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Record W1498789110 · doi:10.1158/1538-7445.am2014-4369

Abstract 4369: The microRNA-218-survivin axis regulates cervical cancer cell migration and invasion

2014· article· en· W1498789110 on OpenAlexaff
Ryunosuke Kogo, Christine How, Jeff Bruce, Willa Shi, Kenneth W. Yip, Laurie Ailles, Fei‐Fei Liu

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsSurvivinClonogenic assayTransfectionGene knockdownmicroRNACancer researchBiologyCervical cancerMolecular biologyCellCancerCell cultureGeneGenetics

Abstract

fetched live from OpenAlex

Abstract MicroRNA (miR)-218 down-regulation has been reported in numerous human malignancies. In cervical cancer, we identified that lower miR-218 expression was significantly associated with poorer overall survival, disease-free survival, and pelvic/para-aortic lymph node recurrence. Further analyses of cervical cancer data from The Cancer Genome Atlas (TCGA) identified that this down-regulation was associated with a genomic locus loss (hsa-mir-218-1:4p15.31, hsa-mir-218-2:5q34, n=105). The objective of the current study was to elucidate the cellular and molecular functions of miR-218. MiR-218 transfection into cervical cancer cells (SiHa and ME-180) significantly reduced cell migration (by 66% and 89%, respectively), invasion (by 49% and 67%, respectively), and clonogenic capacity (by 42% and 53%, respectively), relative to control-transfected cells (P<0.05). In order to identify clinically relevant miR-218 target genes, we used an integrated trimodal approach, incorporating DNA microarray (Affymetrix Human Genome U133 Plus 2.0) analyses of 79 clinical samples, miR-218 transfection, and miRDB target prediction. The most significant target was survivin (BIRC5); miR-218 transfection confirmed a reduction in survivin mRNA and protein expression in both SiHa and ME-180 cells. Furthermore, a direct interaction between the survivin-3′UTR and miR-218 was validated using a luciferase reporter assay. siRNA knockdown of survivin in SiHa and ME-180 significantly reduced cell migration (by 76% and 83%, respectively), invasion (by 79% and 88%, respectively), and clonogenic capacity (by 98% and 97%, respectively), relative to control cells (P<0.05). YM155, a small-molecule survivin suppressant, effectively reduced survivin mRNA and protein levels in a concentration- and time-dependent manner. This compound correspondingly decreased cervical cancer cell proliferation and clonogenic survival. Our results suggest that the miR-218-survivin axis plays an important role in cervical cancer progression. Citation Format: Ryunosuke Kogo, Christine How, Jeff Bruce, Willa Shi, Kenneth W. Yip, Laurie Ailles, Fei-Fei Liu. The microRNA-218-survivin axis regulates cervical cancer cell migration and invasion. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4369. doi:10.1158/1538-7445.AM2014-4369

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 score0.003
Threshold uncertainty score0.009

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)0.0030.001

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 head0.030
GPT teacher head0.330
Teacher spread0.299 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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