# Single Cell Dissection of Epigenetic and Tumor Ecosystem Dynamics During Pancreatic Cancer Progression

> **NIH NIH F31** · WEILL MEDICAL COLL OF CORNELL UNIV · 2022 · $27,186

## Abstract

Project Summary
Previous studies of Pancreatic Ductal Adenocarcinoma (PDAC) have failed to inform treatment
strategies providing sizeable improvements in patient outcomes, and as such this disease is
predicted to be the second leading cause of cancer –related death by the year 2020. A major
reason for this shortcoming stems from the extensive cellular heterogeneity that arises during
PDAC tumorigenesis, which is largely ignored by bulk genomic studies. I hypothesize that a
single cell dissection of the epithelial compartment and tumor ecosystem along disease
progression will reveal novel druggable targets and clarify the specific cellular drivers of the
disease. I further hypothesize that integration of transcriptional and epigenetic data within
computational frameworks will improve the prospects of target detection, as initial evidence
suggests a strong impact of epigenetic dysregulation on tumorigenesis. To this end, the
proposed project leverages single cell transcriptomic (scRNA-seq) and bulk chromatin
accessibility measurements (ATAC-seq) collected in collaboration with the Scott Lowe lab from
genetically engineered mice modeling PDAC progression from the moment of initiation through
metastasis. For my doctoral research, I propose to develop and apply novel computational
methodology to integrate scRNA-seq and ATAC-seq to infer cell type –specific regulatory
programs in subpopulations of PDAC, such that we may identify dysregulated mechanisms
comparing to normal pancreas epithelium (Aim 1). I then propose to model dynamics of
phenotypic shifts over the time course of PDAC progression with a novel method to orient
“velocity” of cellular states, again drawing information from both epigenetic and transcriptomic
data (Aim 2). This latter aim will allow identification of potential stem cell populations and the
phenotypes they give rise to, thus providing a basis for targeting populations driving recurrence
or resistance to treatment. In summary, our proposed approach to studying regulation in cancer
will provide predictions which are unobtainable with existing methods based on either bulk data
or single cell data alone, and which are well-poised to uncover cancer regulators in particular
phenotypic niches.

## Key facts

- **NIH application ID:** 10437591
- **Project number:** 5F31CA246901-03
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** Cassandra Burdziak
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $27,186
- **Award type:** 5
- **Project period:** 2020-06-28 → 2022-10-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10437591

## Citation

> US National Institutes of Health, RePORTER application 10437591, Single Cell Dissection of Epigenetic and Tumor Ecosystem Dynamics During Pancreatic Cancer Progression (5F31CA246901-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10437591. Licensed CC0.

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