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Record W2952686936 · doi:10.1016/j.ebiom.2019.06.009

A role for kinesin-1 subunits KIF5B/KLC1 in regulating epithelial mesenchymal plasticity in breast tumorigenesis

2019· article· en· W2952686936 on OpenAlexafffundabout
Alaa Moamer, Ibrahim Y. Hachim, Najat Binothman, Ni Wang, Jean‐Jacques Lebrun, Suhad Ali

Bibliographic record

VenueEBioMedicine · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsMcGill University Health Centre
FundersCanadian Institutes of Health ResearchMcGill University Health Centre
KeywordsKinesinCarcinogenesisCell biologyCancer researchBiologyChemistryMedicineGeneticsCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Epithelial mesenchymal plasticity (EMP) is deemed vital in breast cancer progression, metastasis, stemness and resistance to therapy. Therefore, characterizing molecular mechanisms contributing to EMP are in need enabling the development of more advanced therapeutics against breast cancer. While kinesin superfamily proteins (KIFs) are well known for their role in intracellular cargo movement, our knowledge of their function in breast tumorigenesis is still limited. METHODS: Various breast cancer cell lines representing different molecular subtypes were used to determine the role of kinesine-1 subunits KIF5B/KLC1 in regulation of EMP. FINDINGS: In breast cancer, we show that kinesin family member 5B (KIF5B) and its partner protein kinesin light chain 1 (KLC1), subunits of kinesin-1, to play differential roles in regulating EMP and tumorigenesis. Indeed, we found KIF5B to be expressed in triple negative (TN)-basal-like/claudin low breast cancer subtype and to be an inducer of epithelial-mesenchymal transition (EMT), stemness, invasiveness, tumor formation and metastatic colonization. Whereas, we found KLC1 to be expressed in epithelial/luminal breast cancer subtypes and to be a suppressor of EMT, invasion, metastasis and stem cell markers expression as well as to be an inducer of epithelial/luminal phenotype. Interestingly, in TN-basal-like/claudin low cells we found a novel nuclear accumulation of KIF5B and its interaction with the EMT transcriptional regulator Snail1 independent of KLC1. In addition, TGF-β mediated pro-invasive activity was found to be dependent on KIF5B expression. In contrast, the epithelial differentiation factor and EMT suppressor prolactin (PRL) was found to repress KIF5B gene expression and KIF5B-Snail1 nuclear accumulation, but enhanced KLC1 gene expression and KIF5B-KLC1 interaction. INTERPRETATION: Together, these results highlight a new paradigm for kinesin-1 function in breast tumorigenesis by regulating EMP programing and aggressiveness. FUND: This work was supported by the Canadian Institutes of Health Research (operating grants #233437 and 233438) granted to Suhad Ali.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.412
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.005
GPT teacher head0.227
Teacher spread0.222 · 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 teacher head, 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

Citations45
Published2019
Admission routes3
Has abstractyes

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