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Record W2087355395 · doi:10.1158/0008-5472.can-10-2041

Overexpression of the Protein Tyrosine Phosphatase PRL-2 Correlates with Breast Tumor Formation and Progression

2010· article· en· W2087355395 on OpenAlexafffund
Serge Hardy, Nau Nau Wong, William J. Muller, Morag Park, Michel L. Tremblay

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsCancer researchMammary tumorBiologyProtein tyrosine phosphataseGenetically modified mouseCarcinogenesisMammary glandTumor progressionMetastasisInternal medicineEndocrinologyCancerMouse mammary tumor virusTransgeneSignal transductionBreast cancerMedicineCell biologyImmunology

Abstract

fetched live from OpenAlex

The PRL-1, PRL-2, and PRL-3 phosphatases are prenylated protein tyrosine phosphatases with oncogenic activity that are proposed to drive tumor metastasis. We found that PRL-2 mRNA is elevated in primary breast tumors relative to matched normal tissue, and also dramatically elevated in metastatic lymph nodes compared with primary tumors. PRL-2 knockdown in metastatic MDA-MB-231 breast cancer cells decreased anchorage-independent growth and cell migration, suggesting that the malignant phenotype of these cells is mediated at least in part through PRL-2 signaling. In different mouse mammary tumor-derived cell lines overexpressing PRL-2, we confirmed its role in anchorage-independent growth and cell migration. Furthermore, injection of PRL-2-overexpressing cells into the mouse mammary fat pad promoted extracellular signal-regulated kinase 1/2 activation and tumor formation. MMTV-PRL-2 transgenic mice engineered to overexpress the enzyme in mammary tissue did not exhibit spontaneous tumorigenesis, but they exhibited an accelerated development of mammary tumors initiated by introduction of an MMTV-ErbB2 transgene. Together, our results argue that PRL-2 plays a role in breast cancer progression.

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 score0.006
Threshold uncertainty score0.242

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 head0.013
GPT teacher head0.318
Teacher spread0.305 · 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

Citations73
Published2010
Admission routes2
Has abstractyes

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