ReviewNature reviews. Cancer2025
Evolutionary paths towards metastasis.
Review in Nature reviews. Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Metabolites and cancer metastasis.Oncogene · 2026Review
- Before the seeds arrive: pre-metastatic niche orchestration in bladder cancer.Cancer metastasis reviews · 2026Review
- Orchestrating the metastatic symphony: the role of extracellular vesicles in the epithelial-mesenchymal transition and pulmonary niche formation of breast cancer.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Molecular insights and therapeutic implications for the tumor suppressor role of LKB1 in non-small cell lung cancer.Cancer letters · 2026Review
- [Evolution of metastases in non-small-cell lung cancer: preliminary results from the TRACERx-PEACE study].Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- A truncated TNS3 isoform expressed in metastatic triple negative breast cancer stabilizes FAK and promotes lung metastasis.Oncogene · 2026Article
- Plasticity of Non-Apoptotic Residual Tumor Cells After Neoadjuvant Immunochemotherapy: Epigenetic and Microenvironmental Determinants.Biomolecules · 2026Review
- Article
- Chromatin architecture and physical constriction cooperate in phenotype switching and cancer cell dissemination.bioRxiv : the preprint server for biology · 2026Article
- Genomic evolution of pancreatic cancer at single-cell resolution.Nature genetics · 2026Article
- A Model for the Diversity Explosion Fundamental to Metastasis.bioRxiv : the preprint server for biology · 2025Article
- Emerging role of long non‑coding RNAs in the Rho/ROCK signaling pathway in tumor metastasis (Review).International journal of molecular medicine · 2025Review
- Segregating DNA lesions point to high selective advantage of tumor initiating cells.bioRxiv : the preprint server for biology · 2025Article
- A novel nomogram for predicting mediastinal lymph node metastasis in non-small cell lung cancer: a retrospective analysis.Journal of thoracic disease · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
The evolution of metastasis in humans is considerably less well understood than the biology of early carcinogenesis. For over a century, clinicians and scientists have been debating whether metastatic potential is the intrinsic property of a cancer, pre-determined by the molecular characteristics of the tumour founder cell, or whether metastatic capacity evolves in a stepwise fashion as the tumour grows, akin to the multistage accumulation of oncogenic alterations that give rise to the first cancer cell. In this Perspective, I examine how genetic analyses of primary tumours and matched metastases can distinguish between these two competing metastasis evolution models, with particular emphasis on the utility of metastatic randomness - a quantitative measure that reflects whether metastases arise from a random selection of primary tumour subclones or whether they are enriched for descendants of privileged lineages that have acquired pro-metastatic traits. Probable metastasis evolution trajectories in tumours with high and low baseline metastatic capacity are discussed, along with the role of seeding rates and selection at different metastatic host sites. Finally, I argue that trailblazing insights into human metastasis biology are immediately possible if we make a concerted effort to apply existing experimental and theoretical tools to the right patient cohorts.
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Registered trials
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.