Evidence map›Paper›PMID 27322337›Full record

ReviewJournal of clinical medicine2016

The Role of microRNAs in the Diagnosis and Treatment of Pancreatic Adenocarcinoma.

Maria Diab, Irfana Muqbil, Ramzi M Mohammad, Asfar S Azmi, Philip A Philip

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  7. Review
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  14. MicroRNA-206 Inhibited the Progression of Glioblastoma Through BCL-2.Journal of molecular neuroscience : MN · 2016
    Article
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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

5 authors.

Maria DiabDepartment of Internal Medicine, School of Medicine, Wayne State University, Detroit, MI 48201, USA. diab.maria@gmail.com.
Irfana MuqbilDepartment of Oncology, Karmanos Cancer institute, Wayne State University, Detroit, MI 48201, USA. irfana.muqbil@wayne.edu.
Ramzi M MohammadDepartment of Oncology, Karmanos Cancer institute, Wayne State University, Detroit, MI 48201, USA. mohammar@karmanos.org.
Asfar S AzmiDepartment of Oncology, Karmanos Cancer institute, Wayne State University, Detroit, MI 48201, USA. azmia@karmanos.org.
Philip A PhilipDepartment of Oncology, Karmanos Cancer institute, Wayne State University, Detroit, MI 48201, USA. philipp@karmanos.org.

Funding

Targeting PAK4 for Overcoming Drug Resistance in Pancreatic CancerR21CA188818 · NCI · WAYNE STATE UNIVERSITY · PI AZMI, ASFAR S, MOHAMMAD, RAMZI M. · 2015 to 2016
$366k
NCI NIH HHS R21 CA188818
6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) remains a very challenging malignancy. Disease is diagnosed in an advanced stage in the vast majority of patients, and PDAC cells are often resistant to conventional cytotoxic drugs. Targeted therapies have made no progress in the management of this disease, unlike other cancers. microRNAs (miRs) are small non-coding RNAs that regulate the expression of multitude number of genes by targeting their 3'-UTR mRNA region. Aberrant expression of miRNAs has been linked to the development of various malignancies, including PDAC. In PDAC, a series of miRs have been defined as holding promise for early diagnostics, as indicators of therapy resistance, and even as markers for therapeutic response in patients. In this mini-review, we present an update on the various different miRs that have been defined in PDAC biology.

Indexed as

biologydiagnosismicro-RNApancreatic ductal adenocarcinomaprognosistherapy

Identifiers

PMID27322337
PMCPMC4929414

What OpenQuestion holds

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Registered trials

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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.