MétaCan
Menu
← Back to cohort
Record W2887883897 · doi:10.1158/1538-7445.am2018-5476

Abstract 5476: Inhibiting lactate transporters MCT-1 and MCT-4 target hypoxic HNSCC cells and sensitize them to metformin

2018· article· en· W2887883897 on OpenAlexaff
Pedro Boasquevisque, Verena Schoeneberger, Laura Caporiccio, Ravi N. Vellanki, Marianne Koritzinsky, Bradly G. Wouters

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMetforminHypoxia (environmental)Head and neck squamous-cell carcinomaRadioresistanceExtracellularBiologyCancer researchGlycolysisGlucose transporterChemistryCell culturePharmacologyCell biologyMetabolismOxygenInternal medicineBiochemistryEndocrinologyMedicineCancerHead and neck cancerDiabetes mellitusInsulin

Abstract

fetched live from OpenAlex

Abstract Head and neck squamous cell carcinoma (HNSCC) is treated primarily through a combination of surgery and radiation therapy. The problem of radioresistance, however, persists and requires new approaches to overcome it. Tumor hypoxia has been shown to be a driver of radioresistance, thereby prompting the targeting of the hypoxic niche, known to be highly glycolytic. Two key components of the hypoxic metabolic profile are lactate transporters MCT-1 and MCT-4, which sustain hypoxia-driven lactate production in cells. We hypothesize that inhibition of MCT-1 and MCT-4 will selectively target the growth of hypoxic tumor cells and potentially exert a synergistic effect with the antidiabetic drug metformin, a known inhibitor of mitochondrial respiration that has been shown to improve the radiation response. To study this, we employed CRISPR-Cas9 to genetically ablate both MCT-1 and MCT-4 in an HNSCC cell line. Validation of double knockout (DKO) cells was done through immunoblotting and sequencing. Cells were grown under conditions of 21% O2 (normoxia) in a regular CO2 incubator or 0.2% O2 (hypoxia) in an H45 HypOxystation® hypoxia chamber. Cell proliferation was measured under normoxia and hypoxia through the use of IncuCyte automated imaging while the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) of cells were measured using a Seahorse™ XF analyzer. Metabolic profiling of the DKO cells showed a higher rate of oxygen consumption and a decreased ability of exporting lactate, indicating a metabolic shift when lactate transport is impaired. The loss of MCT-1 and MCT-4 by themselves did not significantly alter cell proliferation under normoxic conditions, but disruption of both transporters concurrently significantly altered growth under normoxia. When exposed to hypoxia, proliferation of the DKO cells was completely halted. In addition, MCT-1/MCT-4 double knockouts showed greater inhibition of cell growth under metformin treatment than either single knockouts or wild-type cells. Significantly lower doses of metformin, which had no effect on the proliferation of wild-type or single knockout cells, were capable of impairing the growth of DKO cells under hypoxia. In conclusion, our study shows that inhibition of lactate export has a profound effect on cell growth under hypoxic conditions in vitro. Moreover, loss of lactate export enhances the sensitivity of HNSCC cells to metformin and could constitute a new way of targeting the hypoxic niche with the purpose of leading to better treatment outcomes. Citation Format: Pedro H. Boasquevisque, Verena Schoeneberger, Laura Caporiccio, Ravi Vellanki, Marianne Koritzinsky, Bradly G. Wouters. Inhibiting lactate transporters MCT-1 and MCT-4 target hypoxic HNSCC cells and sensitize them to metformin [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5476.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.041
GPT teacher head0.333
Teacher spread0.292 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCancer Research→Same topicCancer, Hypoxia, and Metabolism→French-language works237,207→