MétaCan
Menu
← Back to cohort
Record W1984236918 · doi:10.1158/1538-7445.am2014-2433

Abstract 2433: Metabolic reprogramming by an epigenetic mechanism in endocrine therapy resistance of breast cancer

2014· article· en· W1984236918 on OpenAlexaff
June X. Zou, Junjian Wang, Zhijian Duan, Hong-Wu Chen, Hsing‐Jien Kung, Xinbin Chen, Leigh C. Murphy, Alexander D. Borowsky

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsOccupational and Environmental Medical Association of Canada
Fundersnot available
KeywordsReprogrammingEpigeneticsTamoxifenCancer researchBiologyHistone methyltransferaseBreast cancerCancerCellGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Metabolic reprogramming is a major mechanism of fueling cancer cell growth and proliferation. However, how tumor metabolism is altered to confer therapeutic resistance is poorly understood. Gene expression profiling of tamoxifen sensitive and resistant breast cancer cells revealed that transition to the resistance was associated with a specific expression reprogramming of genes involved in glucose/energy metabolism, which was accompanied by aberration of specific epigenetic regulators such as the histone methyltransferase NSD2/MMSET/WHSC1. In cell and xenograft tumor models, NSD2 overexpression alone was sufficient to confer tamoxifen resistance. Analysis of clinical specimens indicates that NSD2 was a strong predictive factor for early relapse of tamoxifen therapy. NSD2 wild type, but not its methylase-defective mutant form, coordinately stimulated the expression and enzymatic activity of HK2, TIGAR and G6PD and strongly augmented the pentose phosphate pathway (PPP) production of NADPH for ROS reduction and survival of tamoxifen treated cells and tumors. Further mechanistic studies demonstrated that elevated NSD2 stimulates the metabolic gene expression through H3K36 methylation at the target chromatin. Pharmacological targeting aberrant NSD2 by DZNeP, an S-adenosylhomocysteine (AdoHcy) hydrolase inhibitor, effectively blocked the growth of tamoxifen-resistant tumor. The study reveals a novel mechanism of cancer metabolic reprogramming and suggests targeting the key metabolic re-programmer as a viable option for effective treatment of endocrine resistant tumors. Note: This abstract was not presented at the meeting. Citation Format: June X. Zou, Junjian Wang, Zhijian Duan, Hongwu Chen, Hsing-Jien Kung, Xinbin Chen, Leigh C. Murphy, Alexander Borowsky. Metabolic reprogramming by an epigenetic mechanism in endocrine therapy resistance of breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2433. doi:10.1158/1538-7445.AM2014-2433

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 score0.024
Threshold uncertainty score0.080

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0240.004

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 head0.033
GPT teacher head0.364
Teacher spread0.331 · 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
Published2014
Admission routes1
Has abstractyes

Explore more

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