Jeffery E. Green

Molecular Profiling of Angiogenesis Markers

The goal of this study was to develop a sensitive, simple, and widely applicable assay to measure copy numbers of specific mRNAs using real-time quantitative reverse transcriptase-polymerase chain reaction (RT-PCR), and identify a profile of gene expression closely associated with angiogenesis. We measured a panel of nine potential angiogenesis markers from a mouse transgenic model of prostate adenocarcinoma (TRAMP) and a mouse skin model of vascular endothelial growth factor (VEGF)-driven angiogenesis. In both models, expression of VEGF correlated with expression of mRNAs encoding other angiogenic cytokines (angiopoietin-1 and angiopoietin-2), endothelial cell receptor tyrosine kinases (Flt-1, KDR, Tie-1), and endothelial cell adhesion molecules (VE-cadherin, PECAM-1). Relative to control, in dermis highly stimulated by VEGF, the Ang-2 mRNA transcript numbers increased 35-fold, PECAM-1 and VE-cadherin increased 10-fold, Tie-1 increased 8-fold, KDR and Flt-1 each increased 4-fold, and Ang-1 increased 2-fold. All transcript numbers were correspondingly reduced in skin with less VEGF expression, indicating a relationship of each of these seven markers with VEGF. Thus, this study identifies a highly efficient method for precise quantification of a panel of seven specific mRNAs that correlate with VEGF expression and VEGF-induced neovascularization, and it provides evidence that real-time quantitative RT-PCR offers a highly sensitive strategy for monitoring angiogenesis.

BMI1 Cooperates with H-RAS to Induce an Aggressive Breast Cancer Phenotype with Brain Metastases

B-lymphoma Moloney murine leukaemia virus insertion region-1 (BMI1) is a member of the polycomb group of transcription repressors, which functions in stem cell maintenance and oncogenesis through the inhibition of the INK4A/ARF tumour suppressor locus. Overexpression of BMI1 is associated with poor prognosis in several human cancers, including breast cancer. We have previously shown that BMI1 collaborates with H-RAS to induce transformation of MCF10A human mammary epithelial cells through dysregulation of multiple growth pathways independent of the INK4A/ARF locus. In this study, we show that BMI1 collaborates with H-RAS to promote increased proliferation, invasion and resistance to apoptosis in vitro, and an increased rate of spontaneous metastases from mammary fat pad xenografts including novel metastases to the brain. Furthermore, in collaboration with H-RAS, BMI1 induced fulminant metastatic disease in the lung using a tail vein model of haematogenous spread through accelerated cellular proliferation and inhibition of apoptosis. Finally, we show that knockdown of BMI1 in several established breast cancer cell lines leads to decreased oncogenic behaviour in vitro and in vivo. In summary, BMI1 collaborates with H-RAS to induce an aggressive and metastatic phenotype with the unusual occurrence of brain metastasis, making it an important target for diagnosis and treatment of aggressive breast cancer.

Pre-Clinical Applications of Transgenic Mouse Mammary Cancer Models

Breast cancer is a leading cause of cancer morbidity and mortality. Given that the majority of human breast cancers appear to be due to non-genetic factors, identifying agents and mechanisms of prevention is key to lowering the incidence of cancer. Genetically engineered mouse models of mammary cancer have been important in elucidating molecular pathways and signaling events associated with the initiation, promotion, and the progression of cancer. Since several transgenic mammary models of human breast cancer progress through well-defined cancer stages, they are useful pre-clinical systems to test the efficacy of chemopreventive and chemotherapeutic agents. This review outlines several oncogenic pathways through which mammary cancer can be induced in transgenic models and describes several types of preventive and therapeutic agents that have been tested in transgenic models of mammary cancer. The effectiveness of farnesyl inhibitors, aromatase inhibitors, differentiating agents, polyamine inhibitors, anti-angiogenic inhibitors, and immunotherapeutic compounds including vaccines have been evaluated in reducing mammary cancer and tumor progression in transgenic models.

The untapped potential of genetically engineered mouse models in chemoprevention research: Opportunities and challenges

The past decade has witnessed the unveiling of a powerful new generation of genetically engineered mouse (GEM) models of human cancer, which are proving to be highly effective for elucidating cancer mechanisms and interrogating novel experimental therapeutics. This new generation of GEM models are well suited for chemoprevention research, particularly for investigating progressive stages of carcinogenesis, identifying biomarkers for early detection and intervention, and preclinical assessment of novel agents or combinations of agents. Here we discuss opportunities and challenges for the application of GEM models in prevention research, as well as strategies to maximize their relevance for human cancer.

Comparison of strong cation exchange and SDS-PAGE fractionation for analysis of multiprotein complexes.

Affinity purification of protein complexes followed by identification using liquid chromatography/mass spectrometry (LC-MS/MS) is a robust method to study the fundamental process of protein interaction. Although affinity isolation reduces the complexity of the sample, fractionation prior to LC-MS/MS analysis is still necessary to maximize protein coverage. In this study, we compared the protein coverage obtained via LC-MS/MS analysis of protein complexes prefractionated using two commonly employed methods, SDS-PAGE and strong cation exchange chromatography (SCX). The two complexes analyzed focused on the nuclear proteins Bmi-1 and GATA3 that were expressed within the cells at low and high levels, respectively. Prefractionation of the complexes at the peptide level using SCX consistently resulted in the identification of approximately 3-fold more proteins compared to separation at the protein level using SDS-PAGE. The increase in the number of identified proteins was especially pronounced for the Bmi-1 complex, where the target protein was expressed at a low level. The data show that prefractionation of affinity isolated protein complexes using SCX prior to LC-MS/MS analysis significantly increases the number of identified proteins and individual protein coverage, particularly for target proteins expressed at low levels.

Lack of effect of metformin on mammary carcinogenesis in nondiabetic rat and mouse models.

Epidemiologic studies have shown that diabetics receiving the biguanide metformin, as compared with sulfonylureas or insulin, have a lower incidence of breast cancer. Metformin increases levels of activated AMPK (AMP-activated protein kinase) and decreases circulating IGF-1; encouraging its potential use in both cancer prevention and therapeutic settings. In anticipation of clinical trials in nondiabetic women, the efficacy of metformin in nondiabetic rat and mouse mammary cancer models was evaluated. Metformin was administered by gavage or in the diet, at a human equivalent dose, in standard mammary cancer models: (i) methylnitrosourea (MNU)-induced estrogen receptor–positive (ER+) mammary cancers in rats, and (ii) MMTV-Neu/p53KO ER− (estrogen receptor–negative) mammary cancers in mice. In the MNU rat model, metformin dosing (150 or 50 mg/kg BW/d, by gavage) was ineffective in decreasing mammary cancer multiplicity, latency, or weight. Pharmacokinetic studies of metformin (150 mg/kg BW/d, by gavage) yielded plasma levels (Cmax and AUC) higher than humans taking 1.5 g/d. In rats bearing small palpable mammary cancers, short-term metformin (150 mg/kg BW/d) treatment increased levels of phospho-AMPK and phospho-p53 (Ser20), but failed to reduce Ki67 labeling or expression of proliferation-related genes. In the mouse model, dietary metformin (1,500 mg/kg diet) did not alter final cancer incidence, multiplicity, or weight. Metformin did not prevent mammary carcinogenesis in two mammary cancer models, raising questions about metformin efficacy in breast cancer in nondiabetic populations. Cancer Prev Res; 8(3); 231–9. ©2015 AACR.

Functional Analysis of Prognostic Gene Expression Network Genes in Metastatic Breast Cancer Models

Identification of conserved co-expression networks is a useful tool for clustering groups of genes enriched for common molecular or cellular functions [1]. The relative importance of genes within networks can frequently be inferred by the degree of connectivity, with those displaying high connectivity being significantly more likely to be associated with specific molecular functions [2]. Previously we utilized cross-species network analysis to identify two network modules that were significantly associated with distant metastasis free survival in breast cancer. Here, we validate one of the highly connected genes as a metastasis associated gene. Tpx2, the most highly connected gene within a proliferation network specifically prognostic for estrogen receptor positive (ER+) breast cancers, enhances metastatic disease, but in a tumor autonomous, proliferation-independent manner. Histologic analysis suggests instead that variation of TPX2 levels within disseminated tumor cells may influence the transition between dormant to actively proliferating cells in the secondary site. These results support the co-expression network approach for identification of new metastasis-associated genes to provide new information regarding the etiology of breast cancer progression and metastatic disease.

Genetic Background May Contribute to PAM50 Gene Expression Breast Cancer Subtype Assignments

Recent advances in genome wide transcriptional analysis have provided greater insights into the etiology and heterogeneity of breast cancer. Molecular signatures have been developed that stratify the conventional estrogen receptor positive or negative categories into subtypes that are associated with differing clinical outcomes. It is thought that the expression patterns of the molecular subtypes primarily reflect cell-of-origin or tumor driver mutations. In this study however, using a genetically engineered mouse mammary tumor model we demonstrate that the PAM50 subtype signature of tumors driven by a common oncogenic event can be significantly influenced by the genetic background on which the tumor arises. These results have important implications for interpretation of “snapshot” expression profiles, as well as suggesting that incorporation of genetic background effects may allow investigation into phenotypes not initially anticipated in individual mouse models of cancer.

Pathologic progression of mammary carcinomas in a C3(1)/SV40 T/t-antigen transgenic rat model of human triple-negative and Her2-positive breast cancer

The C3(1) component of the rat prostate steroid binding protein has been used to target expression of the SV40 T/t-antigen to the mammary epithelium of mice resulting in pre-neoplastic lesions that progress to invasive and metastatic cancer with molecular features of human basal-type breast cancer. However, there are major differences in the histologic architecture of the stromal and epithelial elements between the mouse and human mammary glands. The rat mammary gland is more enriched with epithelial and stromal components than the mouse and more closely resembles the cellular composition of the human gland. Additionally, existing rat models of mammary cancer are typically estrogen receptor positive and hormone responsive, unlike most genetically engineered mouse mammary cancer models. In an attempt to develop a mammary cancer model that might more closely resemble the pathology of human breast cancer, we generated a novel C3(1)/SV40 T/t-antigen transgenic rat model that developed progressive mammary lesions leading to highly invasive adenocarcinomas. However, aggressive tumor development prevented the establishment of transgenic lines. Characterization of the tumors revealed that they were primarily estrogen receptor and progesterone receptor negative, and either her2/neu positive or negative, resembling human triple-negative or Her2 positive breast cancer. Tumors expressed the basal marker K14, as well as the luminal marker K18, and were negative for smooth muscle actin. The triple negative phenotype has not been previously reported in a rat mammary cancer model. Further development of a C3(1)SV40 T/t-antigen based model could establish valuable transgenic rat lines that develop basal-type mammary tumors.

Bioinformatics Approaches to the Analysis of the Transcriptome of Animal Models of Cancer

The development of genetically engineered mouse (GEM) models of human disease have played an integral role in understanding the mechanisms of action of many classes of genes involved in cancer development and progression. Their development has been critical in exploring the complexity of interactions of biological processes occurring in the entire organism, particularly when combined with recent global genomic approaches and bioinformatics. It has become apparent that breast cancer is a heterogeneous disease and multiple GEM models must be incorporated to represent the various forms of the human disease. Undoubtedly, these models and methods will be invaluable in the establishment of biomarkers and novel therapeutic approaches for patients with various subtypes of breast cancer.