Evidence map›Paper›PMID 30735636›Full record

ArticleCell2019

The Landscape of Circular RNA in Cancer.

Josh N Vo, Marcin Cieslik, Yajia Zhang, Sudhanshu Shukla, Lanbo Xiao, Yuping Zhang, Yi-Mi Wu, Saravana M Dhanasekaran, Carl G Engelke, Xuhong Cao and 3 more

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 981 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
981citing papers in PubMed, 2 pooled it
119.6field-weighted citation impact, top 1% 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

981 citing papers in PubMed, 2 syntheses or guidelines pooled it, 2,031 citations in OpenAlex.

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  17. Acta pharmaceutica Sinica. B · 2026
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921 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 2 countries.

Josh N VoDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Marcin CieslikDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Yajia ZhangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Sudhanshu ShuklaMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, 580011, India.
Lanbo XiaoMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Yuping ZhangMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Yi-Mi WuMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Saravana M DhanasekaranMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Carl G EngelkeMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Xuhong CaoMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Dan R RobinsonMichigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
Alexey I NesvizhskiiDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: nesvi@med.umich.edu.
Arul M ChinnaiyanDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Howard Hughes Medical Institute, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA; Department of Urology, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: arul@umich.edu.
University of Michigan · USHoward Hughes Medical Institute · US

Funding

TRANSCRIPTOME AND PROTEOME STRATIFICATION OF PROSTATE ADENOCARCINOMA PHENOTYPESP50CA097186 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI John Kyung Lee · 2002 to 2026
$58.1M
Tissue/InformaticsP50CA186786 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Robert Timothy Dess · 2014 to 2026
$27.6M
Exploring Precision Oncology: From Gene Fusions to lncRNAsR35CA231996 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHINNAIYAN, ARUL M · 2018 to 2024
$6.4M
University of Michigan Proteogenomics Data Analysis CenterU24CA210967 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHINNAIYAN, ARUL M, DHANASEKARAN, SARAVANA M · 2016 to 2020
$4.1M
Discovery and qualification of transcriptomic biomarkers for the early detection of aggressive prostate cancerU01CA214170 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHINNAIYAN, ARUL M · 2016 to 2021
$3.3M
Howard Hughes Medical InstituteNCI NIH HHS P50 CA097186NCI NIH HHS P50 CA186786NCI NIH HHS R35 CA231996NCI NIH HHS U01 CA214170NCI NIH HHS U24 CA210967
6 · The paper itself

Abstract

Circular RNAs (circRNAs) are an intriguing class of RNA due to their covalently closed structure, high stability, and implicated roles in gene regulation. Here, we used an exome capture RNA sequencing protocol to detect and characterize circRNAs across >2,000 cancer samples. When compared against Ribo-Zero and RNase R, capture sequencing significantly enhanced the enrichment of circRNAs and preserved accurate circular-to-linear ratios. Using capture sequencing, we built the most comprehensive catalog of circRNA species to date: MiOncoCirc, the first database to be composed primarily of circRNAs directly detected in tumor tissues. Using MiOncoCirc, we identified candidate circRNAs to serve as biomarkers for prostate cancer and were able to detect circRNAs in urine. We further detected a novel class of circular transcripts, termed read-through circRNAs, that involved exons originating from different genes. MiOncoCirc will serve as a valuable resource for the development of circRNAs as diagnostic or therapeutic targets across cancer types.

Indexed as

Biomarkers, TumorDatabases, GeneticExome SequencingGene Expression ProfilingGene Expression Regulation, NeoplasticHigh-Throughput Nucleotide SequencingHumansMicroRNAsNeoplasmsRNARNA, CircularSequence Analysis, RNABiomarkers, TumorMicroRNAsRNARNA, CircularbiomarkerscancercircRNAcircRNA databaseexome capture sequencingnon-coding RNAread-through transcripts

Identifiers

PMID30735636
PMCPMC6601354
OpenAlexW2912017471

What OpenQuestion holds

Textmetadata
LicenceTDM
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.