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Record W2460494782 · doi:10.3390/ijms17071025

CD133 Modulate HIF-1α Expression under Hypoxia in EMT Phenotype Pancreatic Cancer Stem-Like Cells

2016· article· en· W2460494782 on OpenAlexaff
Koki Maeda, Qiang Ding, Makoto Yoshimitsu, Taisaku Kuwahata, Yumi Miyazaki, Koichirou Tsukasa, Tomomi Hayashi, Hiroyuki Shinchi, Shoji Natsugoe, Sonshin Takao

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsSt. Michael's Hospital
FundersNational Institutes of Health
KeywordsHypoxia (environmental)Pancreatic cancerPhenotypeStem cellCancer stem cellCancer researchCell biologyChemistryBiologyCancerGeneBiochemistryGeneticsOxygen

Abstract

fetched live from OpenAlex

UNLABELLED: Although CD133 is a known representative cancer stem cell marker, its function in tumor aggressiveness under hypoxia is not fully known. The aim of this study is to demonstrate that CD133 regulates hypoxia inducible factor (HIF)-1α expression with tumor migration. The CD133⁺ pancreatic cancer cell line, Capan1M9, was compared with the CD133(-) cell line, shCD133M9, under hypoxia. HIF-1α expression levels were compared by Western blot, HIF-1α nucleus translocation assay and real-time (RT)-PCR. The hypoxia responsive element (HRE) was observed by luciferase assay. The migration ability was analyzed by migration and wound healing assays. Epithelial mesenchymal transition (EMT) related genes were analyzed by real-time RT-PCR. HIF-1α was highly expressed in Capan1M9 compared to shCD133M9 under hypoxia because of the high activation of HRE. Furthermore, the migration ability of Capan1M9 was higher than that of shCD133M9 under hypoxia, suggesting higher expression of EMT related genes in Capan1M9 compared to shCD133M9. CONCLUSION: HIF-1α expression under hypoxia in CD133⁺ pancreatic cancer cells correlated with tumor cell migration through EMT gene expression. Understanding the function of CD133 in cancer aggressiveness provides a novel therapeutic approach to eradicate pancreatic cancer stem cells.

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 score0.030
Threshold uncertainty score0.366

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 head0.025
GPT teacher head0.307
Teacher spread0.282 · 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

Citations42
Published2016
Admission routes1
Has abstractyes

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