# Single Cell Deconvolution of the Pancreatic Tumor Microenvironment

> **NIH NIH F30** · STATE UNIVERSITY NEW YORK STONY BROOK · 2021 · $37,571

## Abstract

Project Summary/Abstract:
 Pancreatic ductal adenocarcinoma (PDAC) maintains its status as one of most lethal solid cancers with
a 5-year survival of 8%. Minor improvements have been attributed to early detection, but the vast majority of
patients face a grim prognosis without effective therapeutic intervention. Molecular analysis of patient samples
has often been confounded by mixed biological samples, leading to reproducibility challenges. Previously, our
lab performed virtual microdissection on bulk RNA-seq patient samples establishing robust prognostic gene
signatures describing an aggressive basal-like and drug-responsive classical tumor subtypes highlighting the
importance of cancer heterogeneity across patients. Using these signatures as patient classifiers has been an
important utility in preliminary clinical trials and therapeutic profiling of patient derived organoids.
 Building evidence suggests patient unique TME composition impacts PDAC progression and resistance
to standard treatments. While patient tissue characterization with bulk measurements has provided key insights
into cancer biology, parsing the complex tumor microenvironments requires higher resolution due to the
widespread stromal involvement and sparse neoplastic populations. Single-cell sequencing delivers the
analytical power to help identify variable TME elements between patients that lead to the distinct prognostic and
therapeutic responses. Thus, understanding the extent and role of TME heterogeneity in PDAC across patient
tumor subtypes is paramount to widen the door for personalized medicine in oncology.
 In this proposal, I will establish a comprehensive single-cell atlas of human PDAC TME to significantly
lower the barrier between researchers and complex single-cell transcriptomics data to explore novel prognostic
and synergistic therapeutic targets. I will use local and public single cell RNA-seq data of PDAC tissue to
investigate the extent and role of cellular heterogeneity across patient tumor subtypes. Specifically, I will define
molecular signatures and map out the interactome of functional cell types within stromal, lymphocytic, myeloid
populations at unprecedented spatial resolution. Ultimately, by integrating high-dimensional data from single-cell
RNA-seq and Spatial Transcriptomics, this work will shed light on the intricate tissue pathology while laying down
a broad framework for understanding multi-axis cell interactions behind progression and resistance in diverse
cancer types.

## Key facts

- **NIH application ID:** 10151142
- **Project number:** 1F30CA257489-01
- **Recipient organization:** STATE UNIVERSITY NEW YORK STONY BROOK
- **Principal Investigator:** Ki Oh
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $37,571
- **Award type:** 1
- **Project period:** 2020-12-09 → 2024-12-08

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10151142

## Citation

> US National Institutes of Health, RePORTER application 10151142, Single Cell Deconvolution of the Pancreatic Tumor Microenvironment (1F30CA257489-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10151142. Licensed CC0.

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