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Record W3015646212 · doi:10.1038/s41467-020-15290-0

Potent BRD4 inhibitor suppresses cancer cell-macrophage interaction

2020· article· en· W3015646212 on OpenAlexaff
Mingzhu Yin, Ying Guo, Rui Hu, Wesley L. Cai, Yao Li, Shiyao Pei, Hongyin Sun, Cong Peng, Jiali Li, Rui Ye, Qiaohong Yang, Nenghui Wang, Yongguang Tao, Xiang Chen, Qin Yan

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsSKiN Health
FundersCongressionally Directed Medical Research ProgramsNational Center for Advancing Translational SciencesMelanoma Research AllianceNational Cancer InstituteYale UniversityU.S. Department of Health and Human ServicesNational Natural Science Foundation of ChinaU.S. Department of Defense
KeywordsMacrophageCancer researchCancerBRD4Cancer cellChemistryCell biologyBromodomainBiologyBiochemistryGeneticsHistoneDNAIn vitro

Abstract

fetched live from OpenAlex

Small molecule inhibitor of the bromodomain and extraterminal domain (BET) family proteins is a promising option for cancer treatment. However, current BET inhibitors are limited by their potency or oral bioavailability. Here we report the discovery and characterization of NHWD-870, a BET inhibitor that is more potent than three major clinical stage BET inhibitors BMS-986158, OTX-015, and GSK-525762. NHWD-870 causes tumor shrinkage or significantly suppresses tumor growth in nine xenograft or syngeneic models. In addition to its ability to downregulate c-MYC and directly inhibit tumor cell proliferation, NHWD-870 blocks the proliferation of tumor associated macrophages (TAMs) through multiple mechanisms, partly by reducing the expression and secretion of macrophage colony-stimulating factor CSF1 by tumor cells. NHWD-870 inhibits CSF1 expression through suppressing BRD4 and its target HIF1α. Taken together, these results reveal a mechanism by which BRD4 inhibition suppresses tumor growth, and support further development of NHWD-870 to treat solid tumors.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.302
Teacher spread0.284 · 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

Citations188
Published2020
Admission routes1
Has abstractyes

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Same venueNature CommunicationsSame topicProtein Degradation and InhibitorsFrench-language works237,207