Evidence map›Paper›PMID 33760831›Full record

ArticlePloS one2021

Small RNAs as biomarkers to differentiate benign and malign prostate diseases: An alternative for transrectal punch biopsy of the prostate?

Lukas Markert, Jonas Holdmann, Claudia Klinger, Michael Kaufmann, Karin Schork, Michael Turewicz, Martin Eisenacher, Andreas Savelsbergh

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
1.5field-weighted citation impact, top 20% 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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Urinary MicroRNAs as Biomarkers of Urological Cancers: A Systematic Review.International journal of molecular sciences · 2023
    Pooled it
  3. Pooled it
  4. Review
  5. Review
  6. Article
  7. Review
  8. Urinary miRNAs: Technical Updates.MicroRNA (Shariqah, United Arab Emirates) · 2024
    Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. 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

8 authors at 2 institutions in 1 country.

Lukas MarkertDivision of Functional Genomics, Chair for Biochemistry and Molecular Medicine, Witten/Herdecke University, Witten, Germany.ORCID 0000-0002-1739-3619
Jonas HoldmannDivision of Functional Genomics, Chair for Biochemistry and Molecular Medicine, Witten/Herdecke University, Witten, Germany.
Claudia KlingerDivision of Functional Genomics, Chair for Biochemistry and Molecular Medicine, Witten/Herdecke University, Witten, Germany.
Michael KaufmannDivision of Functional Genomics, Chair for Biochemistry and Molecular Medicine, Witten/Herdecke University, Witten, Germany.
Karin SchorkMedizinisches Proteom-Centre, Ruhr-University Bochum, Bochum, Germany.
Michael TurewiczMedizinisches Proteom-Centre, Ruhr-University Bochum, Bochum, Germany.
Martin EisenacherMedizinisches Proteom-Centre, Ruhr-University Bochum, Bochum, Germany.
Andreas SavelsberghDivision of Functional Genomics, Chair for Biochemistry and Molecular Medicine, Witten/Herdecke University, Witten, Germany.
Witten/Herdecke University · DERuhr University Bochum · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer (PCa) is the most common cancer and the third most frequent cause of male cancer death in Germany. MicroRNAs (miRNA) appear to be involved in the development and progression of PCa. A diagnostic differentiation from benign prostate hyperplasia (BPH) is often only possible through transrectal punch biopsy. This procedure is described as painful and carries risks. It was investigated whether urinary miRNAs can be used as biomarkers to differentiate the prostate diseases above. Therefore urine samples from urological patients with BPH (25) or PCa (28) were analysed using Next-Generation Sequencing to detect the expression profile of total and exosomal miRNA/piRNA. 79 miRNAs and 5 piwi-interacting RNAs (piRNAs) were significantly differentially expressed (adjusted p-value < 0.05 and log2-Fc > 1 or < -1). Of these, 6 miRNAs and 2 piRNAs could be statistically validated (AUC on test cohort > = 0.7). In addition, machine-learning algorithms were used to identify a panel of 22 additional miRNAs, whose interaction makes it possible to differentiate the groups as well. There are promising individual candidates for potential use as biomarkers in prostate cancer. The innovative approach of applying machine learning methods to this kind of data could lead to further small RNAs coming into scientific focus, which have so far been neglected.

Indexed as

AdultAgedAged, 80 and overBiomarkersBiomarkers, TumorBiopsyDiagnosis, DifferentialHigh-Throughput Nucleotide SequencingHumansMaleMicroRNAsMiddle AgedProstateProstatic DiseasesProstatic NeoplasmsBiomarkersBiomarkers, TumorMicroRNAs

Identifiers

PMID33760831
PMCPMC7990312
OpenAlexW3136940761

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.