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Record W2121220704 · doi:10.1073/pnas.0710091104

Mammary epithelial-specific disruption of the focal adhesion kinase blocks mammary tumor progression

2007· article· en· W2121220704 on OpenAlexafffund
Hicham Lahlou, Virginie Sanguin‐Gendreau, Dongmei Zuo, Robert D. Cardiff, Gordon W. McLean, Margaret C. Frame, William J. Muller

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2007
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
FundersCanadian Institutes of Health ResearchCanadian Breast Cancer Research AllianceCanada Research ChairsU.S. Department of DefenseMcGill UniversityBreast Cancer Alliance
KeywordsFocal adhesionTumor progressionCancer researchMammary tumorBiologyMammary glandGenetically modified mouseCell biologyKinaseSignal transductionCell adhesion moleculePathologyBreast cancerCancerTransgeneMedicineGeneGenetics

Abstract

fetched live from OpenAlex

Elevated expression and activation of the focal adhesion kinase (FAK) occurs in a large proportion of human breast cancers. Although several studies have implicated FAK as an important signaling molecule in cell culture systems, evidence supporting a role for FAK in mammary tumor progression is lacking. To directly assess the role of FAK in this process, we have used the Cre/loxP recombination system to disrupt FAK function in the mammary epithelium of a transgenic model of breast cancer. Using this approach, we demonstrate that FAK expression is required for the transition of premalignant hyperplasias to carcinomas and their subsequent metastases. This dramatic block in tumor progression was further correlated with impaired mammary epithelial proliferation. These observations provide direct evidence that FAK plays a critical role in mammary tumor 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 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 score0.002
Threshold uncertainty score0.005

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.347
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 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

Citations195
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicCell Adhesion Molecules ResearchFrench-language works237,207