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  • 标题:Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling
  • 本地全文:下载
  • 作者:Mohammad Mazharul Islam ; Andrea Goertzen ; Pankaj K. Singh
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2022
  • 卷号:25
  • 期号:6
  • 页码:1-21
  • DOI:10.1016/j.isci.2022.104483
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryPancreatic ductal adenocarcinoma (PDAC) is a major research focus because of its poor therapy response and dismal prognosis. PDAC cells adapt their metabolism to the surrounding environment, often relying on diverse nutrient sources. Because traditional experimental techniques appear exhaustive to find a viable therapeutic strategy, a highly curated and omics-informed PDAC genome-scale metabolic model was reconstructed using patient-specific transcriptomics data. From the model-predictions, several new metabolic functions were explored as potential therapeutic targets in addition to the known metabolic hallmarks of PDAC. Significant downregulation in the peroxisomal beta oxidation pathway, 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 correlated with potential drug combinations targeting genes with poor prognosis in PDAC. Overall, this study provides a better understanding of the metabolic vulnerabilities in PDAC and will lead to novel effective therapeutic strategies.Graphical abstractDisplay OmittedHighlights•Omics-integrated metabolic models of healthy and PDAC cells were reconstructed•Potential therapeutic targets were explored using model-predicted flux modulations•Potential drug combinations and repositioning strategies were suggestedMetabolomics; Cancer systems biology; Experimental models in systems biology; Transcriptomics
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