Evidence map›Paper›PMID 32084333›Full record

ArticleCell2020

Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences.

Sushant Kumar, Jonathan Warrell, Shantao Li, Patrick D McGillivray, William Meyerson, Leonidas Salichos, Arif Harmanci, Alexander Martinez-Fundichely, Calvin W Y Chan, Morten Muhlig Nielsen and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers.

0numbers the graph read from it
0cells of the map it votes in
105citing 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

105 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. COSMIC-Linked Ras Mutations at the Interface Between H-Ras and PI3KγbioRxiv : the preprint server for biology · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Integrating evidence from protein domains to identify cancer driver mutations.Protein science : a publication of the Protein Society · 2026
    Article
  13. The functional imperative in high-grade glioma.Experimental & molecular medicine · 2026
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review

45 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

19 authors.

Sushant KumarProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.
Jonathan WarrellProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.
Shantao LiProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.
Patrick D McGillivrayDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Yale School of Medicine, Yale University, New Haven, CT 06510, USA.
William MeyersonProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Yale School of Medicine, Yale University, New Haven, CT 06510, USA.
Leonidas SalichosProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.
Arif HarmanciProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Center for Precision Health, School of Biomedical Informatics, University of Texas Health Sciences Center, Houston, TX 77030, USA.
Alexander Martinez-FundichelyInstitute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA.
Calvin W Y ChanDivision of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Faculty of Biosciences, Heidelberg University, Heidelberg 69120, Germany.
Morten Muhlig NielsenDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark.
Lucas LochovskyProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.
Yan ZhangProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210, USA; The Ohio State University Comprehensive Cancer Center (OSUCCC-James), Columbus, OH 43210, USA.
Xiaotong LiProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
Shaoke LouProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.
Jakob Skou PedersenDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark; Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark.
Carl HerrmannDivision of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Health Data Science Unit, Medical Faculty Heidelberg and BioQuant, Heidelberg 69120, Germany.
Gad GetzThe Broad Institute of MIT and Harvard, Cambridge, MA 02124, USA; Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02129, USA; Harvard Medical School, 250 Longwood Avenue, Boston, MA 02115, USA.
Ekta KhuranaInstitute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, 1300 York Avenue, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA; Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
Mark B GersteinProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Department of Computer Science, Yale University, New Haven, CT 06511, USA. Electronic address: mark@gersteinlab.org.

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007205 · NIGMS · YALE UNIVERSITY · PI KAZMIERCZAK, BARBARA I · 1985 to 2019
$42.9M
Predicting the functional impact of non-coding mutations using patient-specific gene regulatory networksR01CA218668 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI EKTA KHURANA, Neville Sanjana · 2018 to 2026
$4.7M
Prioritizing rare variants associated with cancer using non-coding annotationR01HG008126 · NHGRI · YALE UNIVERSITY · PI GERSTEIN, MARK BENDER · 2016 to 2018
$2.4M
NCI NIH HHS R01 CA218668NHGRI NIH HHS R01 HG008126NIGMS NIH HHS T32 GM007205
6 · The paper itself

Abstract

The dichotomous model of "drivers" and "passengers" in cancer posits that only a few mutations in a tumor strongly affect its progression, with the remaining ones being inconsequential. Here, we leveraged the comprehensive variant dataset from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project to demonstrate that-in addition to the dichotomy of high- and low-impact variants-there is a third group of medium-impact putative passengers. Moreover, we also found that molecular impact correlates with subclonal architecture (i.e., early versus late mutations), and different signatures encode for mutations with divergent impact. Furthermore, we adapted an additive-effects model from complex-trait studies to show that the aggregated effect of putative passengers, including undetected weak drivers, provides significant additional power (∼12% additive variance) for predicting cancerous phenotypes, beyond PCAWG-identified driver mutations. Finally, this framework allowed us to estimate the frequency of potential weak-driver mutations in PCAWG samples lacking any well-characterized driver alterations.

Indexed as

Disease ProgressionDNA Mutational AnalysisGenome, HumanGenomicsHumansMutationNeoplasmsWhole Genome Sequencingadditive-efectscancer genomicsdeleterious passengersdriver mutationsmolecular impactpassenger mutationsPCAWGweak drivers

Identifiers

PMID32084333
PMCPMC7210002

What OpenQuestion holds

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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.