Literature DB >> 28317618

MiR-1, a Potential Predictive Biomarker for Recurrence in Prostate Cancer After Radical Prostatectomy.

Wei Wei1, Jiangyong Leng2, Hongxiang Shao2, Weidong Wang2.   

Abstract

BACKGROUND: Increasing evidence suggests that aberrant microRNAs expressions are significantly associated with cancer progression. Previous studies have reported that the relative expression of miR-1 is significantly downregulated in recurrent prostate cancer (PCa) samples when compared with nonrecurrent PCa tissues. However, whether miR-1 can serve as a novel predictive biomarker for PCa recurrence still remains unclear.
MATERIALS AND METHODS: The patients with clinically localized PCa who underwent radical prostatectomy by the same medical team at the Department of Urology, Ningbo No.2 Hospital were enrolled in this study. We examined the miR-1 expression levels in recurrent and nonrecurrent tumor samples by quantitative reverse transcription polymerase chain reaction. Univariate and multivariate Cox proportional hazards analyses were used for the evaluation of potential predictors of PCa recurrence.
RESULTS: During the study period, 78 patients (including 27 in the recurrent group and 51 in the nonrecurrent group) who were diagnosed with PCa and who underwent radical prostatectomy were included in the final analysis. MiR-1 was significantly downregulated in recurrent PCa tissues when compared with nonrecurrent tumor samples (P < 0.001). The univariate and multivariate Cox proportional hazards analyses indicated that miR-1 was the only independent prognostic factor for PCa recurrence (hazard ratio = 1.86; 95% CI: 1.21-2.94; P = 0.011). The area under the curve value of miR-1 for PCa recurrence was 0.885 (P < 0.001) with the sensitivity of 0.863 and specificity of 0.889 based on receiver operating characteristic curve analysis.
CONCLUSIONS: This study identifies that miR-1 in PCa tissues can function as an important independent predictive factor for PCa recurrence.
Copyright © 2017 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Biomarker; Prostate cancer; Recurrence; miR-1

Mesh:

Substances:

Year:  2017        PMID: 28317618     DOI: 10.1016/j.amjms.2017.01.006

Source DB:  PubMed          Journal:  Am J Med Sci        ISSN: 0002-9629            Impact factor:   2.378


  9 in total

1.  Evaluation of a 3-base pair indel polymorphism within pre-microRNA-3131 in patients with prostate cancer using mismatch polymerase chain reaction-restriction fragment length polymorphism.

Authors:  Mohammad Hashemi; Gholamreza Bahari; Hedieh Sattarifard; Behzad Narouie
Journal:  Mol Clin Oncol       Date:  2017-08-08

Review 2.  Tissue-Based MicroRNAs as Predictors of Biochemical Recurrence after Radical Prostatectomy: What Can We Learn from Past Studies?

Authors:  Zhongwei Zhao; Carsten Stephan; Sabine Weickmann; Monika Jung; Glen Kristiansen; Klaus Jung
Journal:  Int J Mol Sci       Date:  2017-09-21       Impact factor: 5.923

3.  A Novel Predictor Tool of Biochemical Recurrence after Radical Prostatectomy Based on a Five-MicroRNA Tissue Signature.

Authors:  Zhongwei Zhao; Sabine Weickmann; Monika Jung; Michael Lein; Ergin Kilic; Carsten Stephan; Andreas Erbersdobler; Annika Fendler; Klaus Jung
Journal:  Cancers (Basel)       Date:  2019-10-21       Impact factor: 6.639

4.  High-Throughput and Automated Acoustic Trapping of Extracellular Vesicles to Identify microRNAs With Diagnostic Potential for Prostate Cancer.

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Authors:  Ana Paula Alarcón-Zendejas; Anna Scavuzzo; Miguel A Jiménez-Ríos; Rosa M Álvarez-Gómez; Rogelio Montiel-Manríquez; Clementina Castro-Hernández; Miguel A Jiménez-Dávila; Delia Pérez-Montiel; Rodrigo González-Barrios; Francisco Jiménez-Trejo; Cristian Arriaga-Canon; Luis A Herrera
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8.  Liquid Biopsy to Detect DNA/RNA Based Markers of Small DNA Oncogenic Viruses for Prostate Cancer Diagnosis, Prognosis, and Prediction.

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9.  Exploration of the diagnostic value and molecular mechanism of miR‑1 in prostate cancer: A study based on meta‑analyses and bioinformatics.

Authors:  Zu-Cheng Xie; Jia-Cheng Huang; Li-Jie Zhang; Bin-Liang Gan; Dong-Yue Wen; Gang Chen; Sheng-Hua Li; Hai-Biao Yan
Journal:  Mol Med Rep       Date:  2018-10-25       Impact factor: 2.952

  9 in total

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