Evidence map›Paper›PMID 26590405›Full record

ArticleNucleic acids research2016

TSGene 2.0: an updated literature-based knowledgebase for tumor suppressor genes.

Min Zhao, Pora Kim, Ramkrishna Mitra, Junfei Zhao, Zhongming Zhao

Abstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 263 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
263citing papers in PubMed, 2 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

263 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  15. DIOPT: the DRSC Integrative Ortholog Prediction Tool, 2026 update.bioRxiv : the preprint server for biology · 2026
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203 more citing papers are in PubMed but not listed here.

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

5 authors.

Min ZhaoSchool of Engineering, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Maroochydore DC, Queensland 4558, Australia.
Pora KimDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Ramkrishna MitraDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Junfei ZhaoDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Zhongming ZhaoDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, TN 37212, USA School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA zhongming.zhao@vanderbilt.edu.

Funding

Tumor Immunology and Microenvironment Research ProgramP30CA068485 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MATTHEW J TYSKA · 1995 to 2026
$172.8M
TISSUE CoreP50CA098131 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PARK, BEN HO, PIETENPOL, JENNIFER A · 2003 to 2024
$48.7M
Understanding and Controlling p120 Dysfunction in CRCP50CA095103 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI COFFEY, ROBERT J. · 2002 to 2017
$33.6M
Mapping the Genetic Architecture of Complex Disease via RNA-seq and GWAS DataR01LM011177 · NLM · VANDERBILT UNIVERSITY · PI WANG, LILY, ZHAO, ZHONGMING · 2012 to 2014
$1.0M
NCI NIH HHS P30CA068485NCI NIH HHS P50CA095103NCI NIH HHS P50CA098131NLM NIH HHS R01LM011177
6 · The paper itself

Abstract

Tumor suppressor genes (TSGs) are a major type of gatekeeper genes in the cell growth. A knowledgebase with the systematic collection and curation of TSGs in multiple cancer types is critically important for further studying their biological functions as well as for developing therapeutic strategies. Since its development in 2012, the Tumor Suppressor Gene database (TSGene), has become a popular resource in the cancer research community. Here, we reported the TSGene version 2.0, which has substantial updates of contents (e.g. up-to-date literature and pan-cancer genomic data collection and curation), data types (noncoding RNAs and protein-coding genes) and content accessibility. Specifically, the current TSGene 2.0 contains 1217 human TSGs (1018 protein-coding and 199 non-coding genes) curated from over 9000 articles. Additionally, TSGene 2.0 provides thousands of expression and mutation patterns derived from pan-cancer data of The Cancer Genome Atlas. A new web interface is available at http://bioinfo.mc.vanderbilt.edu/TSGene/. Systematic analyses of 199 non-coding TSGs provide numerous cancer-specific non-coding mutational events for further screening and clinical use. Intriguingly, we identified 49 protein-coding TSGs that were consistently down-regulated in 11 cancer types. In summary, TSGene 2.0, which is the only available database for TSGs, provides the most updated TSGs and their features in pan-cancer.

Indexed as

Databases, Nucleic AcidGenes, Tumor SuppressorDown-RegulationGene Expression Regulation, NeoplasticHumansKnowledge BasesMicroRNAsMolecular Sequence AnnotationMutationNeoplasmsPubMedRNA, Long NoncodingTumor Suppressor ProteinsMicroRNAsRNA, Long NoncodingTumor Suppressor Proteins

Identifiers

PMID26590405
PMCPMC4702895

What OpenQuestion holds

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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.