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Record W2806165623 · doi:10.18632/oncotarget.25525

Metabolite profiling identifies a signature of tumorigenicity in hepatocellular carcinoma

2018· article· en· W2806165623 on OpenAlex
Shamir Cassim, Valérie‐Ann Raymond, Benoit Lacoste, Pascal Lapierre, Marc Bilodeau

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOncotarget · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsGlycolysisCancer researchHepatocellular carcinomaMetaboliteAnaerobic glycolysisBiologyMetabolomeMetabolomicsCancer cellHypoxia (environmental)EndocrinologyInternal medicineMedicineCancerMetabolismChemistryBioinformatics

Abstract

fetched live from OpenAlex

// Shamir Cassim 1 , Valérie-Ann Raymond 1 , Benoit Lacoste 1 , Pascal Lapierre 1, 2 and Marc Bilodeau 1, 2 1 Laboratoire d’hépatologie cellulaire, Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada 2 Département de médecine, Université de Montréal, Montréal, QC, Canada Correspondence to: Marc Bilodeau, email: marc.bilodeau@umontreal.ca Keywords: liver; hepatocellular carcinoma; glucose; tumorigenicity; metabolic signature Received: March 26, 2018      Accepted: May 17, 2018      Published: June 01, 2018 ABSTRACT HCC (Hepatocellular carcinoma) cells exhibit greater metabolic plasticity than normal hepatocytes since they must survive in a dynamic microenvironment where nutrients and oxygen are often scarce. Using a metabolomic approach combined with functional in vitro and in vivo assays, we aimed to identify an HCC metabolic signature associated with increased tumorigenicity and patient mortality. Metabolite profiling of HCC Dt81Hepa1-6 cells revealed that their increased tumorigenicity was associated with elevated levels of glycolytic metabolites. Tumorigenic Dt81Hepa1-6 also had an increased ability to uptake glucose leading to a higher glycolytic flux that stemmed from an increased expression of glucose transporter GLUT-1. Dt81Hepa1-6-derived tumors displayed increased mRNA expressions of glycolytic genes, Hypoxia-inducible factor-1alpha and of Cyclin D1 . HCC tumors also displayed increased energy charge, reduced antioxidative metabolites and similar fatty acid biosynthesis compared to healthy liver. Increased tumoral expression of glycolytic and hypoxia signaling pathway mRNAs was associated with decreased survival in HCC patients. In conclusion, HCC cells can rapidly alter their metabolism according to their environment and switch to the use of glucose through aerobic glycolysis to sustain their tumorigenicity and proliferative ability. Therefore, cancer metabolic reprogramming could be essential for the tumorigenicity of HCC cells during cancer initiation and invasion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.247
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it