinically relevant PCLs, and we will thereby expand the racial and ethnic diversity of our Panc Cyst Registry.
Our registry is a prospective longitudinal research resource that uses patient-directed input and includes
demographic and lifestyle information. Together these novel tools are expected to make a significant impact
on the management of “indeterminate” PCLs and improve the detection of early-stage pancreatic cancer,
while reducing the burdens of overdiagnosis and overtreatment.

## Key facts

- **NIH application ID:** 10867035
- **Project number:** 1U01CA282269-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Kimberly Saunders Kirkwood
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $812,450
- **Award type:** 1
- **Project period:** 2024-06-01 → 2029-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10867035

## Citation

> US National Institutes of Health, RePORTER application 10867035, Using microvolumetric cyst fluid proteolysis for early detection of pancreatic cancer (1U01CA282269-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10867035. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*