ArticlePLoS computational biology2024
Synergistic epistasis among cancer drivers can rescue early tumors from the accumulation of deleterious passengers.
Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Evolutionary dynamics under phenotypic uncertainty.bioRxiv : the preprint server for biology · 2026Article
- The role of environmental stress in promoting mutators through evolutionary rescue: quantitative predictions.Genetics · 2025Article
- Sequential anlotinib and camrelizumab combination therapy achieves exceptional survival in multi-driver mutated, TMB-low/PD-L1-low/MSS pulmonary sarcomatoid carcinoma: case report and literature review.Frontiers in immunology · 2025Review
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Authors and funding
3 authors.
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Abstract
Epistasis among driver mutations is pervasive and explains relevant features of cancer, such as differential therapy response and convergence towards well-characterized molecular subtypes. Furthermore, a growing body of evidence suggests that tumor development could be hampered by the accumulation of slightly deleterious passenger mutations. In this work, we combined empirical epistasis networks, computer simulations, and mathematical models to explore how synergistic interactions among driver mutations affect cancer progression under the burden of slightly deleterious passengers. We found that epistasis plays a crucial role in tumor development by promoting the transformation of precancerous clones into rapidly growing tumors through a process that is analogous to evolutionary rescue. The triggering of epistasis-driven rescue is strongly dependent on the intensity of epistasis and could be a key rate-limiting step in many tumors, contributing to their unpredictability. As a result, central genes in cancer epistasis networks appear as key intervention targets for cancer therapy.
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