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Record W2486011716 · doi:10.1158/1538-7445.am2016-686

Abstract 686: MNK1 promotes the progression of breast ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC)

2016· article· en· W2486011716 on OpenAlexaff
Qianyu Guo, Sonia V. del Rincón, Christophe Gonçalves, Wilson H. Miller

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsMcGill University
Fundersnot available
KeywordsDuctal carcinomaCancer researchIn situBiologyPathologyMedicineBreast cancerCancerInternal medicineChemistry

Abstract

fetched live from OpenAlex

Abstract The mechanism by which breast ductal carcinoma in situ (DCIS) progresses to invasive ductal carcinoma (IDC) is poorly described. Previous studies have revealed that DCIS and IDC share similar genomes and transcriptomes. We hypothesize that one mechanism contributing to the DCIS to IDC conversion involves aberrations in mRNA translation. The Mnk/eIF4E axis has a critical role in promoting the translation of tumor promoting and pro-invasive mRNAs, thus we propose to study whether aberrant activation of this axis promotes the transition of DCIS to IDC. Our model system involved overexpressing constitutively active Mnk1 (caMNK1) in MCF10 variants: (1) MCF10A immortalized mammary epithelial cells and (2) MCFDCIS.com ductal carcinoma in situ cells (termed DCIS cells). Our in vitro results suggest that caMNK1 enables DCIS cells to gain invasive properties. First, overexpression of caMnk1 increased colony formation, larger acinar size in 3D culture, and promoted the migration and invasion of MCF10A and MCFDCIS cells. Second, SEL201, a novel Mnk1/2 inhibitor, can inhibit proliferation, colony formation, 3D acini formation, and the migration and invasion capacity of DCIS-pBABE and -caMNK1 expressing cells. Tumor xenografting in athymic nude mice revealed that caMNK1 facilitates the conversion of DCIS to IDC as the DCIS-caMNK1 expressing tumors progress to IDC, while DCIS-pBABE derived tumors retain DCIS-like structures. Breast tumor samples from patients with DCIS, IDC or mixed DCIS-IDC will also be obtained to examine the levels of phospho-Mnk1 and phospho-eIF4E. Citation Format: Qianyu Guo, Sonia V. del Rincon, Christophe Goncalves, Wilson H. Miller. MNK1 promotes the progression of breast ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC). [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 686.

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: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

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)0.0030.001

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 head0.033
GPT teacher head0.356
Teacher spread0.324 · 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
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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