Metabolic network-based stratification of hepatocellular carcinoma reveals three distinct tumor subtypes (Q61445639): Difference between revisions

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Latest revision as of 22:27, 11 June 2024

article published in the Proceedings of the National Academy of Sciences of the United States of America

Language	Label	Description	Also known as
English	Metabolic network-based stratification of hepatocellular carcinoma reveals three distinct tumor subtypes	article published in the Proceedings of the National Academy of Sciences of the United States of America

Statements

instance of

scholarly article

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title

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

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main subject

hepatocellular carcinoma

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based on heuristic

inferred from title

metabolic network

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based on heuristic

inferred from title

author

Adil Mardinoglu

object named as

Adil Mardinoglu

series ordinal

8

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Mathias Uhlén

object named as

Mathias Uhlen

series ordinal

6

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Rui Benfeitas

object named as

Rui Benfeitas

series ordinal

2

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Cheng Zhang

object named as

Cheng Zhang

series ordinal

4

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Jens Nielsen

series ordinal

5

object named as

Jens Nielsen

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Jan Borén

series ordinal

7

object named as

Jan Boren

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Gholamreza Bidkhori

series ordinal

1

object named as

Gholamreza Bidkhori

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author name string

Martina Klevstig

series ordinal

3

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language of work or name

English

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publication date

11 December 2018

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published in

Proceedings of the National Academy of Sciences of the United States of America

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volume

115

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issue

50

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page(s)

E11874-E11883

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cites work

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reference URL

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Differential effects of inactivated Axin1 and activated beta-catenin mutations in human hepatocellular carcinomas

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reference URL

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Functional integration of a metabolic network model and expression data without arbitrary thresholding.

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Predicting selective drug targets in cancer through metabolic networks.

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An endogenous tumour-promoting ligand of the human aryl hydrocarbon receptor

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β-catenin is essential for ethanol metabolism and protection against alcohol-mediated liver steatosis in mice

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reference URL

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Sixty-five gene-based risk score classifier predicts overall survival in hepatocellular carcinoma

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β-Catenin regulates hepatic mitochondrial function and energy balance in mice

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Exact controllability of complex networks

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based on heuristic

inferred from PubMed ID database lookup

Network-based stratification of tumor mutations

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inferred from PubMed ID database lookup

The Cancer Genome Atlas Pan-Cancer analysis project

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Inferring tumour purity and stromal and immune cell admixture from expression data

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Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease

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based on heuristic

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based on heuristic

inferred from PubMed ID database lookup

Teneligliptin Decreases Uric Acid Levels by Reducing Xanthine Dehydrogenase Expression in White Adipose Tissue of Male Wistar Rats.

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Kynurenine Pathway of Tryptophan Metabolism: Regulatory and Functional Aspects

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Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma

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based on heuristic

inferred from PubMed ID database lookup

New Challenges to Study Heterogeneity in Cancer Redox Metabolism

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12 December 2020

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Integrative clinical genomics of metastatic cancer

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A pathology atlas of the human cancer transcriptome

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12 December 2020

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inferred from PubMed ID database lookup

Network analyses identify liver-specific targets for treating liver diseases

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Glutamine synthetase mediates sorafenib sensitivity in β-catenin-active hepatocellular carcinoma cells.

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Asparagine bioavailability governs metastasis in a model of breast cancer.

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Recon3D enables a three-dimensional view of gene variation in human metabolism.

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Systems biology in hepatology: approaches and applications.

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Metabolic Network-Based Identification and Prioritization of Anticancer Targets Based on Expression Data in Hepatocellular Carcinoma

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Identifiers

DOI

10.1073/PNAS.1807305115

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PMC publication ID

6294939

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PubMed publication ID

30482855

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