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Updated: Jul 15, 2026
Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
Published on: May 18, 2020
Accelerated preclinical testing using transplanted tumors from genetically engineered mouse breast cancer models
Lyuba Varticovski1, Melinda G Hollingshead, Ana I Robles
1Center for Cancer Research, National Cancer Institute, Frederick, Maryland. varticol@mail.nih.gov
Purpose:
The use of genetically engineered mouse (GEM) models for preclinical testing of anticancer therapies is hampered by variable tumor latency, incomplete penetrance, and complicated breeding schemes. Here, we describe and validate a transplantation strategy that circumvents some of these difficulties.
Experimental Design:
Tumor fragments from tumor-bearing MMTV-PyMT or cell suspensions from MMTV-PyMT, -Her2/neu, -wnt1, -wnt1/p53(+/-), BRCA1/p53(+/-), and C3(1)T-Ag mice were transplanted into the mammary fat pad or s.c. into naïve syngeneic or immunosuppressed mice. Tumor development was monitored and tissues were processed for histopathology and gene expression profiling. Metastasis was scored 60 days after the removal of transplanted tumors.
Results:
PyMT tumor fragments and cell suspensions from anterior glands grew faster than posterior tumors in serial passages regardless of the site of implantation. Microarray analysis revealed genetic differences between these tumors. The transplantation was reproducible using anterior tumors from multiple GEM, and tumor growth rate correlated with the number of transplanted cells. Similar morphologic appearances were observed in original and transplanted tumors. Metastasis developed in >90% of mice transplanted with PyMT, 40% with BRCA1/p53(+/-) and wnt1/p53(+/-), and 15% with Her2/neu tumors. Expansion of PyMT and wnt1 tumors by serial transplantation for two passages did not lead to significant changes in gene expression. PyMT-transplanted tumors and anterior tumors of transgenic mice showed similar sensitivities to cyclophosphamide and paclitaxel.
Conclusions:
Transplantation of GEM tumors can provide a large cohort of mice bearing mammary tumors at the same stage of tumor development and with defined frequency of metastasis in a well-characterized molecular and genetic background.
Insights
Transplanting tumors from genetically engineered mouse models (GEMs) offers a reproducible method for preclinical cancer therapy testing. This approach overcomes challenges like variable tumor growth and allows for consistent metastasis studies.
Area of Science:
- Oncology
- Genetics
- Preclinical Research
Background:
- Genetically engineered mouse (GEM) models are crucial for preclinical cancer therapy testing.
- However, challenges such as variable tumor latency, incomplete penetrance, and complex breeding hinder their utility.
- A novel transplantation strategy is needed to improve the reliability of these models.
Purpose of the Study:
- To describe and validate a tumor transplantation strategy for genetically engineered mouse models.
- To overcome limitations of traditional GEM models in preclinical cancer therapy research.
- To establish a reproducible method for generating mammary tumors in mice for drug testing.
Main Methods:
- Tumor fragments or cell suspensions from various GEMs (e.g., MMTV-PyMT, Her2/neu, wnt1) were transplanted into syngeneic or immunosuppressed mice.
- Tumor development, histopathology, gene expression, and metastasis were monitored.
- Serial passages and drug sensitivity assays were performed.
Main Results:
- Transplanted anterior tumors grew faster than posterior tumors, with growth rate correlating to cell number.
- The transplantation method was reproducible across multiple GEMs.
- High metastasis rates were observed in PyMT, BRCA1/p53(+/-), and wnt1/p53(+/-) models (>90%, 40%, 40% respectively).
- Transplanted PyMT tumors showed similar gene expression and drug sensitivity to original tumors.
Conclusions:
- Tumor transplantation in GEMs provides a consistent cohort of mice with synchronized tumor development.
- This method facilitates well-defined metastasis studies within a characterized genetic background.
- The strategy enhances the reliability of preclinical anticancer therapy testing using GEM models.
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