Evidence map›Paper›PMID 35078526›Full record

ArticleGenome medicine2022

The transcriptional landscape and biomarker potential of circular RNAs in prostate cancer.

Emma Bollmann Hansen, Jacob Fredsøe, Trine Line Hauge Okholm, Benedicte Parm Ulhøi, Søren Klingenberg, Jørgen Bjerggaard Jensen, Jørgen Kjems, Kirsten Bouchelouche, Michael Borre, Christian Kroun Damgaard and 3 more

Abstract read
In one paragraph

Article in Genome medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

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

  1. Pooled it
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  7. Review
  8. Article
  9. Development of Mathematical Models Using circRNA Combinations (International journal of molecular sciences · 2025
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  11. Review
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  14. Article
  15. Article
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  17. Review
  18. Circular RNA in cancer.Nature reviews. Cancer · 2024
    Review
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  20. 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

13 authors.

Emma Bollmann HansenDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus, Denmark.
Jacob FredsøeDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus, Denmark.
Trine Line Hauge OkholmDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus, Denmark.
Benedicte Parm UlhøiDepartment of Pathology, Aarhus University Hospital, Aarhus, Denmark.
Søren KlingenbergDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus, Denmark.
Jørgen Bjerggaard JensenDepartment of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Jørgen KjemsDepartment of Molecular Biology and Genetics (MBG), Aarhus University, Aarhus, Denmark.
Kirsten BoucheloucheDepartment of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Michael BorreDepartment of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Christian Kroun DamgaardDepartment of Molecular Biology and Genetics (MBG), Aarhus University, Aarhus, Denmark.
Jakob Skou PedersenDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus, Denmark.
Lasse Sommer KristensenDepartment of Biomedicine, Aarhus University, Aarhus, Denmark.
Karina Dalsgaard SørensenDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus, Denmark. kdso@clin.au.dk.ORCID 0000-0002-4902-5490

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCircular RNAs (circRNAs) constitute a largely unexplored source for biomarker discovery in prostate cancer (PC). Here, we characterize the biomarker potential of circRNAs in PC, where the need for novel diagnostic and prognostic tools to facilitate more personalized management is pressing.

methodsWe profiled the transcriptomic landscape of circRNAs in PC by total RNA sequencing of 31 adjacent-normal and 143 tumor samples from localized (radical prostatectomy (RP)) and metastatic PC patients (cohort 1, training). Diagnostic and prognostic potential was evaluated in cohort 1, and 39 top circRNA candidates were selected for validation in two additional PC cohorts (cohort 2, n = 111; RP cohort 3, n = 191) by NanoString-based expression analysis. Biochemical recurrence (BCR)-free survival was assessed using Kaplan-Meier, univariate, and multivariate Cox regression analyses. The circRNA candidates were further detected in extracellular vesicle (EV)-enriched plasma samples from PC patients and controls (cohort 4, n = 54).

resultsExpression of circABCC4, circFAT3, circATRNL1, and circITGA7 was highly cancer-specific (area under the curve 0.71-0.86), while low circITGA7 expression was significantly (P < 0.05) associated with BCR in univariate analysis in two RP cohorts. Moreover, we successfully trained and validated a novel 5-circRNA prognostic signature (circKMD1A/circTULP4/circZNF532/circSUMF1/circMKLN1) significantly associated with BCR beyond routine clinicopathological variables (RP cohort 1: P = 0.02, hazard ratio = 2.1; RP cohort 3: P < 0.001, hazard ratio = 2.1). Lastly, we provide proof-of-principle for detection of candidate circRNAs in EV-enriched plasma samples from PC patients.

conclusionscircRNAs hold great biomarker potential in PC and display both high cancer specificity and association to disease progression.

Indexed as

Prostatic NeoplasmsRNA, CircularBiomarkers, TumorHumansMaleNeoplasm Recurrence, LocalPrognosisProstatectomyBiomarkers, TumorRNA, CircularBiomarkerCancercircRNAProstate

Identifiers

PMID35078526
PMCPMC8788096

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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.