Evidence map›Paper›PMID 26238304›Full record

SynthesisPituitary2016

Gene expression in prolactinomas: a systematic review.

Justin Seltzer, Thomas C Scotton, Keiko Kang, Gabriel Zada, John D Carmichael

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Pituitary, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 22% of its field
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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Relation among Aromatase P450 and Tumoral Growth in Human Prolactinomas.International journal of molecular sciences · 2017
    Review
  7. 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

5 authors at 1 institution in 1 country.

Justin SeltzerDepartment of Neurosurgery, Keck School of Medicine of USC, 1200 North State St., Los Angeles, CA, 90033, USA. jseltzer@usc.edu.ORCID http://orcid.org/0000-0002-1628-5878
Thomas C ScottonSemel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Keiko KangDepartment of Neurosurgery, Keck School of Medicine of USC, 1200 North State St., Los Angeles, CA, 90033, USA.
Gabriel ZadaDepartment of Neurosurgery, Keck School of Medicine of USC, 1200 North State St., Los Angeles, CA, 90033, USA.
John D CarmichaelDivision of Endocrinology, Department of Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA.
Keck Hospital of USC · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionProlactinomas are the most common functional pituitary adenomas. Current classification systems rely on phenotypic elements and have few molecular markers for complementary classification. Treatment protocols for prolactinomas are also devoid of molecular targets, leaving those refractory to standard treatments without many options.

methodsA systematic literature review was performed utilizing the PRISMA guidelines. We aimed to summarize prior research exploring gene and protein expression in prolactinomas in order to highlight molecular variations associated with tumor development, growth, and prolactin secretion. A PubMed search of select MeSH terms was performed to identify all studies reporting gene and protein expression findings in prolactinomas from 1990 to 2014.

results1392 abstracts were screened and 51 manuscripts were included in the analysis, yielding 54 upregulated and 95 downregulated genes measured by various direct and indirect analytical methods. Of the many genes identified, three upregulated (HMGA2, HST, SNAP25), and three downregulated (UGT2B7, Let7, miR-493) genes were selected for further analysis based on our subjective identification of strong potential targets.

conclusionsMany significant genes have been identified and validated in prolactinomas and most have not been fully analyzed for therapeutic and diagnostic potential. These genes could become candidate molecular targets for biomarker development and precision drug targeting as well as catalyze deeper research efforts utilizing next generation profiling/sequencing techniques, particularly genome scale expression and epigenomic analyses.

Indexed as

Gene Expression Regulation, NeoplasticHumansPituitary NeoplasmsProlactinomaGene expressionLactotrophPituitary adenomaProlactinProlactinomaProtein expression

Identifiers

PMID26238304
OpenAlexW2249510383

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.