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Utilization of cancer-specific genome-scale metabolic models in pancreatic ductal adenocarcinomas for biomarkers discovery and patient stratification
University of Skövde, School of Bioscience.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 40 credits / 60 HE creditsStudent thesis
Abstract [en]

Pancreatic Ductal Adenocarcinomas initiates in the exocrine part of the pancreatic tissue and represents over 90% of all the pancreatic cancers. Pancreatic Ductal Adenocarcinomas are extremely aggressive and are one of the most lethal malignant neoplasms. The five-year relative survival is currently less than 8% of the patients. The main reason behind such a low survival rate is that most of the cases are diagnosed at a very late stage. Although substantial advancement in pancreatic cancer research has been done, there has not been any remarkable significance in the mortality to incidence ratio. This is mainly a result of the scarce of early diagnostic characteristic symptoms and reliable biomarkers besides the unresponsiveness to the treatments. In this study, transcriptomics and proteomics data were used for the construction of a genome-scale metabolic model that was used in the detection of altered metabolic pathways, genes and metabolites using gene set analysis and reporter metabolites analysis. As a result, altered metabolic pathways in PDAC tumours were detected, including the lipid metabolism-related pathways as well as carbohydrate metabolism, in addition to nucleotide metabolism, which are considered as potential candidates for diagnostic biomarkers. Moreover, classification of the filtered DIRAC tightly regulated network genes, based on their prognostic values from the pathology atlas, detected two groups of PDAC patients that have significantly different survival outcome. The differential expression analysis of the two groups showed that six of the eight genes used in clustering were showing significantly altered expression, which suggests their importance in PDAC patient stratification. As a conclusion, this study shows the valuable outcome of the GEM reconstructions and other systems-level analyses for elucidating the underlying altered metabolic mechanisms of PDAC. Such analyses results should provide more insights into the biomarker discovery and developing of potential treatments.

Place, publisher, year, edition, pages
2019. , p. 40
Keywords [en]
Genome-Scale Metabolic Models, GEM, Pancreatic Ductal Adenocarcinomas, pancreatic cancer, cancer metabolism, biomarker, LDHA, L-lactate dehydrogenase A chain
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:his:diva-17376OAI: oai:DiVA.org:his-17376DiVA, id: diva2:1335085
External cooperation
Science for Life Laboratory (Scilifelab), KTH-Royal Institute of Technology in Sweden
Subject / course
Systems Biology
Educational program
Tumor Biology - Master’s Programme
Supervisors
Examiners
Available from: 2019-07-04 Created: 2019-07-03 Last updated: 2019-07-04Bibliographically approved

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The full text will be freely available from 2020-08-01 19:28
Available from 2020-08-01 19:28

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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More styles
Language
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Output format
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