Evidence map›Paper›PMID 35013316›Full record

ArticleNature communications2022

Association of mutation signature effectuating processes with mutation hotspots in driver genes and non-coding regions.

John K L Wong, Christian Aichmüller, Markus Schulze, Mario Hlevnjak, Shaymaa Elgaafary, Peter Lichter, Marc Zapatka

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. 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
2.6field-weighted citation impact, top 9% 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, 29 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Mutational signatures in hematological malignancies.Einstein (Sao Paulo, Brazil) · 2026
    Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Cancer driver mutations: predictions and reality.Trends in molecular medicine · 2023
    Review
  14. Article
  15. Review
  16. 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

7 authors at 2 institutions in 1 country.

John K L WongDivision of Molecular Genetics and German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany. j.wong@dkfz-heidelberg.de.ORCID 0000-0001-6362-373X
Christian AichmüllerDivision of Molecular Genetics and German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Markus SchulzeComputational Oncology Group, Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) and DKFZ, Heidelberg, Germany.
Mario HlevnjakComputational Oncology Group, Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) and DKFZ, Heidelberg, Germany.
Shaymaa ElgaafaryGynecologic Oncology, National Center for Tumor Diseases (NCT) and University of Heidelberg, Heidelberg, Germany.ORCID 0000-0002-2846-6000
Peter LichterDivision of Molecular Genetics and German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Marc ZapatkaDivision of Molecular Genetics and German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany. m.zapatka@dkfz-heidelberg.de.ORCID 0000-0001-8287-5967
German Cancer Research Center · DEHeidelberg University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer driving mutations are difficult to identify especially in the non-coding part of the genome. Here, we present sigDriver, an algorithm dedicated to call driver mutations. Using 3813 whole-genome sequenced tumors from International Cancer Genome Consortium, The Cancer Genome Atlas Program, and a childhood pan-cancer cohort, we employ mutational signatures based on single-base substitution in the context of tri- and penta-nucleotide motifs for hotspot discovery. Knowledge-based annotations on mutational hotspots reveal enrichment in coding regions and regulatory elements for 6 mutational signatures, including APOBEC and somatic hypermutation signatures. APOBEC activity is associated with 32 hotspots of which 11 are known and 11 are putative regulatory drivers. Somatic single nucleotide variants clusters detected at hypermutation-associated hotspots are distinct from translocation or gene amplifications. Patients carrying APOBEC induced PIK3CA driver mutations show lower occurrence of signature SBS39. In summary, sigDriver uncovers mutational processes associated with known and putative tumor drivers and hotspots particularly in the non-coding regions of the genome.

Indexed as

Gene Drive TechnologyAPOBEC DeaminasesAtlases as TopicChildClass I Phosphatidylinositol 3-KinasesDatabases, GeneticDNA, IntergenicGene Expression Regulation, NeoplasticGenome, HumanHumansMutagenesisMutation RateNeoplasm ProteinsNeoplasmsNucleotide MotifsOpen Reading FramesAPOBEC DeaminasesClass I Phosphatidylinositol 3-KinasesDNA, IntergenicNeoplasm ProteinsPIK3CA protein, human

Identifiers

PMID35013316
PMCPMC8748499
OpenAlexW4206548225

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.