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Record W3108409030 · doi:10.1038/s42003-020-01458-3

A C21-steroidal derivative suppresses T-cell lymphoma in mice by inhibiting SIRT3 via SAP18-SIN3

2020· article· en· W3108409030 on OpenAlexafffund
Babu Gajendran, Krishnapriya M. Varier, Wuling Liu, Chunlin Wang, Klarke M. Sample, Eldad Zacksenhaus, Cui Juiwei, Lie‐Jun Huang, Xiao‐Jiang Hao, Yaacov Ben‐David

Bibliographic record

VenueCommunications Biology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHistone Deacetylase Inhibitors Research
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersPetroleum Technology Research CentreNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsSIRT3Cancer researchChemistryCell growthHistone deacetylaseNAD+ kinaseCell biologyBiologyHistoneBiochemistrySirtuinEnzyme

Abstract

fetched live from OpenAlex

Abstract The SIN3 repressor complex and the NAD-dependent deacetylase SIRT3 control cell growth, and development as well as malignant transformation. Even then, a little known about cross-talks between these two chromatin modifiers or whether their interaction explored therapeutically. Here we describe the identification of a C 21 -steroidal derivative compound, 3- O -chloroacetyl-gagamine, A671, which potently suppresses the growth of mouse and human T-cell lymphoma and erythroleukemia in vitro and preclinical models. A671 exerts its anti-neoplastic effects by direct interaction with Histone deacetylase complex subunit SAP18, a component of the SIN3 suppressor complex. This interaction stabilizes and activates SAP18, leading to transcriptional suppression of SIRT3 , consequently to inhibition of proliferation and cell death. The resistance of cancer cells to A671 correlated with diminished SAP18 activation and sustained SIRT3 expression. These results uncover the SAP18-SIN3-SIRT3 axis that can be pharmacologically targeted by a C 21 -steroidal agent to suppress T-cell lymphoma and other malignancies.

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 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 score0.078
Threshold uncertainty score0.829

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 science0.0010.001
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 head0.024
GPT teacher head0.296
Teacher spread0.272 · 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 teacher head, 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

Citations12
Published2020
Admission routes2
Has abstractyes

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