Evidence map›Paper›PMID 31432762›Full record

ArticleRNA biology2020

tRic: a user-friendly data portal to explore the expression landscape of tRNAs in human cancers.

Zhao Zhang, Hang Ruan, Chun-Jie Liu, Youqiong Ye, Jing Gong, Lixia Diao, An-Yuan Guo, Leng Han

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

Article in RNA biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

16 citing papers in PubMed, 22 citations in OpenAlex.

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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 3 institutions in 2 countries.

Zhao ZhangDepartment of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston , Houston, TX, USA.
Hang RuanDepartment of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston , Houston, TX, USA.
Chun-Jie LiuDepartment of Bioinformatics and Systems Biology, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology , Wuhan, Hubei, PR China.
Youqiong YeDepartment of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston , Houston, TX, USA.
Jing GongDepartment of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston , Houston, TX, USA.
Lixia DiaoDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center , Houston, TX, USA.
An-Yuan GuoDepartment of Bioinformatics and Systems Biology, Hubei Bioinformatics and Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology , Wuhan, Hubei, PR China.
Leng HanDepartment of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston , Houston, TX, USA.
The University of Texas Health Science Center at Houston · USHuazhong University of Science and Technology · CNThe University of Texas MD Anderson Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transfer RNAs (tRNAs) play critical roles in human cancer. Currently, no database provides the expression landscape and clinical relevance of tRNAs across a variety of human cancers. Utilizing miRNA-seq data from The Cancer Genome Atlas, we quantified the relative expression of tRNA genes and merged them into the codon level and amino level across 31 cancer types. The expression of tRNAs is associated with clinical features of patient smoking history and overall survival, and disease stage, subtype, and grade. We further analysed codon frequency and amino acid frequency for each protein coding gene and linked alterations of tRNA expression with protein translational efficiency. We include these data resources in a user-friendly data portal, tRic (tRNA in cancer, https://hanlab.uth.edu/tRic/ or http://bioinfo.life.hust.edu.cn/tRic/), which can be of significant interest to the research community.

Indexed as

Gene Expression Regulation, NeoplasticSoftwareAmino AcidsCodonComputational BiologyDatabases, GeneticHumansMolecular Sequence AnnotationNeoplasmsProtein BiosynthesisRNA, TransferAmino AcidsCodonRNA, Transferamino acidcancercodoncodon usagetRNA

Identifiers

PMID31432762
PMCPMC7567503
OpenAlexW2969908920

What OpenQuestion holds

Textmetadata
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.