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Record W2127749273 · doi:10.1177/1947601911408888

Impaired MicroRNA Processing Facilitates Breast Cancer Cell Invasion by Upregulating Urokinase-Type Plasminogen Activator Expression

2011· article· en· W2127749273 on OpenAlexaff
Hyunjin Noh, Soon Auck Hong, Zheng Dong, Zhixing K. Pan, Qing Jing, Shuang Huang

Bibliographic record

VenueGenes & Cancer · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsInstitute for Biological Sciences
FundersNational Cancer InstituteNational Heart, Lung, and Blood Institute
KeywordsDicerDroshamicroRNAGene knockdownUrokinase receptorBiologyCancer researchGene silencingCancer cellDownregulation and upregulationRNA interferenceCancerCell cultureCellTransfectionSmall interfering RNARNAGenetics

Abstract

fetched live from OpenAlex

Global mature microRNA (miRNA) expression is downregulated in cancers, and impaired miRNA processing enhances cancer cell proliferation. These findings indicate that the miRNA system generally serves as a negative regulator during cancer progression. In this study, we investigated the role of the miRNA system in cancer cell invasion by determining the effect of damaging miRNA processing on invasion-essential urokinase-type plasminogen activator (uPA) expression in breast cancer cells. Short hairpin RNAs specific for Drosha, DGCR8, and Dicer, key components of miRNA processing machinery, were introduced into 2 breast cancer cell lines with high uPA expression and 2 lines with poor uPA expression. Knockdown of Drosha, DGCR8, or Dicer led to even higher uPA expression in cells with high uPA expression, while it was unable to increase uPA level in cells with poor uPA expression, suggesting that the miRNA system most likely impacts uPA expression as a facilitator. In cells with high uPA expression, knockdown of Drosha, DGCR8, or Dicer substantially increased in vitro invasion, and depleting uPA abrogated enhanced invasion. These results thus link the augmented invasion conferred by impaired miRNA processing to upregulated uPA expression. uPA mRNA was a direct target of miR-193a/b and miR-181a, and a higher uPA level in cells with impaired miRNA processing resulted from less mature miR-193a/b and miR-181a processed from their respective primary miRNAs. Importantly, the levels of mature miR-193a, miR-193b, and miR-181a, but not their respective primary miRNAs, were lower in high uPA-expressing cells compared to cells with low uPA expression, and this apparently attributed to lower Drosha/DGCR8 expression in high uPA-expressing cells. This study suggests that less efficient miRNA processing can be a mechanism responsible for reduced levels of mature forms of tumor-suppressive miRNAs frequently detected in cancers.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.018
GPT teacher head0.247
Teacher spread0.228 · 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

Citations51
Published2011
Admission routes1
Has abstractyes

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