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Record W2944121001 · doi:10.1139/bcb-2018-0380

MicroRNA-211-5p promotes apoptosis and inhibits the migration of osteosarcoma cells by targeting proline-rich protein PRR11

2019· article· en· W2944121001 on OpenAlexvenueno aff
Dandan Song, Kun Yang, Wei Wang, Run Tian, Haoyu Wang, Kunzheng Wang

Bibliographic record

VenueBiochemistry and Cell Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsnot available
Fundersnot available
KeywordsOsteosarcomaApoptosisCancer researchmicroRNACarcinogenesisIn vivoBiologyMetastasisCell cultureCell migrationGeneCancerGenetics

Abstract

fetched live from OpenAlex

Osteosarcoma remains fatal in adolescents and young adults, with a 5-year survival rate of less than 20%. However, the details for mechanisms that regulate osteosarcoma metastasis are poorly understood. We analyzed the expression levels of miR-211-5p in clinical samples of osteosarcoma as well as cell lines, and found that the expression of miR-211-5p was reduced in osteosarcoma. Moreover, induction of miR-211-5p in several osteosarcoma cell lines dramatically inhibited their migration and invasiveness. Furthermore, miR-211-5p overexpression led to a significant increase in the apoptosis of osteosarcoma cell. Importantly, our in vivo xenograft experiments showed that miR-211-5p strongly inhibits tumorigenesis. Additionally, functional experiments demonstrated that miR-211-5p suppresses the expression of proline-rich protein 11 (PRR11) by directly binding to the 3' region of PRR11 mRNA. Moreover, we showed that PRR11 overexpression attenuated the increase of apoptosis and decreased migration and invasiveness when the upstream miR-211-5p was overexpressed. Our data provide new insights into the mechanisms that regulate osteosarcoma metastasis, and novel potential pharmaceutical targets for personalized medicine.

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 score0.008
Threshold uncertainty score0.595

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 head0.003
GPT teacher head0.189
Teacher spread0.186 · 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

Citations18
Published2019
Admission routes1
Has abstractyes

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