Evidence map›Paper›PMID 26382040›Full record

ArticleJournal of visualized experiments : JoVE2015

miRNA Expression Analyses in Prostate Cancer Clinical Tissues.

Nathan Bucay, Varahram Shahryari, Shahana Majid, Soichiro Yamamura, Yozo Mitsui, Z Laura Tabatabai, Kirsten Greene, Guoren Deng, Rajvir Dahiya, Yuichiro Tanaka and 1 more

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Reference Genes for qPCR-Based miRNA Expression Profiling in 14 Human Tissues.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2022
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Nathan BucayDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Varahram ShahryariDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Shahana MajidDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Soichiro YamamuraDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Yozo MitsuiDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Z Laura TabatabaiDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Kirsten GreeneDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Guoren DengDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Rajvir DahiyaDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Yuichiro TanakaDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco.
Sharanjot SainiDepartment of Urology, Veterans Affairs Medical Center, San Francisco, University of California San Francisco; SainiS@urology.ucsf.edu.

Funding

MicroRNAs in the Progression and Metastisis of Prostate CancerR01CA138642 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DAHIYA, RAJVIR · 2010 to 2014
$2.6M
MicroRNAs in frequently deleted loci regulate prostate cancer EMT and metastasisR01CA177984 · NCI · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI SAINI, SHARANJOT · 2014 to 2018
$1.9M
Role of genetic biomarkers in clinical assessment of prostate cancerIP1BX001604 · VA · VETERANS AFFAIRS MED CTR SAN FRANCISCO · PI DAHIYA, RAJVIR, LAU, YUN-FAI CHRIS · 2013 to 2016
–
BLRD VA IP1 BX001604NCI NIH HHS R01 CA138642NCI NIH HHS R01CA138642NCI NIH HHS R01 CA177984NCI NIH HHS R01CA177984
6 · The paper itself

Abstract

A critical challenge in prostate cancer (PCa) clinical management is posed by the inadequacy of currently used biomarkers for disease screening, diagnosis, prognosis and treatment. In recent years, microRNAs (miRNAs) have emerged as promising alternate biomarkers for prostate cancer diagnosis and prognosis. However, the development of miRNAs as effective biomarkers for prostate cancer heavily relies on their accurate detection in clinical tissues. miRNA analyses in prostate cancer clinical specimens is often challenging owing to tumor heterogeneity, sampling errors, stromal contamination etc. The goal of this article is to describe a simplified workflow for miRNA analyses in archived FFPE or fresh frozen prostate cancer clinical specimens using a combination of quantitative real-time PCR (RT-PCR) and in situ hybridization (ISH). Within this workflow, we optimize the existing methodologies for miRNA extraction from FFPE and frozen prostate tissues and expression analyses by Taqman-probe based miRNA RT-PCR. In addition, we describe an optimized method for ISH analyses formiRNA detection in prostate tissues using locked nucleic acid (LNA)- based probes. Our optimized miRNA ISH protocol can be applied to prostate cancer tissue slides or prostate cancer tissue microarrays (TMA).

Indexed as

HumansIn Situ HybridizationMaleMicroRNAsOligonucleotidesParaffin EmbeddingPrognosisProstatic NeoplasmsReal-Time Polymerase Chain ReactionRNA ProbesTissue Fixationlocked nucleic acidMicroRNAsOligonucleotidesRNA Probes

Identifiers

PMID26382040
PMCPMC4692597

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.