Evidence map›Paper›PMID 39821024›Full record

ReviewAdvances in experimental medicine and biology2025

Rat Models of Breast Cancer.

Wen Bu, Yi Li

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Rat somatic genome editing enables ER+ breast cancer modeling.bioRxiv : the preprint server for biology · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Wen BuLester & Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA.
Yi LiLester & Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA. liyi@bcm.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the first mammal to be domesticated for research purposes, rats served as the primary animal model for various branches of biomedical research, including breast cancer studies, up until the late 1990s and early 2000s. During this time, genetic engineering of mice, but not rats, became routine, and mice gradually supplanted rats as the preferred rodent model. But recent advances in creating genetically engineered rat models, especially with the assistance of CRISPR/Cas9 technology, have rekindled the significance of rats as a critical model in exploring various facets of breast cancer research. This is particularly pronounced in the study of the formation and progression of the estrogen receptor-positive subtype, which remains challenging to model in mice. In this chapter, we embark on a historical journey through the evolution of rat models in biomedical research and provide an overview of the general and histological characteristics of rat mammary glands. Next, we critically review major rat models for breast cancer research, including those induced by carcinogens, hormones, radiation, germline transgenes, germline knockouts, and intraductal injection of retrovirus/lentivirus to deliver oncogenic drivers into mature mammary glands. We also discuss the advances in building rat models using somatic genome editing powered by CRISPR/Cas9. This chapter concludes with our forward-looking perspective on future applications of advanced rat models in critical areas of breast cancer research that have continued to challenge the mouse model community.

Indexed as

Breast NeoplasmsDisease Models, AnimalMammary Neoplasms, ExperimentalAnimalsCRISPR-Cas SystemsFemaleHumansMammary Glands, AnimalMiceRatsCarcinogenIntraductal injectionKnockout modelMammary glandRatSomatic genome editingTransgenic modelViral vector

Identifiers

PMID39821024

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.