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Abstract P5-05-01: IGFBP-7 Reduces Growth of Xenografted Breast Tumors in Mice and Inhibits Breast Cancer Cell Proliferation and Migration through the MEK-ERK Pathway

2010· article· en· W2318268630 on OpenAlexaff
Tania Benatar, Yutaka Amemiya, Weining Yang, Arun Seth

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsCancer researchTriple-negative breast cancerBreast cancerEctopic expressionCyclin-dependent kinase 6Cell growthBiologyMetastasisCancerCarcinogenesisCyclin D1Cell cultureCell cycleGenetics

Abstract

fetched live from OpenAlex

Abstract To identify genes correlated with breast tumorigenesis and eventual metastasis, gene expression profiles were generated using 28K whole genome microarrays. Gene expression profiles of primary breast tumors that grew and metastasized in the NOD/SCID mice were compared with other primary breast tumors that had different growth and metastatic potentials. Five hundred and eighty two genes were significantly differentially expressed by our statistical comparison criteria using the GeneSpring GX 7.3.1 software suite. In the metastatic set eight genes were selectively overexpressed (YB1, MMP7, MMP9, RAB5A, RABGDIB, EPHRB3, WNT2B, CSF1R) and 12 were selectively underexpressed (IGFBP7, GATA3, CST5, CDK6, SERBP1, MGP, TGF1L4, ESE3, ELF3, EDNRB, HECTD1, TINP1). In the present study we focused on the IGFBP-7 gene product which was found to be inversely correlated with disease progression in breast cancer. To further investigate the role of IGFBP-7 in breast tumor suppression, it was overexpressed in the triple negative MDA-MB-468 human breast cancer line. Ectopic overexpression of IGFBP-7 clearly reduced the growth of the MDA-MB-468/IGFBP-7 cells compared to the parental MDA-MB-468 cells. Ectopic overexpression or addition of rIGFBP-7 to breast cancer cell lines in vitro clearly reduced the growth of several breast cancer cell lines and resulted in phenotypic changes characterized by cell aggregation. Investigation of downstream signalling pathways affected by IGFBP-7 revealed that addition of IGFBP-7 to a triple negative breast cancer cell line not only inhibited phosphorylation of ERK-1/2 but also increased expression of the cyclin-dependent kinase inhibitor 1, p21. Similar IGFBP-7 treatment of an ER+ breast cancer line resulted not only in inhibition of ERK-1/2 phosphorylation, but also AKT phosphorylation, suggesting that IGFBP-7 may affect multiple pathways in hormone responsive breast cancer cell lines. IGFBP-7 protein is processed into a shorter form by matriptase. Breast cancer cell lines which were unable to process IGFBP-7 into the shorter form were unaffected by IGFBP-7 mediated growth inhibition, suggesting that cleaved IGFBP-7 may be required for growth inhibitory effects. When injected subcutaneously into NOD/SCID mice, the increased expression of IGFBP-7 in the MDA-MB-468/IGFBP-7 cells reduced the rate of tumor growth in comparison to the parental MDA-MB-468 cells. Furthermore, injection of rIGFBP-7 protein at the tumor site into breast cancer xenografted NOD/SCID mice also resulted in significant tumor growth reduction. These results suggest that the growth of breast cancer could be prevented by the forced expression of IGFBP-7 protein. Work in progress will further uncover the mechanism of IGFBP-7-mediated inhibition on signalling pathways, as well as differentiate the impact of both full length and cleaved IGFBP-7 protein on breast tumor inhibition. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P5-05-01.

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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.018
GPT teacher head0.307
Teacher spread0.289 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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