Uncovering potential interventions for pancreatic cancer patients via mathematical modeling

Daniel Plaugher, Boris Aguilar, David Murrugarra

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Pancreatic Ductal Adenocarcinoma (PDAC) is widely known for its poor prognosis because it is often diagnosed when the cancer is in a later stage. We built a Boolean model to analyze the microenvironment of pancreatic cancer in order to better understand the interplay between pancreatic cancer, stellate cells, and their signaling cytokines. Specifically, we have used our model to study the impact of inducing four common mutations: KRAS, TP53, SMAD4, and CDKN2A. After implementing the various mutation combinations, we used our stochastic simulator to derive aggressiveness scores based on simulated attractor probabilities and long-term trajectory approximations. These aggression scores were then corroborated with clinical data. Moreover, we found sets of control targets that are effective among common mutations. These control sets contain nodes within both the pancreatic cancer cell and the pancreatic stellate cell, including PIP3, RAF, PIK3 and BAX in pancreatic cancer cell as well as ERK and PIK3 in the pancreatic stellate cell. Many of these nodes were found to be differentially expressed among pancreatic cancer patients in the TCGA database. Furthermore, literature suggests that many of these nodes can be targeted by drugs currently in circulation. The results herein help provide a proof of concept in the path towards personalized medicine through a means of mathematical systems biology. All data and code used for running simulations, statistical analysis, and plotting is available on a GitHub repository at https://github.com/drplaugher/PCC_Mutations.

Original languageEnglish
Article number111197
JournalJournal of Theoretical Biology
Volume548
DOIs
StatePublished - Sep 7 2022

Bibliographical note

Funding Information:
The results shown here are in whole or part based upon data hosted by the Institute for Systems Biology Cancer Gateway in the Cloud (ISB-CGC) platform. ISB-CGC has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, Task Order No. 17X053 under Contract No. HHSN261200800001E. DM received funding from the Simons Foundation (850896).

Funding Information:
The results shown here are in whole or part based upon data hosted by the Institute for Systems Biology Cancer Gateway in the Cloud (ISB-CGC) platform. ISB-CGC has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, Task Order No. 17X053 under Contract No. HHSN261200800001E. DM received funding from the Simons Foundation (850896).

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

  • Boolean networks
  • Cytokines
  • Pancreatic cancer
  • Pancreatic stellate cells
  • Phenotype control

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology (all)
  • Immunology and Microbiology (all)
  • Agricultural and Biological Sciences (all)
  • Applied Mathematics

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