# Project 3: Transcriptomic subtypes, response predictions, and therapy selection

> **NIH NIH P50** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2022 · $471,647

## Abstract

PROJECT 3: ABSTRACT
FOLFIRINOX and gemcitabine plus nab-paclitaxel (GnP) have emerged as the first-line treatment for patients
with metastatic pancreatic cancer (PDAC). These two regimens have not been compared in the first-line
setting, and treatment selection is guided by physician choice. Among patients with metastatic PDAC who do
not respond to first-line FOLFIRINOX, a substantial proportion will have a robust response to second-line GnP.
This strongly suggests that there may be a subset of patients who may have significant clinical response to
GnP but not FOLFIRINOX. Matching patients to the most effective first-line therapy is a critical and unmet
need.
We have identified molecular subtypes of PDAC that are robust and replicable. Analysis from two clinical trials
has shown that the basal subtype does not respond to FOLFIRINOX-based therapies and emphasizes the
critical need to identify alternative treatments. Recent results have shown that patients with basal tumors are
more responsive to GnP compared to FOLFIRINOX. Based on our findings of subtype associated treatment
response, we developed a robust and replicable single-sample classifier (PurIST) that is now a CLIA-approved
assay, and will be used this proposal to prospectively evaluate whether the PurIST classifier can be used to
direct treatment selection.
Leveraging the strength of molecular subtyping expertise at the University of North Carolina at Chapel Hill and
the tremendous clinical infrastructure at the Medical College of Wisconsin’s Pancreatic Cancer Program, we
propose a clinical trial where PurIST subtyping will be used to direct the initial chemotherapy. To our
knowledge this will be the first trial to use molecular subtyping to direct treatment in the neoadjuvant setting.
Results from this trial will demonstrate if precision oncology approaches such as PurIST may help direct
treatment and improve outcome for patients that may otherwise be less responsive to either FOLFIRINOX or
GnP.
In parallel, we will determine if specific characteristics in the tumor and tumor microenvironment may predict
response to different therapies through innovative computational approaches of cutting edge trials. Finally,
through our novel proteomic approaches we have found that basal tumors have differential kinase profiles. We
show that effectiveness of kinases inhibitors in PDAC may have been overlooked as ~20% of PDAC patients
are basal, and that subtype-specific kinases may be promising targets.

## Key facts

- **NIH application ID:** 10334085
- **Project number:** 1P50CA257911-01A1
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Jen Jen Yeh
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $471,647
- **Award type:** 1
- **Project period:** 2022-09-16 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10334085

## Citation

> US National Institutes of Health, RePORTER application 10334085, Project 3: Transcriptomic subtypes, response predictions, and therapy selection (1P50CA257911-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10334085. Licensed CC0.

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