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Record W2081571678 · doi:10.4161/cc.22227

The milk protein α-casein functions as a tumor suppressor via activation of STAT1 signaling, effectively preventing breast cancer tumor growth and metastasis

2012· article· en· W2081571678 on OpenAlex

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.

Bibliographic record

VenueCell Cycle · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDigestive system and related health
Canadian institutionsInstitute of Cancer Research
FundersMargaret Q. Landenberger Research Foundation
KeywordsBiologyCancer researchSuppressorBreast cancerMetastasisSignal transductionSTAT1CancerCell biologyGenetics

Abstract

fetched live from OpenAlex

Here, we identified the milk protein α-casein as a novel suppressor of tumor growth and metastasis. Briefly, Met-1 mammary tumor cells expressing α-casein showed a ~5-fold reduction in tumor growth and a near 10-fold decrease in experimental metastasis. To identify the molecular mechanism(s), we performed genome-wide transcriptional profiling. Interestingly, our results show that α-casein upregulates gene transcripts associated with interferon/STAT1 signaling and downregulates genes associated with "stemness." These findings were validated by immunoblot and FACS analysis, which showed the upregulation and hyperactivation of STAT1 and a decrease in the number of CD44(+) "cancer stem cells." These gene signatures were also able to predict clinical outcome in human breast cancer patients. Thus, we conclude that a lactation-based therapeutic strategy using recombinant α-casein would provide a more natural and non-toxic approach to the development of novel anticancer therapies.

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 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 score0.012
Threshold uncertainty score0.367

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 head0.006
GPT teacher head0.241
Teacher spread0.235 · 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