Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling

View ORCID ProfileMohammad Mazharul Islam, Andrea Goertzen, Pankaj K. Singh, Rajib Saha
doi: https://doi.org/10.1101/2021.07.14.452356
Mohammad Mazharul Islam
1Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mohammad Mazharul Islam
Andrea Goertzen
1Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Pankaj K. Singh
2Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198
3Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, NE 68198
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rajib Saha
1Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: rsaha2@unl.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a major research focus due to its poor therapy response and dismal prognosis. PDAC cells adapt their metabolism efficiently to the environment to which they are exposed, often relying on diverse fuel sources depending on availability. Since traditional experimental techniques appear exhaustive in the search for a viable therapeutic strategy against PDAC, in this study, a highly curated and omics-informed genome-scale metabolic model of PDAC was reconstructed using patient-specific transcriptomic data. From the analysis of the model-predicted metabolic changes, several new metabolic functions were explored as potential therapeutic targets against PDAC in addition to the already known metabolic hallmarks of pancreatic cancer. Significant downregulation in the peroxisomal fatty acid beta oxidation pathway reactions, flux modulation in the carnitine shuttle system, and upregulation in the reactive oxygen species detoxification pathway reactions were observed. These unique metabolic traits of PDAC were then correlated with potential drug combinations that can be repurposed for targeting genes with poor prognosis in PDAC. Overall, these studies provide a better understanding of the metabolic vulnerabilities in PDAC and will lead to novel effective therapeutic strategies.

Author summary Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, with late diagnosis, early metastasis, insufficient therapy response, and very low survival rates. Due to these challenges associated with the diagnosis and treatment of PDAC, it has been a research area of interest. With the goal of understanding the metabolic reprogramming in proliferating PDAC cells, we reconstructed healthy and PDAC models by incorporating patient transcriptomic data into a genome-scale global human metabolic model. Comparing the metabolic flux space for the reactions in the two context-specific models, we identified significantly divergent pathways in PDAC. These results allowed us to further investigate growth-limiting genes in PDAC and identify potential drug combinations that can be repositioned for treatment of PDAC.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted July 15, 2021.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling
Mohammad Mazharul Islam, Andrea Goertzen, Pankaj K. Singh, Rajib Saha
bioRxiv 2021.07.14.452356; doi: https://doi.org/10.1101/2021.07.14.452356
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling
Mohammad Mazharul Islam, Andrea Goertzen, Pankaj K. Singh, Rajib Saha
bioRxiv 2021.07.14.452356; doi: https://doi.org/10.1101/2021.07.14.452356

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Systems Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4237)
  • Biochemistry (9140)
  • Bioengineering (6784)
  • Bioinformatics (24010)
  • Biophysics (12133)
  • Cancer Biology (9537)
  • Cell Biology (13792)
  • Clinical Trials (138)
  • Developmental Biology (7639)
  • Ecology (11707)
  • Epidemiology (2066)
  • Evolutionary Biology (15514)
  • Genetics (10648)
  • Genomics (14330)
  • Immunology (9484)
  • Microbiology (22850)
  • Molecular Biology (9096)
  • Neuroscience (49019)
  • Paleontology (355)
  • Pathology (1483)
  • Pharmacology and Toxicology (2570)
  • Physiology (3848)
  • Plant Biology (8332)
  • Scientific Communication and Education (1471)
  • Synthetic Biology (2296)
  • Systems Biology (6194)
  • Zoology (1301)