MétaCan
Menu
← Back to cohort

Abstract PR08: Lactate dehydrogenase A is a pharmacologically tractable EWS-FLI1 transcriptional target that regulates the glycolytic dependence of Ewing sarcoma

2020· article· en· W3044435499 on OpenAlexaboutno aff
Choh Yeung, Anna E. Gibson, Sameer H. Issaq, Nobu Oshima, Marielle E. Yohe, Haiyan Lei, Ganesha Rai, Daniel J. Urban, Michelle S. Johnson, Gloria A. Benevides, Giuseppe L. Squadrito, Sandy Eldridge, John Hamre, Arnulfo Mendoza, Jack F. Shern, Lee J. Helman, Murali C. Krishna, Matthew D. Hall, Victor Darley‐Usmar, Leonard Μ. Neckers, Christine M. Heske

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsGlycolysisLactate dehydrogenase AGene knockdownCancer researchLactate dehydrogenaseCell cultureCancer cellCancerChemistryBiologyApoptosisCell biologyBiochemistryEnzymeGenetics

Abstract

fetched live from OpenAlex

Abstract Altered cellular metabolism, including an increased dependence on aerobic glycolysis, is a hallmark of cancer. Despite the fact that this observation was first made nearly a century ago, effective therapeutic targeting of glycolysis in cancer has remained elusive. One potentially promising approach involves targeting the glycolytic enzyme lactate dehydrogenase (LDH), which is overexpressed and plays a critical role in several cancers. To uncover cell type-specific dependencies to LDH, we screened a diverse panel of 94 cancer cell lines for responsiveness to two novel LDH A/B inhibitors developed through the NCI Experimental Therapeutics Program (NExT). We found that Ewing sarcoma (EWS) cell lines were exquisitely sensitive, with IC50 values approximately ten-fold below the median IC50 of the panel. To understand the mechanism behind this sensitivity, we genetically knocked down LDHA and LDHB using siRNA, and discovered that EWS cell lines were sensitive to loss of LDHA only, which inhibited proliferation and induced apoptosis. Notably, treatment of EWS cells with the LDH inhibitors phenocopied these effects. Additionally, genetic knockdown of EWS-FLI1, the oncogenic driver of EWS, resulted in loss of LDHA, but not LDHB. Analysis of publicly available ChIP-seq data generated using shFLI1-transfected EWS cells revealed that LDHA, but not LDHB, is directly regulated by EWS-FLI1. Functional mechanistic studies of glycolytic intermediates and cellular bioenergetics in EWS cells treated with the LDH inhibitors demonstrated that loss of viability was due to impairment of glycolysis, which occurred both in vitro and in vivo, and perturbation of the NAD+/NADH ratio. The translational potential of these compounds was next evaluated using in vivo analyses of pharmacokinetics, pharmacodynamics, efficacy, and toxicity. Intravenous administration of the LDH inhibitors resulted in diminished LDH activity, reduction of the lactate-to-pyruvate ratio, tumor cell necrosis, and a decrease in tumor growth rate in aggressive xenograft models of EWS. The major dose-limiting toxicity observed was hemolysis, indicating that a narrow therapeutic window exists for these compounds. Taken together, our data suggest that targeting glycolysis through inhibition of LDH should be further investigated as a potential therapeutic approach for cancers such as EWS that exhibit oncogene-dependent expression of LDH and increased glycolytic activity. This abstract is also being presented as Poster B33. Citation Format: Choh Yeung, Anna E. Gibson, Sameer H. Issaq, Nobu Oshima, Marielle E. Yohe, Haiyan Lei, Ganesha Rai, Daniel J. Urban, Michelle S. Johnson, Gloria A. Benevides, Giuseppe L. Squadrito, Sandy Eldridge, John Hamre III, Arnulfo Mendoza, Jack F. Shern, Lee J. Helman, Murali C. Krishna, Matthew D. Hall, Victor M. Darley-Usmar, Leonard M. Neckers, Christine M. Heske. Lactate dehydrogenase A is a pharmacologically tractable EWS-FLI1 transcriptional target that regulates the glycolytic dependence of Ewing sarcoma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr PR08.

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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0070.003

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 head0.092
GPT teacher head0.363
Teacher spread0.271 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

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