Evidence map›Paper›PMID 36808143›Full record

ArticleCommunications biology2023

Pan-cancer clinical impact of latent drivers from double mutations.

Bengi Ruken Yavuz, Chung-Jung Tsai, Ruth Nussinov, Nurcan Tuncbag

Abstract read
In one paragraph

Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–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

20 citing papers in PubMed.

  1. Review
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  5. The structural heterogeneity of AKT autoinhibition.Protein science : a publication of the Protein Society · 2026
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  9. Tumors and their microenvironments: Learning from pediatric brain pathologies.Biochimica et biophysica acta. Reviews on cancer · 2025
    Review
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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

4 authors.

Bengi Ruken YavuzGraduate School of Informatics, Department of Health Informatics, Middle East Technical University, Ankara, 06800, Turkey.
Chung-Jung TsaiComputational Structural Biology Section, Frederick National Laboratory for Cancer Research, National Cancer Institute at Frederick, Frederick, MD, 21702, USA.ORCID 0000-0003-1524-9928
Ruth NussinovComputational Structural Biology Section, Frederick National Laboratory for Cancer Research, National Cancer Institute at Frederick, Frederick, MD, 21702, USA.
Nurcan TuncbagDepartment of Chemical and Biological Engineering, College of Engineering, Koç University, Istanbul, 34450, Turkey. ntuncbag@ku.edu.tr.ORCID 0000-0002-0389-9459

Funding

NCI NIH HHS HHSN261201500003CNCI NIH HHS HHSN261201500003I
6 · The paper itself

Abstract

Here, we discover potential 'latent driver' mutations in cancer genomes. Latent drivers have low frequencies and minor observable translational potential. As such, to date they have escaped identification. Their discovery is important, since when paired in cis, latent driver mutations can drive cancer. Our comprehensive statistical analysis of the pan-cancer mutation profiles of ~60,000 tumor sequences from the TCGA and AACR-GENIE cohorts identifies significantly co-occurring potential latent drivers. We observe 155 same gene double mutations of which 140 individual components are cataloged as latent drivers. Evaluation of cell lines and patient-derived xenograft response data to drug treatment indicate that in certain genes double mutations may have a prominent role in increasing oncogenic activity, hence obtaining a better drug response, as in PIK3CA. Taken together, our comprehensive analyses indicate that same-gene double mutations are exceedingly rare phenomena but are a signature for some cancer types, e.g., breast, and lung cancers. The relative rarity of doublets can be explained by the likelihood of strong signals resulting in oncogene-induced senescence, and by doublets consisting of non-identical single residue components populating the background mutational load, thus not identified.

Indexed as

Lung NeoplasmsHumansMutationProteomics

Identifiers

PMID36808143
PMCPMC9941481

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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.