ReviewAnnual review of nutrition2021
Designing Relevant Preclinical Rodent Models for Studying Links Between Nutrition, Obesity, Metabolism, and Cancer.
Review in Annual review of nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Ketogenic Diet Prevents Obesity-Associated Pancreatic Cancer Independent of Weight Loss and Induces Pancreatic Metabolic Reprogramming.Cancer research · 2026Article
- Integrated Machine Learning and Multi-Omics Analysis Identifies Mitophagy-Related Core Genes and Mechanisms in Non-Alcoholic Fatty Liver Disease.Journal of inflammation research · 2026Article
- Obesity promotes conserved inflammatory and metabolic transcriptional programs in colon tumors: evidence from mouse models and the ColoCare Study Patient Cohort.The American journal of clinical nutrition · 2025Article
- Weight Loss Reverses the Effects of Aging and Obesity on Mammary Tumor Immunosuppression and Progression.Cancer prevention research (Philadelphia, Pa.) · 2025Article
- Ketogenic diet prevents obesity-associated pancreatic cancer independent of weight loss and induces pancreatic metabolic reprogramming.bioRxiv : the preprint server for biology · 2025Article
- Glutathione peroxidase 4 (GPX4) and obesity interact to impact tumor progression and treatment response in triple negative breast cancer.Cancer & metabolism · 2025Article
- A Standardized Method for Vertical Sleeve Gastrectomy Bariatric Surgery Investigations in Cancer.Frontiers in microbiomes · 2025Article
- Article
- Multifaceted effects of obesity on cancer immunotherapies: Bridging preclinical models and clinical data.Seminars in cancer biology · 2023Review
- Review
- Weight Loss and/or Sulindac Mitigate Obesity-associated Transcriptome, Microbiome, and Protumor Effects in a Murine Model of Colon Cancer.Cancer prevention research (Philadelphia, Pa.) · 2022Article
- Translating energy balance research from the bench to the clinic to the community: Parallel animal-human studies in cancer.CA: a cancer journal for cliniciansReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Diet and nutrition are intricately related to cancer prevention, growth, and treatment response. Preclinical rodent models are a cornerstone to biomedical research and remain instrumental in our understanding of the relationship between cancer and diet and in the development of effective therapeutics. However, the success rate of translating promising findings from the bench to the bedside is suboptimal. Well-designed rodent models will be crucial to improving the impact basic science has on clinical treatment options. This review discusses essential experimental factors to consider when designing a preclinical cancer model with an emphasis on incorporatingthese models into studies interrogating diet, nutrition, and metabolism. The aims of this review are to (
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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.