MétaCan
Menu
Back to cohort

Abstract P1-04-05: Role of the Rb and p53 Tumor Suppressor Pathways in Mammary Tumorigenesis

2012· article· en· W2316086785 on OpenAlexaff
R.K. Jones, Jinchang Liu, AA Schimmer, Z Eldad

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsCancer researchCarcinogenesisBiologyCre recombinaseMammary tumorRetinoblastomaMammary glandTumor suppressor geneCancerBreast cancerMolecular biologyGeneTransgeneGenetically modified mouseGenetics

Abstract

fetched live from OpenAlex

Abstract The retinoblastoma (Rb) and p53 tumor suppressor pathways are frequently altered in human malignancies including breast cancer. To investigate the role of these pathways in mammary tumorigenesis, we crossed mice expressing Cre recombinase in the mammary epithelium (MMTV-Cre) with mice harboring Rb and p53 floxed alleles to generate MMTV-Cre:Rbf/f:p53f/f mutant mice. Combined somatic loss of Rb and p53 led to the formation of aggressive triple-negative tumors (ER−, PR−, HER2−) that often displayed features of an epithelial to mesenchymal transition (EMT) including sarcomatoid differentiation and high expression of the mesenchymal marker N-Cadherin. Molecular profiling revealed Rb/p53 deficient tumors shared similar gene expression profiles with mouse and human claudin-low breast cancers. Interstingly, limiting dilution transplantation analysis also suggests that Rb/p53 deficient claudin-low tumors are enriched for tumor-initiating cells (TICs). To investigate the cellular origin of claudin-low tumors, the Rbf/f and p53f/f alleles were deleted within the luminal and basal compartments of the mammary gland using a Cre-expressing adenovirus (Ad-Cre) and CD24-CD49f-based FACS analysis. The different cellular fractions were then transplanted into the cleared mammary fat pad of recipient mice which are currently being monitored for tumor development. Finally, primary cell lines isolated from Rb/p53 deficient mammary tumors were used in conjunction with high-throughput chemical and genetic screens to identify new therapeutic targets. A primary screen of 260 kinase inhibitors and 312 FDA-approved off-patent drugs has identified novel candidates and a genome wide negative selection (‘drop-out’) screen is currently in progress. Ultimately, the results of this research will provide important insight into the biology of triple-negative breast cancer and will lead to the identification of novel therapeutic targets for the treatment of patients living with this disease. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P1-04-05.

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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.051
GPT teacher head0.342
Teacher spread0.291 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicCancer-related Molecular PathwaysFrench-language works237,207