Evidence map›Paper›PMID 35885888›Full record

ArticleGenes2022

Use of Publication Dynamics to Distinguish Cancer Genes and Bystander Genes.

László Bányai, Mária Trexler, László Patthy

Open access · goldAbstract read
In one paragraph

Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 55% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  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

3 authors at 1 institution in 1 country.

László BányaiInstitute of Enzymology, Research Centre for Natural Sciences, Eötvös Loránd Research Network (ELKH), 1117 Budapest, Hungary.
Mária TrexlerInstitute of Enzymology, Research Centre for Natural Sciences, Eötvös Loránd Research Network (ELKH), 1117 Budapest, Hungary.
László PatthyInstitute of Enzymology, Research Centre for Natural Sciences, Eötvös Loránd Research Network (ELKH), 1117 Budapest, Hungary.ORCID 0000-0003-1329-0484
Institute of Molecular Life Sciences · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

de Magalhães has shown recently that most human genes have several papers in PubMed mentioning cancer, leading the author to suggest that every gene is associated with cancer, a conclusion that contradicts the widely held view that cancer is driven by a limited number of cancer genes, whereas the majority of genes are just bystanders in carcinogenesis. We have analyzed PubMed to decide whether publication metrics supports the distinction of bystander genes and cancer genes. The dynamics of publications on known cancer genes followed a similar pattern: seminal discoveries triggered a burst of cancer-related publications that validated and expanded the discovery, resulting in a rise both in the number and proportion of cancer-related publications on that gene. The dynamics of publications on bystander genes was markedly different. Although there is a slow but continuous time-dependent rise in the proportion of papers mentioning cancer, this phenomenon just reflects the increasing publication bias that favors cancer research. Despite this bias, the proportion of cancer papers on bystander genes remains low. Here, we show that the distinctive publication dynamics of cancer genes and bystander genes may be used for the identification of cancer genes.

Indexed as

Genes, NeoplasmNeoplasmsHumansPubMedbystander genecancer geneconfirmation biasfunding biaspassenger genepublication biastumor essential gene

Identifiers

PMID35885888
PMCPMC9315931
OpenAlexW4283274270

What OpenQuestion holds

Textmetadata
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.