Evidence map›Paper›PMID 36420213›Full record

ArticleMolecular therapy. Nucleic acids2022

CRIT: Identifying RNA-binding protein regulator in circRNA life cycle via non-negative matrix factorization.

Mengting Shao, Shijia Hao, Leiming Jiang, Yujie Cai, Xing Zhao, Qiuyang Chen, Xuefei Gao, Jianzhen Xu

Open access · goldAbstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Circular RNAs in Cell Cycle Regulation of Cancers.International journal of molecular sciences · 2024
    Review
  6. Article
  7. Article
  8. Review
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 4 institutions in 2 countries.

Mengting ShaoComputational Systems Biology Lab, Department of Bioinformatics, Shantou University Medical College (SUMC), 515041 Shantou, China.
Shijia HaoComputational Systems Biology Lab, Department of Bioinformatics, Shantou University Medical College (SUMC), 515041 Shantou, China.
Leiming JiangComputational Systems Biology Lab, Department of Bioinformatics, Shantou University Medical College (SUMC), 515041 Shantou, China.
Yujie CaiComputational Systems Biology Lab, Department of Bioinformatics, Shantou University Medical College (SUMC), 515041 Shantou, China.
Xing ZhaoComputational Systems Biology Lab, Department of Bioinformatics, Shantou University Medical College (SUMC), 515041 Shantou, China.
Qiuyang ChenComputational Systems Biology Lab, Department of Bioinformatics, Shantou University Medical College (SUMC), 515041 Shantou, China.
Xuefei GaoDepartment of Physiology, School of Basic Medical Sciences, Southern Medical University, 510515 Guangzhou, China.
Jianzhen XuComputational Systems Biology Lab, Department of Bioinformatics, Shantou University Medical College (SUMC), 515041 Shantou, China.
Shantou University · CNGuangdong Medical College · CNKey Laboratory of Guangdong Province · CNUniversity Medical Center Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circular RNAs (circRNAs) are endogenous non-coding RNAs that regulate gene expression and participate in carcinogenesis. However, the RNA-binding proteins (RBPs) involved in circRNAs biogenesis and modulation remain largely unclear. We developed the circRNA regulator identification tool (CRIT), a non-negative matrix-factorization-based pipeline to identify regulating RBPs in cancers. CRIT uncovered 73 novel regulators across thousands of samples by effectively leveraging genomics data and functional annotations. We demonstrated that known RBPs involved in circRNA control are significantly enriched in these predictions. Analysis of circRNA-RBP interactions using two large cross-linking immunoprecipitation (CLIP) databases, we validated the consistency between CRIT prediction and the CLIP experiments. Furthermore, newly discovered RBPs are functionally connected with authentic circRNA regulators by various biological associations, such as physical interaction, similar binding motifs, common transcription factor modulation, and co-expression. When analyzing RNA sequencing (RNA-seq) datasets after short hairpin RNA (shRNA)/small interfering RNA (siRNA) knockdown, we found several novel RBPs that can affect global circRNA expression, which strengthens their role in the circRNA life cycle. The above evidence provided independent confirmation that CRIT is a useful tool to capture RBPs in circRNA processing. Finally, we show that authentic regulators are more likely the core splicing proteins and peripheral factors and usually harbor more alterations in the vast majority of cancers.

Indexed as

cancercircular RNAdata integrationMT:Bioinformaticsnon-negative matrix factorizationRNA-binding protein

Identifiers

PMID36420213
PMCPMC9664520
OpenAlexW4307724421

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.