Evidence map›Paper›PMID 23185449›Full record

SynthesisPloS one2012

Molecular pathways involved in prostate carcinogenesis: insights from public microarray datasets.

Sarah C Baetke, Michiel E Adriaens, Renaud Seigneuric, Chris T Evelo, Lars M T Eijssen

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 2012. 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
0.8field-weighted citation impact, top 26% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
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  4. Article
  5. Review
  6. Article
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  9. Article
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  11. Clinical significance of NUCB2 mRNA expression in prostate cancer.Journal of experimental & clinical cancer research : CR · 2013
    Article
  12. Article
  13. Prostatic Carcinogenesis: More Insights.Journal of microscopy and ultrastructure
    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 2 institutions in 3 countries.

Sarah C BaetkeDepartment of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands.
Michiel E Adriaens
Renaud Seigneuric
Chris T Evelo
Lars M T Eijssen
Maastricht University · NLUniversité de Bourgogne · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProstate cancer is currently the most frequently diagnosed malignancy in men and the second leading cause of cancer-related deaths in industrialized countries. Worldwide, an increase in prostate cancer incidence is expected due to an increased life-expectancy, aging of the population and improved diagnosis. Although the specific underlying mechanisms of prostate carcinogenesis remain unknown, prostate cancer is thought to result from a combination of genetic and environmental factors altering key cellular processes. To elucidate these complex interactions and to contribute to the understanding of prostate cancer progression and metastasis, analysis of large scale gene expression studies using bioinformatics approaches is used to decipher regulation of core processes. METHODOLOGY/PRINCIPAL

findingsIn this study, a standardized quality control procedure and statistical analysis (http://www.arrayanalysis.org/) were applied to multiple prostate cancer datasets retrieved from the ArrayExpress data repository and pathway analysis using PathVisio (http://www.pathvisio.org/) was performed. The results led to the identification of three core biological processes that are strongly affected during prostate carcinogenesis: cholesterol biosynthesis, the process of epithelial-to-mesenchymal transition and an increased metabolic activity.

conclusionsThis study illustrates how a standardized bioinformatics evaluation of existing microarray data and subsequent pathway analysis can quickly and cost-effectively provide essential information about important molecular pathways and cellular processes involved in prostate cancer development and disease progression. The presented results may assist in biomarker profiling and the development of novel treatment approaches.

Indexed as

Biomarkers, TumorCell Transformation, NeoplasticMetabolic Networks and PathwaysProstatic NeoplasmsComputational BiologyGene Expression Regulation, NeoplasticHumansMaleOligonucleotide Array Sequence AnalysisBiomarkers, Tumor

Identifiers

PMID23185449
PMCPMC3502280
OpenAlexW2015094239

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.