# Stratification of Pancreatic Cancer Subpopulations for Effective Immunotherapy

> **NIH VA I01** · MICHAEL E DEBAKEY VA MEDICAL CENTER · 2020 · —

## Abstract

As the risk for pancreatic ductal adenocarcinoma (PDAC) has increased to a higher rate
in veterans relative to that in the general population, there is an urgent need to develop effective
therapies to treat PDAC for veterans in the VA system. Recently, cancer immunotherapy has
shown great promise in several cancers, but not in PDAC. Part of the reason for this is the
heterogeneity of PDAC and lack of tailoring of immunotherapy to individual tumor subtypes.
PDAC patient stratification for therapy remains in its infancy, and a reliable method to
deconvolute complex tumor composition to stratify PDAC subtypes has not been recognized.
Recently, we participated in whole genome sequencing of PDAC specimens, which provides the
basis for classifying PDAC into four subtypes based upon patterns of genomic structural
variation (Nature, 2016). Among these, the immunogenic subtype accounts for 30% of 178
PDAC samples in the TCGA database and is characterized by upregulated immune cell
networks, which could indicate differential responses to immunotherapy. In addition, the
Epigenomic Deconvolution (EDec) method, first developed by our co-investigator Dr.
Milosavljevic’s group, provides valuable information about cell type composition of tumors and
cell-type specific gene expression (Cell Rep. 2016). When applied to immunogenic subtype
PDAC tumors, EDec reveals an immunosuppressive microenvironment characterized by the
highest Foxp3 expression among all four subtypes. Cancer cells falling into the immunogenic
subtype also show the highest mesothelin (MSLN) expression. Therefore, we hypothesize that
PDACs with an immunogenic profile could be a target subgroup that is responsive to
immunotherapy either by MSLN virus-like particle (VLP) vaccination or combination therapy of
VLPs and an immune checkpoint inhibitor. We will test our hypothesis in pre-clinical animal
models that best recapitulate human PDAC patient’s response to immunotherapy, including
patient-derived tumor xenografts (PDX) and humanized mouse models. Our preliminary data
have shown that our anti-MSLN VLP vaccine is effective against MSLN-high expressing PDX in
a humanized NSG mouse model (PDX-hu-NSG). Based on our strong preliminary results, we
propose to develop an effective cancer immunotherapeutic approach by combining three highly
synergistic innovations: (1) A novel epigenetic deconvolution method to stratify PDAC tumors;
(2) PDX-hu-NSG models; and (3) Combination therapy of MSLN-VLP vaccine plus anti-PD-1
antibody. We propose two specific aims. In Aim 1, we will determine whether the immunogenic
subtype of PDAC is responsive to MSLN-VLP vaccine in PDX-hu-NSG model. Here, we will
use EDec method to stratify VA PDACs by subtype and then determine MSLN-VLP vaccine
efficacy in specific PDAC subgroups in humanized PDX mouse model. In Aim 2, we will
determine whether combination therapy with anti-PD-1 Ab enhances MSLN VLP vaccine
responses and efficacy in onco-humice model. We will also determine s...

## Key facts

- **NIH application ID:** 9780735
- **Project number:** 1I01CX001822-01A2
- **Recipient organization:** MICHAEL E DEBAKEY VA MEDICAL CENTER
- **Principal Investigator:** Qizhi C. Yao
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2020-01-01 → 2024-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9780735

## Citation

> US National Institutes of Health, RePORTER application 9780735, Stratification of Pancreatic Cancer Subpopulations for Effective Immunotherapy (1I01CX001822-01A2). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9780735. Licensed CC0.

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