# Translational Applications in an Animal Model of Pancreatic Cystic Neoplasm and Cancer

> **NIH NIH R01** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2020 · $597,598

## Abstract

ABSTRACT
Pancreatic ductal adenocarcinoma (PDAC) has a median 5-year survival of only 8%, and early diagnosis of
PDAC is an area of highest priority for the NCI. Amongst the best-recognized risk factors for PDAC are mucinous
pancreatic cysts, of which the most common subtype is known as intraductal papillary mucinous neoplasm
(IPMN). Currently, IPMN patients either undergo surgical resection due to “worrisome” imaging features, or are
followed conservatively by serial imaging studies for risk of progression to invasive PDAC. Unfortunately, the
imaging criteria reflexing patients to surgery are imperfect, leading to both over- and under-treatment of IPMNs.
Further, there are no credentialed blood-based biomarkers with a sensitivity and specificity that warrants reliable
therapeutic stratification. Our group has identified oncogenic mutations of KRAS and GNAS as the two most
common driver mutations in IPMNs – one or other is present in ~96% of cases. We have now engineered the
first animal model of IPMN that harbors the mutational combination (Kras;Gnas) found most commonly in the
cognate human disease. Upon doxycycline induction, the Kras;Gnas mice uniformly develop cystic lesions by 6
weeks, with progression to invasive cancer in 25% of mice by 21 weeks, mimicking the multistep progression of
human IPMN to PDAC. The objective of this proposal is to enhance the translational applicability of this model
by using it as a controlled platform to address key unmet needs in the management of IPMNs in two areas:
imaging correlates and circulating biomarkers. In Aim 1, we will use the animal model to investigate two novel
imaging platforms – quantitative feature extraction from MRI scans using an indigenously developed algorithm
known as “Enhancement Pattern Mapping” (EPM) and second, hyperpolarized MRI (HPMRI), in order to
determine imaging correlates that coincide with the transition from low grade IPMN to cancer. In Aim 2, we will
use a combination of unbiased mass spectrometry and array-based approaches to identify circulating proteins
and autoantibodies, respectively that correlate with progression of murine IPMNs to PDAC. In addition, we will
examine the potential of genomic liquid biopsies for cancer prediction, through utilizing an ultrasensitive and
quantitative droplet digital PCR (ddPCR) platform for detection of mutant KRAS and GNAS DNA within circulating
exosomes. All three classes of blood-based biomarkers (proteins, autoantibodies and exoDNA) will be assessed
in matched murine plasma samples, which will allow us to estimate the additive performance for cancer detection
using robust statistical paradigms. Both aims will benefit from ready access to imaging scans and biospecimens
from IPMN patients for cross-species translational validation studies, through NCI-funded multicenter U01
consortia that are led by the PI. We believe this multidisciplinary proposal has the potential for long-term impact
on PDAC mortality through practice changing a...

## Key facts

- **NIH application ID:** 9904574
- **Project number:** 5R01CA218004-03
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** ANIRBAN MAITRA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $597,598
- **Award type:** 5
- **Project period:** 2018-04-04 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9904574

## Citation

> US National Institutes of Health, RePORTER application 9904574, Translational Applications in an Animal Model of Pancreatic Cystic Neoplasm and Cancer (5R01CA218004-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9904574. Licensed CC0.

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