MétaCan
Menu
Back to cohort
Record W2301645580 · doi:10.1002/pros.23177

MiR‐301a regulates E‐cadherin expression and is predictive of prostate cancer recurrence

2016· article· en· W2301645580 on OpenAlexafffund
Robert K. Nam, Tania Benatar, Christopher J.D. Wallis, Yutaka Amemiya, Wen‐Yi Yang, Alaina Garbens, Magda Naeim, Christopher Sherman, Linda Sugar, Arun Seth

Bibliographic record

VenueThe Prostate · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
FundersSunnybrook Foundation
KeywordsProstate cancerMetastasismicroRNACarcinogenesisCancer researchTranscriptomePCA3CancerProstateOncologyEpithelial–mesenchymal transitionMedicineBiologyInternal medicineGene expressionGeneGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: MicroRNAs (miRNAs) are small, noncoding RNAs that regulate gene expression post-transcriptionally. Dysregulation of miRNA has been implicated in the development and progression of prostate cancer. Through next generation miRNA sequencing, we recently identified a panel of five miRNAs associated with prostate cancer recurrence and metastasis. Of the five miRNAs, miR-301a had the strongest association with prostate cancer recurrence. Overexpression of miR-301a in prostate cancer cells, PC3, and LNCaP resulted in increased growth both in vitro and in xenografted tumors. We therefore sought to examine its role in prostate carcinogenesis in greater detail. METHODS: We examined the effect of miR-301a expression on biochemical recurrence and metastasis among 585 men treated with radical prostatectomy for prostate cancer. We examined the mechanism of growth deregulation by miR-301a in prostate cancer cells using analysis of the miRome of prostate cancer cell lines, quantitative PCR, and Western blotting. RESULTS: High levels of miR-301a (above the median) were associated with an increased risk of biochemical recurrence (adjusted hazard ratio [aHR] 1.42, 95% confidence interval (CI) 1.06-1.90, P = 0.002) but not of metastasis (aHR 0.84, 95%CI 0.41-1.70, P = 0.6) after adjustment for known prognostic factors. RNA transcriptome sequencing analysis of miR-301a overexpressing prostate cancer cell lines identified the tumor suppressor p63 as a potential direct miR-301a target. Transcriptome sequencing, qPCR and Western blotting showed that miR-301a induced epithelial-mesenchymal transition (EMT) in prostate cancer cells through a pathway initiated by p63 inhibition. Luciferase assay verified p63 as a direct target of miR-301a. Loss of p63 resulted in miR-205 downregulation, releasing Zeb1 and Zeb2 from inhibition, culminating in Zeb1/Zeb2 suppression of E-cadherin. This pathway of growth alteration mediated by miR-301a upregulation was shown to be valid in prostate cancer cell lines and patient-derived tumors. CONCLUSIONS: These data indicate that miR-301a functions as an oncogene in prostate cancer by directly targeting the p63 tumor suppressor leading to loss of E-cadherin and EMT. Hence, miR-301a may serve as a novel biomarker in prostate cancer as well as a therapeutic target for prostate cancer management. Prostate 76:869-884, 2016. © 2016 Wiley Periodicals, Inc.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.249
Teacher spread0.241 · 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

Citations74
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueThe ProstateSame topicMicroRNA in disease regulationFrench-language works237,207