Evidence map›Paper›PMID 30945018›Full record

ArticleMolecular genetics and genomics : MGG2019

Disease association of human tumor suppressor genes.

Asim Bikas Das

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular genetics and genomics : MGG, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. 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

1 author.

Asim Bikas DasDepartment of Biotechnology, National Institute of Technology Warangal, Warangal, Telangana, 506004, India. asimbikas@nitw.ac.in.ORCID http://orcid.org/0000-0003-1801-7487

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The multifactorial disease, cancer, frequently emerges due to perturbations in tumor suppressor genes (TSGs). However, a growing number of noncanonical target genes of TSGs and the highly interconnected nature of the human interactome reveal that the functions of TSGs are not limited to cancer-specific events. The various functions of TSGs lead to the assumption that cancer is linked with other human disorders. Therefore, a disease-gene association network of TSGs (TSDN) was constructed by integrating protein-protein interaction networks of TSGs (TSN) with Morbid Map in Online Mendelian Inheritance in Man. The TSDN revealed links between TSGs and 22 different human disorders including cancer and indicated disease-disease associations. In addition, high-density functional protein clusters in the TSN showed cohesive and overlapping disease-TSG associations, which proved the prevalent role of TSGs in various human diseases beyond cancer. The presence of overlapping disease-gene modules and disease-disease associations via the TSN demonstrated that other diseases can serve as possible roots of the life-threatening disease cancer. Therefore, a disease association map of TSGs could be a promising tool for exploring intricate relationships between cancer and other diseases for the early prediction of cancer and the understanding of disease etiology.

Indexed as

Gene OntologyGene Regulatory NetworksGenetic Association StudiesGenetic Predisposition to DiseaseHumansNeoplasmsProtein Interaction MapsTumor Suppressor ProteinsTumor Suppressor ProteinsCancerDisease–gene associationProtein–protein interaction networkTumor suppressor gene

Identifiers

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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.