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Insights into gemcitabine resistance in pancreatic cancer: association with metabolic reprogramming and TP53 pathogenicity in patient derived xenografts

  1. Author:
    Konaté, Mariam M
    Krushkal, Julia
    Li, Ming-Chung
    Chen, Li
    Kotliarov, Yuri
    Palmisano, Alida
    Pauly,Rini
    Xie, Qian
    Williams, P Mickey
    McShane, Lisa M
    Zhao, Yingdong [ORCID]
  2. Author Address

    Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Rockville, MD, 20850, USA., Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research, Frederick, MD, 21704, USA., General Dynamics Information Technology (GDIT), Falls Church, VA, 22042, USA., Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Rockville, MD, 20850, USA. zhaoy@mail.nih.gov.,
    1. Year: 2024
    2. Date: Aug 05
    3. Epub Date: 2024 08 05
  1. Journal: Journal of Translational Medicine
    1. 22
    2. 1
    3. Pages: 733
  2. Type of Article: Article
  3. Article Number: 733
  1. Abstract:

    With poor prognosis and high mortality, pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. Standard of care therapies for PDAC have included gemcitabine for the past three decades, although resistance often develops within weeks of chemotherapy initiation through an array of possible mechanisms. We reanalyzed publicly available RNA-seq gene expression profiles of 28 PDAC patient-derived xenograft (PDX) models before and after a 21-day gemcitabine treatment using our validated analysis pipeline to identify molecular markers of intrinsic and acquired resistance. Using normalized RNA-seq quantification measurements, we first identified oxidative phosphorylation and interferon alpha pathways as the two most enriched cancer hallmark gene sets in the baseline gene expression profile associated with intrinsic gemcitabine resistance and sensitivity, respectively. Furthermore, we discovered strong correlations between drug-induced expression changes in glycolysis and oxidative phosphorylation genes and response to gemcitabine, which suggests that these pathways may be associated with acquired gemcitabine resistance mechanisms. Thus, we developed prediction models using baseline gene expression profiles in those pathways and validated them in another dataset of 12 PDAC models from Novartis. We also developed prediction models based on drug-induced expression changes in genes from the Molecular Signatures Database (MSigDB)'s curated 50 cancer hallmark gene sets. Finally, pathogenic TP53 mutations correlated with treatment resistance. Our results demonstrate that concurrent upregulation of both glycolysis and oxidative phosphorylation pathways occurs in vivo in PDAC PDXs following gemcitabine treatment and that pathogenic TP53 status had association with gemcitabine resistance in these models. Our findings may elucidate the molecular basis for gemcitabine resistance and provide insights for effective drug combination in PDAC chemotherapy. © 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

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External Sources

  1. DOI: 10.1186/s12967-024-05528-6
  2. PMID: 39103840
  3. PMCID: PMC11301937
  4. PII : 10.1186/s12967-024-05528-6

Library Notes

  1. Fiscal Year: FY2023-2024
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