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Record W4254376651 · doi:10.1158/1538-7445.am2019-3554

Abstract 3554: miR-139 is associated with improved prognosis in patients with localized prostate cancer

2019· article· en· W4254376651 on OpenAlexaff
Tania Benatar, Robert K. Nam, Elizabeth Kobylecky, Yutaka Amemiya, Arun Seth

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCircular RNAs in diseases
Canadian institutionsPublic Health OntarioOntario GenomicsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsProstate cancerMedicineBiochemical recurrenceProstatectomyProportional hazards modelOncologyHazard ratioInternal medicinemicroRNAMetastasisCancerSurgical marginLymph nodeSurvival analysisStage (stratigraphy)BiologyGeneConfidence interval

Abstract

fetched live from OpenAlex

Abstract Background: We previously identified a panel of five miRNAs associated with biochemical recurrence and metastasis following prostatectomy based on NGS-based whole miRNome discovery and qPCR-based validation analysis. In this analysis, we examine the effect of miR-139-5p, one of the down-regulated miRNAs identified in the panel, in greater detail. Methods: Using a cohort of 585 patients treated with radical prostatectomy, we examined the prognostic significance of miR-139 (dichotomized around the median) using the Kaplan Meier method and Cox proportional hazard models. We validated these results using The Cancer Genome Atlas (TCGA) data. We created cell lines that over-expressed miR-139 or transiently transfected cells using miR-139 mimics for functional assays. Finally, we examined pathways through which miR-139 may function using prediction algorithms and confirmed targets by Western blotting and reporter assays. Results: MiR-139 down-regulation was significantly associated with a variety of accepted prognostic factors in prostate cancer, including Gleason score, pathologic stage, margin positivity and lymph node status. MiR-139 was associated with prognosis: the cumulative incidence of biochemical recurrence and metastasis were significantly lower among patients with high miR-139 expression (p=0.0004 and 0.038, respectively). After adjusting for known prognostic factors, patients with high miR-139 expression had significantly lower risk of recurrence (HR 0.77, 95% 0.58-1.04). Validation in the TCGA dataset showed a significant association between dichotomized miR-139 expression and biochemical recurrence (OR 0.52, 95% CI 0.33-0.82). Over-expression of miR-139 in prostate cancer cells led to a significant reduction in cell proliferation and migration compared to control cells, with cells arrested in G2 of cell cycle. IGF1R, RUNX1 and AXL were identified as potential gene targets of miR-139 based on their association with prostate cancer growth pathways and multiple miRNA binding site prediction tools. The reporter assays using luciferase gene constructs containing the predicted miRNA targeting sequence from IGFR1 and RUNX1 verified them as direct targets of miR-139. Furthermore, Western blotting of prostate cancer cells demonstrated RUNX1 and AXL expression were inhibited by miR-139 treatment, which was reversed by addition of miR-139 antagomir. Examination of the molecular mechanism of growth inhibition by miR-139 revealed the downregulation of activated Akt and cyclin D1, with upregulation of the CDK inhibitor p21. Conclusions: miR-139 is associated with improved prognosis in patients with localized prostate cancer, which may be mediated through inhibition of IGF1R, RUNX1 and/or AXL and their associated growth signaling pathways. Citation Format: Tania Benatar, Robert K. Nam, Elizabeth Kobylecky, Yutaka Amemiya, Arun K. Seth. miR-139 is associated with improved prognosis in patients with localized prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3554.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.612

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 head0.018
GPT teacher head0.327
Teacher spread0.310 · 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 designObservational
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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