ArticleNature communications2026
The cumulative impact of passenger mutations on cancer development.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- The cumulative impact of passenger mutations on cancer development.Nature communications · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The traditional binary classification of somatic mutations in cancer as either drivers or passengers overlooks the potential cumulative impact of smaller-effect mutations. Here, we analyze more than 11,000 whole-genome-sequenced primary tumors across 3 cancer cohorts to assess the functional contribution of passenger mutations in cancer development. We find that in the absence of canonical driver mutations, passenger mutations in cancer genes are significantly enriched, exhibit higher predicted pathogenicity, and are associated with aberrant expression, splicing disruption, altered transcription factor binding, and clinical outcomes that resemble those in the presence of driver mutations. The accumulation of passenger mutations in tumor suppressor genes correlates with significantly reduced expression and poorer prognosis, suggesting that progressive mutational burden may contribute to gradual impairment of tumor suppressor function, mirroring the functional outcomes of driver mutations. Together, these results support a continuum model of mutational impact, where the collective influence of passenger mutations contributes to oncogenesis and clinical outcomes. This work advocates for integrative cancer models that incorporate all somatic mutations to more accurately reflect the complexity of tumor evolution.
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