ReviewNature reviews. Genetics2025
Integrating model systems and genomic insights to decipher mechanisms of cancer metastasis.
Review in Nature reviews. Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Review
- Unraveling the molecular-pathological characteristics and cellular complexity of the tumor immune microenvironment in metastatic non-small cell lung cancer.Cell communication and signaling : CCS · 2025Review
- Bioactive Potential ofPlants (Basel, Switzerland) · 2025Article
- Orthotopically Implanted Murine Lung Adenocarcinoma Cell Lines for Preclinical Investigations.Cancers · 2025Review
- Bridging the Gap in Breast Cancer Dormancy: Models, Mechanisms, and Translational Challenges.Pharmaceuticals (Basel, Switzerland) · 2025Review
- The Establishment of 3D Polarity-Reversed Organoids From Human Endometrial Tissue as a Model for Infection-Induced Endometritis.Bio-protocol · 2025Article
- Inhibition of RPA32 and Cytotoxic Effects of the Carnivorous PlantPlants (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Deciphering metastatic processes is crucial for understanding cancer progression and potential treatment options. Genetic studies of model systems engineered to mimic metastatic disease, including organoids, genetically engineered mice and human cell lines, have had an important role in shaping our understanding of the metastatic cascade and how it can be manipulated. More recently, advances in high-throughput sequencing have enabled human metastases to be studied at single-cell and single-nucleotide resolution, providing insights into metastatic evolution and phenotypes of both cancer cells and immune cells. However, human tissue studies are often correlative and descriptive, whereas experimental models are reductionistic by nature, meaning that individual results should be interpreted with caution. Crucially, these seemingly disparate branches of metastasis research can and should complement each other to strengthen and validate findings. Here we explore the synergies between model systems and sequencing studies and outline key areas that must be explored to improve our understanding of the metastatic process.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.