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Record W4386819147 · doi:10.1002/1873-3468.14737

Inhibiting <scp>SETD7</scp> methyl‐transferase activity impairs differentiation, lipid metabolism and lactogenesis in mammary epithelial cells

2023· article· en· W4386819147 on OpenAlexfundno aff
Fátima Liliana Monteiro, André Góis, Inês Direito, Tânia Melo, Bruna Neves, Mariana Alves, Inês A. Batista, M. Rosário Domingues, Luísa A. Helguero

Bibliographic record

VenueFEBS Letters · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaUniversity of TorontoLaboratório Associado para a Química VerdeCentro de Estudos Ambientais e Marinhos, Universidade de AveiroUniversidade de AveiroRede de Química e TecnologiaLiga Portuguesa Contra o Cancro
KeywordsCellular differentiationChemistryCell growthLipid metabolismCell cultureMolecular biologyCell biologyBiologyBiochemistryGene

Abstract

fetched live from OpenAlex

SETD7 (SET7/9, KMT7) is a lysine methyltransferase that targets master regulators of cell proliferation and differentiation. Here, the impact of inhibiting SETD7 catalytic activity on mammary epithelial cell differentiation was studied by focusing on genes associated with epithelial differentiation, lactogenesis, and lipid metabolism in HC11 and EpH4 cell lines. Setd7 mRNA and protein levels were induced upon lactogenic differentiation in both cell lines. Inhibition of SETD7 activity by the compound (R)-PFI-2 increased cell proliferation and downregulated E-cadherin, beta-catenin, lactoferrin, insulin-like growth factor binding protein 5, and beta-casein levels. In addition, inhibition of SETD7 activity affected the lipid profile and altered the mRNA expression of the phospholipid biosynthesis-related genes choline phosphotransferase 1, and ethanolamine-phosphate cytidylyltransferase. Altogether, the results suggest that inhibiting SETD7 catalytic activity impairs mammary epithelial and lactogenic differentiation.

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 score0.117
Threshold uncertainty score0.893

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 science0.0000.000
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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