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Record W4411197130 · doi:10.1002/mc.23937

Reduced <i>JAG1</i> Expression Through miR‐200 Overexpression or Crispr‐Cas Mediated Knockout Impairs TNBC Growth and Metastasis

2025· article· en· W4411197130 on OpenAlex
Katrina L. Watson, Roger A. Moorehead

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular Carcinogenesis · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of Guelph
FundersCanadian Institutes of Health Research
KeywordsBiologyCRISPRCancer researchMetastasisExpression (computer science)microRNAJAG1Cell biologyGeneticsSignal transductionCancerGeneNotch signaling pathway

Abstract

fetched live from OpenAlex

Studies from our lab demonstrated that increasing miR-200 expression in human triple negative breast cancer (TNBC) reduced tumor growth and metastasis In Vivo. In this study, we found that overexpression of miR-200s in TNBC cells significantly reduced the expression of JAG1. When JAG1 was knocked out in MDA-MB-231 cells proliferation and invasion were significantly reduced In Vitro. Moreover, loss of JAG1 inhibited mammary tumor growth and metastasis In Vivo. RNA sequencing revealed that loss of JAG1 altered the expression of genes associated with the ECM, angiogenesis, and EMT. These results imply that miR-200s may mediate some of their antitumor actions through reducing JAG1 expression and suggest that agents targeting JAG1 should be further evaluated as a therapeutic strategy for TNBC.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.013
Threshold uncertainty score1.000

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 head0.011
GPT teacher head0.268
Teacher spread0.257 · 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