Due to obvious ethical considerations, cancer research conducted in humans is restricted to observational and analytical studies, with therapy focused clinical trials being the one exception to this rule. Preclinical mouse tumour models therefore provide a critical intermediate experimental model system tying together more basic in vitro research with studies in humans, thereby providing bench-to-bedside translational oncology research.
How to choose your mouse models
The first question to be asked is ‘which in vivo model should be used’ as it’s important to take this into consideration - different models serve different purposes. One invaluable oncology model is Patient Derived Xenografts (PDX), whereby tissue or cells from a patient’s tumor are implanted into an immunodeficient mouse. They are currently the only model system that can directly incorporate the vast inter-patient and intra-tumour heterogeneity that is inherent to human cancer (Gengenbacher, et al, 2017). Pioneering PDX studies from the mid-1980s have shown evidence that PDXs can accurately and reproducibly predict cancer therapy responses using clinically approved drugs.
Things to consider with PDX
The first limitation is that engraftment rates are not only reliant on both the recipient mouse strain and original patient sample quality, but can also strongly vary between different tumour types and grades, therefore disparities in engraftment can limit the genetic complexity portrayed by PDXs (Eirew et al., 2015). PDX’s engraftment rate can be used as a predictive biomarker, as patients from whom PDXs can be readily established show the worst prognosis, as shown for various types of cancers including breast cancer (Eyre et al., 2016). Another limitation is that initially present human stroma following engraftment is over time replaced by mouse stoma constituents following in vivo passaging.
Analysis of Breast Tumor Xenografts
Proteomic analysis of breast tumor xenografts have revealed differences in the benefits of using either Bottom-Up proteomics or Top-Down proteomics techniques (Ntai et al., 2016). Bottom-Up proteomics employs proteases to identify thousands of protein groups in complex samples while Top-Down proteomics is ideally suited to direct analysis of small proteins. Ntai et al., ingeniously for the first time, combined both types of analysis techniques to provide complementary data reporting back on human xenograft proteoforms. Improved analysis techniques of PDXs will ultimately only hasten cancer treatment breakthroughs.
Putting Xenografts into translational practice
Breast cancer treatment where there’s endocrine therapy resistance, observed for example in individuals with estrogen receptor (ESR1) mutations, provide a particular challenge in treatment development. This is where PDX models (Wardell et al., 2015), have been deployed to evaluate the efficacy of different combinations of compounds in targeting cancerous cells. In particular, new classes of drugs such as a selective estrogen receptor downregulator (SERD) were evaluated along with selective estrogen receptor modulators (SERM) that were shown to downregulate ESR1 in ESR1-mutant PDX models of endocrine-resistant breast tumors. This particular research and other related research all show much hope for the future in the fight against breast cancer.