# Genetic Determinants of Evolutionary Trajectories and Clinical Course in Pancreatic Cancer

> **NIH NIH F31** · SLOAN-KETTERING INST CAN RESEARCH · 2022 · $46,752

## Abstract

PROJECT SUMMARY
Genetic intratumoral heterogeneity (gITH) has been associated with cancer progression and is thought to be a
major contributor to treatment resistance. However, the extent to which different genetic drivers that arise during
carcinogenesis specifically influence subsequent evolutionary trajectories and clinical course remains unknown.
Some cancer types with a protracted clinical course, e.g. clear cell renal cell carcinoma, generally follow a
Darwinian growth pattern, displaying extensive gITH characterized by heterogeneous somatic mutations and
multiple subclonal drivers. By contrast, aggressive tumor types such as pancreatic ductal adenocarcinoma
(PDAC) characteristically have multiple clonal driver events consisting of both somatic coding mutations and
copy number alterations, and subsequent evolutionary trajectories appear genetically restrained. However, both
tumor types contain outliers for which different genetic features and clinical courses have been observed.
Ultimately, a deep understanding of evolutionary trajectories within and across multiple tumor types, as well as
before and after treatment may distinguish patients with more indolent disease biology or oligometastatic
progression from those with more rapid dissemination and clinical courses. Such insights have the potential to
facilitate clinical trial stratification and disease management.
 The aim of this project is to determine the extent to which diversity and evolutionary timing of driver gene
mutations impacts clinical disease course in a single cancer type, PDAC. While there are known driver genes in
PDAC, the extent to which the quantity, quality, or chronology of these drivers impacts tumor evolution remains
unclear. Therefore, we will perform bulk and single cell DNA sequencing on multiregion sampled human PDACs
to assess gITH. Unlike traditional biopsies, multiregion sampling is more comprehensive and helps to eliminate
false negative and false positive conclusions regarding whether a particular mutation is present at a given site.
In-depth analyses of subclones will be performed using multiple computational methods and phylogenetic trees
will be reconstructed for individual patients’ cancers. These data will then be correlated with various metrics of
clinical disease course, including stage at diagnosis, overall survival, treatment status, mode of treatment, and
metastatic burden when such information is available. By improving our understanding of a tumor’s subclonal
architecture, we anticipate that this knowledge will help improve risk predictions regarding disease relapse and
the metastatic cascade. Additionally, identifying genetic factors that allow minor subclones to support or restrict
tumor growth may provide new opportunities for targeted intervention and tumor control.

## Key facts

- **NIH application ID:** 10372953
- **Project number:** 5F31CA260796-02
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** Katelyn Mullen
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $46,752
- **Award type:** 5
- **Project period:** 2021-04-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10372953

## Citation

> US National Institutes of Health, RePORTER application 10372953, Genetic Determinants of Evolutionary Trajectories and Clinical Course in Pancreatic Cancer (5F31CA260796-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10372953. Licensed CC0.

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