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L773:0027 8424 OR L773:1091 6490
 

Sökning: L773:0027 8424 OR L773:1091 6490 > Chalmers tekniska högskola > Zhang C. > Metabolic network-b...

Metabolic network-based stratification of hepatocellular carcinoma reveals three distinct tumor subtypes

Bidkhori, Gholamreza (författare)
KTH,Science for Life Laboratory, SciLifeLab
Benfeitas, Rui (författare)
KTH,Science for Life Laboratory, SciLifeLab
Klevstig, Martina (författare)
Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för molekylär och klinisk medicin,Institute of Medicine, Department of Molecular and Clinical Medicine,University of Gothenburg
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Zhang, C. (författare)
KTH,Science for Life Laboratory, SciLifeLab
Nielsen, Jens B, 1962 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Uhlén, Mathias (författare)
KTH,Science for Life Laboratory, SciLifeLab
Borén, Jan, 1963 (författare)
Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för molekylär och klinisk medicin,Institute of Medicine, Department of Molecular and Clinical Medicine,University of Gothenburg
Mardinoglu, Adil, 1982 (författare)
KTH,Science for Life Laboratory, SciLifeLab
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 (creator_code:org_t)
2018-11-27
2018
Engelska.
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 115:50
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Hepatocellular carcinoma (HCC) is one of the most frequent forms of liver cancer, and effective treatment methods are limited due to tumor heterogeneity. There is a great need for comprehensive approaches to stratify HCC patients, gain biological insights into subtypes, and ultimately identify effective therapeutic targets. We stratified HCC patients and characterized each subtype using transcriptomics data, genome-scale metabolic networks and network topology/controllability analysis. This comprehensive systems-level analysis identified three distinct subtypes with substantial differences in metabolic and signaling pathways reflecting at genomic, transcriptomic, and proteomic levels. These subtypes showed large differences in clinical survival associated with altered kynurenine metabolism, WNT/beta-catenin-associated lipid metabolism, and PI3K/AKT/mTOR signaling. Integrative analyses indicated that the three subtypes rely on alternative enzymes (e.g., ACSS1/ACSS2/ACSS3, PKM/PKLR, ALDOB/ALDOA, MTHFD1L/MTHFD2/MTHFD1) to catalyze the same reactions. Based on systems-level analysis, we identified 8 to 28 subtype-specific genes with pivotal roles in controlling the metabolic network and predicted that these genes may be targeted for development of treatment strategies for HCC subtypes by performing in silico analysis. To validate our predictions, we performed experiments using HepG2 cells under normoxic and hypoxic conditions and observed opposite expression patterns between genes expressed in high/moderate/low-survival tumor groups in response to hypoxia, reflecting activated hypoxic behavior in patients with poor survival. In conclusion, our analyses showed that the heterogeneous HCC tumors can be stratified using a metabolic network-driven approach, which may also be applied to other cancer types, and this stratification may have clinical implications to drive the development of precision medicine.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Medicinsk genetik (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Medical Genetics (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)

Nyckelord

hepatocellular carcinoma
biological networks
personalized medicine
genome-scale metabolic
gene-expression
pathway
catenin
classification
activation
prediction
survival
biology
model
Personalized medicine

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ref (ämneskategori)
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