# Identification of multi-omic marker associations in pancreatic cancer

> **NIH NIH P20** · NORTH DAKOTA STATE UNIVERSITY · 2020 · $225,454

## Abstract

Abstract:
Identifying important epigenetic changes is a central challenge in the quest to create effective
treatment targets or useful biomarker panels which can be used to screen for susceptibilities to
complex, multi-factorial diseases like cancer. Developing an understanding of which epigenetic
variations are important in developing and progressing disease will enhance our knowledge of
disease mechanisms and improve our ability to predict disease and target interventions to high risk sub-populations. Pancreatic ductal adenocarcinoma (PDAC) has an extremely high
mortality/incidence ratio and poor 5-year survival rates about 7%, especially among non-respectable disease where mean survival is 3-6 months. For patients with early stage and resectable disease the mean survival is much better at 32 months. It is clear that early
detection is key for PDAC. Unfortunately, limited progress has been made identifying and
validated such epigenetic marker panels for PDAC in the epidemiological setting. Most
epigenome-wide studies (EWAS) rely on statistical evidence of effect alone and are often likely
to be underpowered to detect modest differences. In this proposal, we describe a two-stage
multi-omics approach that addresses the limitations of standard EWAS approaches and
provides validation of identified key networks. We will apply our approach using tumor samples
collected as part of the Mayo Clinic Pancreatic Cancer Resource. We propose to search for
differentiated epigenetic and genetic markers focusing on 12 key PDAC driver genes or
biological processes when comparing pancreatic cancer patient tumors or patient derived cell
lines to control tissue samples using existing public and Mayo Clinic datasets (Aim 1). Using
the identified network of epigenetic-genetic alterations, we will then test for significance in an
independent Mayo Clinic patient tumor set and build clinical variables into the model (Aim 2).
Our team is ideally suited to accomplish these aims, as we have conducted research on early
detection methods and genome-wide analyses in multiple disease conditions. We have
designed and managed numerous study types including cohort, case-control, and family
studies. Leveraging our experience in environmental, molecular, genetic, and cancer
epidemiology. We believe there is a great advantage in using publicly available data and
exploratory-based methods to analyze multiple types of genomic markers. This step is relatively
cost effective and efficient, as a way to improve power and resources in deeper analyses.
Additionally with this project, we will be creating a unique, high quality PDAC resource linking
tumor genomics and patient characteristics to be used in future research such as projects
focused on understanding PDAC progress and tumor treatment response. Our framework has
very high potential to be generalized to the analysis of other PDAC samples and other cancers
or disease types. Additionally, our results can provide other researchers with...

## Key facts

- **NIH application ID:** 10118382
- **Project number:** 5P20GM109024-05
- **Recipient organization:** NORTH DAKOTA STATE UNIVERSITY
- **Principal Investigator:** Rick J Jansen
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $225,454
- **Award type:** 5
- **Project period:** — → 2022-07-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10118382

## Citation

> US National Institutes of Health, RePORTER application 10118382, Identification of multi-omic marker associations in pancreatic cancer (5P20GM109024-05). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10118382. Licensed CC0.

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