ReviewJournal of mammary gland biology and neoplasia2019
How to Choose a Mouse Model of Breast Cancer, a Genomic Perspective.
Review in Journal of mammary gland biology and neoplasia, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Murine Models of Obesity-Related Cancer Risk.Cancer prevention research (Philadelphia, Pa.) · 2025Review
- Hippo-TAZ signaling is the master regulator of the onset of triple-negative basal-like breast cancers.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Drug efficacy and toxicity prediction: an innovative application of transcriptomic data.Cell biology and toxicology · 2020Article
- Pathological and genetic aspects of spontaneous mammary gland tumor in Tupaia belangeri (tree shrew).PloS one · 2020Article
- ppGalNAc-T4-catalyzed O-Glycosylation of TGF-β type Ⅱ receptor regulates breast cancer cells metastasis potential.The Journal of biological chemistryArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Human breast cancer is a heterogeneous disease with numerous subtypes that have been defined through immunohistological, histological, and gene expression patterns. The diversity of breast cancer has made the study of its various underlying causes complex. To facilitate the examination of particular facets of breast cancer, mouse models have been generated, ranging from carcinogen induced models to genetically engineered mice. While mouse models have been generated to mimic the initiating event, including p53 loss, BRCA loss, or overexpression of HER2 / Neu / erbB2, other genomic events are often not well characterized. However, these secondary genetic events are often critical to the mouse tumor evolution, subtype, and outcome, just as they are in human breast cancer. As such, these other genomic events are a critical component of what models are chosen to study specific subtypes of human breast cancer. Here we review the genomic analyses that have been completed for various genetically engineered mouse models, how they compare to human breast cancer, and detail how this information can be used in choosing a mouse model for analysis.
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Identifiers
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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.