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Record W2044889475 · doi:10.1158/1538-7445.am2011-2356

Abstract 2356: Investigating the role of mammalian RNA binding protein Musashi-2 (MSI2) in breast cancer invasion and nodal metastasis

2011· article· en· W2044889475 on OpenAlexaff
Nick Holzapfel, Ranju Nair, Susan J. Done

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsCentre for Social InnovationOntario Institute for Cancer ResearchUniversity of Toronto
Fundersnot available
KeywordsWnt signaling pathwayBiologyNUMBCancer stem cellCancer researchNotch signaling pathwayCarcinogenesisStem cellMolecular biologyCancerCell biologySignal transductionGenetics

Abstract

fetched live from OpenAlex

Abstract Previous array comparative genomic hybridization (aCGH) studies in our lab have shown that chromosomal gains on 17q22-24.2 are associated with invasion when detected in duct carcinoma in situ (DCIS) and nodal metastasis when detected in invasive duct carcinoma (IDC). Of nine candidate genes identified within this region, MSI2 was selected for further study. MSI2 is a Musashi family RNA binding protein that translationally regulates target mRNAs. RNAi screens have indicated that MSI2 down regulation impairs hematopoietic stem cell repopulation. Other studies implicate its role in leukemia and colon cancer. Downstream targets of the MSI2 homologue MSI1, have shown a strong correlation with cancer related processes through their roles in cell cycle modulation, proliferation, differentiation, and apoptosis. MSI1 has also been shown to modulate WNT and Notch signaling through its interactions with the Notch inhibitor NUMB and the WNT antagonist DKK3. Invasion, migration, and proliferation assays were carried out in the breast cancer cell lines MDA231 and MCF7 over-expressing MSI2. These cell lines were also transfected with the TOPflash TCF reporter plasmid to investigate the effect of MSI2 over-expression on WNT signaling. To investigate the effects of WNT signaling on MSI2, MDA231 cell lines were treated with the human WNT agonist WNT-3a and MSI2 levels were quantified via western blotting. RNA immunoprecipitation was performed to analyze the downstream targets of MSI2. To investigate the role of MSI2 in breast stem and progenitor cell populations, cell lines were grown as non-adherent mammospheres. MSI2 RNA levels in mammospheres were compared via qRT-PCR. Lastly, the expression of a panel of stem cell markers was compared between cells over-expressing MSI2 and GFP controls via qRT-PCR. Our results show MSI2 over-expressing MCF7 and MDA231 cells have increased levels of proliferation, migration, and invasion. MSI2 over-expressing cells also up-regulate several putative stem cell markers including Epithelial Cell Adhesion Molecule (EpCAM), CD133, and Aldehyde Dehydrogenase. MSI2 levels are significantly enhanced in mammosphere culture and MSI2 over-expressing cells have demonstrated an increase in mammosphere forming capabilities. We believe MSI2 plays an important role in breast cancer through its modulation of RNA translation and subsequent regulation of WNT signaling and stem cell biology. MSI2 represents a promising therapeutic target which could be used to block breast cancer invasion and metastasis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2356. doi:10.1158/1538-7445.AM2011-2356

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 score0.008

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.062
GPT teacher head0.339
Teacher spread0.277 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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