ReviewNature reviews. Cancer2016
Optimizing mouse models for precision cancer prevention.
Review in Nature reviews. Cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 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
48 citing papers in PubMed, 70 citations in OpenAlex.
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- Emerging strategies to investigate the biology of early cancer.Nature reviews. Cancer · 2024Review
- OBSERVE: guidelines for the refinement of rodent cancer models.Nature protocols · 2024Review
- Perineural invasion in colorectal cancer: mechanisms of action and clinical relevance.Cellular oncology (Dordrecht, Netherlands) · 2024Review
- NGF-mediated crosstalk: unraveling the influence of metabolic deregulation on the interplay between neural and pancreatic cancer cells and its impact on patient outcomes.Frontiers in pharmacology · 2024Review
- Esophageal adenocarcinoma models: a closer look.Frontiers in molecular biosciences · 2024Review
- Towards system genetics analysis of head and neck squamous cell carcinoma using the mouse model, cellular platform, and clinical human data.Animal models and experimental medicine · 2023Review
- Patient-derived tumor models: a suitable tool for preclinical studies on esophageal cancer.Cancer gene therapy · 2023Review
- Unraveling the Mysteries of Perineural Invasion in Benign and Malignant Conditions.Current oncology (Toronto, Ont.) · 2023Review
- Three-dimensional (3D) liver cell models - a tool for bridging the gap between animal studies and clinical trials when screening liver accumulation and toxicity of nanobiomaterials.Drug delivery and translational research · 2022Review
- Mouse Models to Study Secondary Cancer Prevention.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Systems genetics analysis of oral squamous cell carcinoma susceptibility using the mouse model: current position and new perspective.Mammalian genome : official journal of the International Mammalian Genome Society · 2021Review
- NKX3.1 Localization to Mitochondria Suppresses Prostate Cancer Initiation.Cancer discovery · 2021Article
- Porcine pancreatic ductal epithelial cells transformed with KRASScientific reports · 2021Article
- Precision and Immunoprevention Strategies for Tobacco-Related Head and Neck Cancer Chemoprevention.Current treatment options in oncology · 2021Review
- Intravital mesoscopic fluorescence molecular tomography allows non-invasive in vivo monitoring and quantification of breast cancer growth dynamics.Communications biology · 2021Article
- Basal and Luminal Molecular Subtypes in Naturally-Occurring Canine Urothelial Carcinoma are Associated with Tumor Immune Signatures and Dog Breed.Bladder cancer (Amsterdam, Netherlands) · 2021Article
- Lifestyle and Environmental Approaches for the Primary Prevention of Hepatocellular Carcinoma.Clinics in liver disease · 2020Review
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 at 2 institutions in 1 country.
Funding
Abstract
As cancer has become increasingly prevalent, cancer prevention research has evolved towards placing a greater emphasis on reducing cancer deaths and minimizing the adverse consequences of having cancer. 'Precision cancer prevention' takes into account the collaboration of intrinsic and extrinsic factors in influencing cancer incidence and aggressiveness in the context of the individual, as well as recognizing that such knowledge can improve early detection and enable more accurate discrimination of cancerous lesions. However, mouse models, and particularly genetically engineered mouse (GEM) models, have yet to be fully integrated into prevention research. In this Opinion article, we discuss opportunities and challenges for precision mouse modelling, including the essential criteria of mouse models for prevention research, representative success stories and opportunities for more refined analyses in future studies.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.