The MMTV-PyMT transgenic mouse model, developed over 30 years ago [1], remains an invaluable tool for studying breast cancer progression—from tumor initiation to distant metastasis [2]. Despite its widespread use, criticisms persist, particularly regarding its relevance to human cancer. After all, neither the mouse mammary tumor virus (MMTV) promoter nor the oncogene polyomavirus middle T antigen (PyMT) is present in human malignancies. However, as the British statistician George Box famously said, "All models are wrong, but some are useful." And indeed, MMTV-PyMT has proven indispensable in our recent study published in NPJ Breast Cancer [3].

The C57BL Background Advantage

I first encountered MMTV-PyMT as a graduate student at the Lester and Sue Smith Breast Center, Baylor College of Medicine. At the time, I was using breast cancer cell lines to investigate the tumor microenvironment, with a particular focus on pericytes—mural cells that envelop blood vessels [4]. Since my pericyte-labeling model was in the C57BL/6 background, I had only two breast cancer models to choose from: E0771 (a spontaneous murine breast cancer cell line) and AT3 (derived from an MMTV-PyMT tumor in C57BL/6 mice).

Unlike other MMTV-driven models (e.g., MMTV-Neu or MMTV-Wnt), MMTV-PyMT is unique in its ability to form orthotopic tumors and spontaneous metastases in the C57BL/6 background. This is a major advantage, as it allows for seamless crossbreeding with the vast array of existing C57BL/6 transgenic tools.

"Everything Should Be Made as Simple as Possible, But No Simpler"

Another key strength of MMTV-PyMT is its reliance on a single oncogene. This stands in stark contrast to genetically engineered models of lung, pancreatic, or colorectal cancer, which often require multiple transgenes—including tissue-specific Cre recombinase, Cre-dependent oncogene activation, and tumor suppressor deletion. The simplicity of MMTV-PyMT makes it highly compatible with sophisticated lineage-tracing tools, such as the proliferation tracing and ablation system used in this study.

By combining MMTV-PyMT with proliferation-dependent cell ablation, we developed a powerful system to eliminate fast-proliferating cells and model gradual tumor relapse. Notably, most existing relapse models rely on oncogene addiction—where oncogene withdrawal leads to dramatic tumor shrinkage, followed by a dormant phase and eventual relapse. In contrast, our MMTV-PyMT;ProTracer/Deleter model exhibited distinct kinetics, with no apparent dormancy period. This suggests that relapsed tumors in our system do not need to acquire new traits to overcome oncogene deprivation.

Another intriguing finding was that relapsed tumors were not mere replicas of the primary tumor. Instead, recurrent lesions were enriched for cancer cells with stem-like properties and resided in a more immunosuppressive microenvironment. Through cell-cell communication analysis, we identified a positive feedback loop driving neutrophil recruitment as a likely contributor to this immunosuppression.

Acknowledging the First Author and the Team

This work would not have been possible without the exceptional collaboration of our team, particularly first author Chuang Zhao, a second-year graduate student. Chuang’s journey in the lab is a testament to adaptability and curiosity. Initially planning to focus on wet-lab work, he quickly became captivated by bioinformatics. After completing his first-year coursework, he requested a two-month leave to attend specialized training in single-cell RNA sequencing analysis.

Though I was hesitant at first, I ultimately granted Chuang his "two-month sabbatical"—a decision that proved to be a wise investment. Today, Chuang is not only proficient in wet-lab techniques (PCR, cell culture, genotyping, etc.), but he has also become an expert in bioinformatics, applying his skills to multiple projects in the lab.

Reference

[1] Induction of mammary tumors by expression of polyomavirus middle T oncogene: a transgenic mouse model for metastatic disease, CT Guy , RD Cardiff, WJ Muller, Mol Cell Biol. 1992, 12(3):954-61. PMID: 1312220

[2] Insights from transgenic mouse models of PyMT-induced breast cancer: recapitulating human breast cancer progression in vivo, S Attalla, T Taifour, T Bui, W Muller, Oncogene. 2021, 40(3):475-491, PMID: 33235291

[3] Modeling tumor relapse using proliferation tracing and ablation transgenic mouse, C Zhao , XN Zheng, HY Huang, L Tian, NPJ Breast Cancer. 2025, 11:73, PMID: 40675988

[4] Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming, L Tian, A Goldstein, H Wang, HC Lo, IS Kim, T Welte, KW Sheng, LE Dobrolecki, XM Zhang, N Putluri, TL Phung, SA Mani, F Stossi, A Sreekumar, MA Mancini, WK Decker, CH Zong, MT Lewis, XH-F Zhang, Nature: 544(7649):250-254, PMID: 28371798