The paucity of well validated preclinical models is frequently cited as a contributing factor to the high attrition rates seen in clinical oncological trials. There remains a critical need to develop models which are accurately able to recapitulate the features of human disease. The aims of this study were to use genetically engineered mouse models (GEMMs) to explore the efficacy of novel treatment strategies in HER2 positive breast cancer and to further develop the model to facilitate the study of mechanisms underpinning drug resistance. Using the BLG--HER2KI-PTEN+/- model, we demonstrated that Src plays an important role in the early stages of tumour development. Chemopreventative treatment with dasatinib delayed tumour inititation (p= 0.046, Wilcoxon signed rank test) and prolonged overall survival (OS) (p=0.06, Wilcoxon signed rank test). Dasatinib treatment also induced squamous metaplasia in 66% of drug treated tumours. We used 2 cell lines derived from this model to further explore dasatinib’s mechanism of action and demonstrated reduced proliferation, migration and invasion following in vitro treatment. Due to the prolonged tumour latency and the low metastatic rate seen in this model, further studies were undertaken with the MMTV-NIC model. This model also allowed us to study the impact of PTEN loss on therapeutic response. We validated this model by treating a cohort of MMTV-NIC PTEN+/- mice with paclitaxel and demonstrated prolonged OS (p=0.035, Gehan Breslow Wilcoxon test). AZD8931 is an equipotent signalling inhibitor of HER2, HER3 and EGFR. We observed heterogeneity in tumour response but overall AZD8931 treatment prolonged OS in both MMTV-NIC PTEN FL/+ and MMTV-NIC PTEN+/- models. PTEN loss was associated with reduced sensitivity to AZD8931 and failure to suppress Src activity, suggesting these may be suitable predictive biomarkers of AZD8931 response. To facilitate further studies exploring resistance, we transplanted MMTV-NIC PTEN+/- fragments into syngeneic mice and generated 3 tumours with acquired resistance to AZD8931. These tumours displayed differing resistance strategies; 1 tumour continued to express HER2 whilst the remaining 2 underwent EMT and lost HER2 expression reflecting to a very limited degree some of the heterogeneity of resistance strategies seen in human disease. To further explore resistance to HER2 targeting tyrosine kinase inhibitors, we generated a panel of human cell lines with acquired resistance to AZD8931 and lapatinib. Western blotting demonstrated loss of HER2, HER3 and PTEN in all resistant lines. Acquisition of resistance was associated with a marked change in phenotype and western blotting confirmed all lines had undergone EMT. We used a combination of RPPA and mass spectrometry to further characterise the AZD8931 resistant lines and identified multiple potential novel proteins involved in the resistant phenotype, including several implicated in EMT. In conclusion, when coupled with appropriate in vitro techniques, the MMTV-NIC model is a valuable tool for selection of emerging drugs to carry forward into clinical trials of HER2 positive breast cancer.

The incidence of breast cancer became the most common female cancer, and the fourth cause of female cancer death. In this study, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/MS) have been combined with multivariate statistics to investigate breast cancer tissues and cell lines. Core needle biopsy and fine needle aspiration (FNA) are techniques largely applied in the diagnosis of breast cancer. In this study, we have established an efficient protocol for detecting breast tissue and FNA samples with MALDI-TOF/MS. With the help of statistical analysis software, we can find the lipid-derived ion signals which can be use to distinguish breast cancer tumor tissues from non-tumor parts. This strategy can differentiate normal and tumor tissue, which is potential to apply in clinical diagnoses. The analysis of breast cancer tissue is challenging as the complexity of the tissue sample. Direct tissue analyses by matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) allows us to investigate the molecular structure and their distribution while maintaining the integrity of the tissue and avoiding the loss of signals from extraction steps. Combined MALDI-IMS with statistic software, tissues can be analyzed and classified based on their molecular content which is helpful to distinguish tumor regions from non-tumor regions of breast cancer tissue. Our result shows the differences in the distribution and content of lipids between tumor and non-tumor tissue which can be supplements of current pathological analysis in tumor margins. In this study, MALDI-TOF/MS combined with multivariate statistics were used to rapidly differentiate breast cancer cell lines with different estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) status. The protocol for efficiently detecting peptides and proteins in breast cancer cells with MALDI-TOF/MS was established, two multivariate statistics including principle component analysis (PCA) and hierarchical clustering analysis were used to process the obtaining MALDI mass spectra of six different breast cancer cell lines and one normal breast cell lines. Based on the difference of the peptide and protein profiles, breast cancer cell lines with same ER and HER-2 status were grouped in nearby region on the PCA score plot. The results of hierarchical cluster analysis also revealed high conformity between breast cancer cell protein profiles and respective hormone receptor types.

In breast cancer therapeutic decisions are based on the expression of estrogen (ER), progesterone (PR), the human epidermal growth factor 2 (HER2) receptors and the proliferation marker Ki67. However, only little is known concerning heterogeneity between the primary tumor and axillary lymph node metastases (LNM) in the primary site. We retrospectively analyzed receptor profiles of 215 early breast cancer patients with axillary synchronous LNM. Of our cohort, 69% were therapy naive and did not receive neoadjuvant treatment. Using immunohistochemistry, receptor status and Ki67 were compared between core needle biopsy of the tumor (t-CNB) and axillary LNM obtained during surgery. The discordance rates between t-CNB and axillary LNM were 12% for HER2, 6% for ER and 20% for PR. Receptor discordance appears to already occur at the primary site. Receptor losses might play a role concerning overtreatment concomitant with adverse drug effects, while receptor gains might be an option for additional targeted or endocrine therapy. Hence, not only receptor profiles of the tumor tissue but also of the synchronous axillary LNM should be considered in the choice of treatment.