Mouse Models of Breast Cancer Share Amplification and Deletion Events with Human Breast Cancer

Molecular Characterization and Landscape of Breast cancer Models from a multi-omics Perspective

Breast cancer is well-known to be a highly heterogenous disease. This facet of cancer makes finding a research model that mirrors the disparate intrinsic features challenging. With advances in multi-omics technologies, establishing parallels between the various models and human tumors is increasingly intricate. Here we review the various model systems and their relation to primary breast tumors using available omics data platforms. Among the research models reviewed here, breast cancer cell lines have the least resemblance to human tumors since they have accumulated many mutations and copy number alterations during their long use. Moreover, individual proteomic and metabolomic profiles do not overlap with the molecular landscape of breast cancer. Interestingly, omics analysis revealed that the initial subtype classification of some breast cancer cell lines was inappropriate. In cell lines the major subtypes are all well represented and share some features with primary tumors. In contrast, patient-derived xenografts (PDX) and patient-derived organoids (PDO) are superior in mirroring human breast cancers at many levels, making them suitable models for drug screening and molecular analysis. While patient derived organoids are spread across luminal, basal- and normal-like subtypes, the PDX samples were initially largely basal but other subtypes have been increasingly described. Murine models offer heterogenous tumor landscapes, inter and intra-model heterogeneity, and give rise to tumors of different phenotypes and histology. Murine models have a reduced mutational burden compared to human breast cancer but share some transcriptomic resemblance, and representation of many breast cancer subtypes can be found among the variety subtypes. To date, while mammospheres and three- dimensional cultures lack comprehensive omics data, these are excellent models for the study of stem cells, cell fate decision and differentiation, and have also been used for drug screening. Therefore, this review explores the molecular landscapes and characterization of breast cancer research models by comparing recent published multi-omics data and analysis.

Characterization of Mammary Tumors Arising from MMTV-PyVT Transgenic Mice

Among genetically engineered mouse models of breast cancer, MMTV-PyVT is a mouse strain in which the oncogenic polyoma virus middle T antigen is driven by the mouse mammary tumor virus promoter. The aim of the present study was to perform morphologic and genetic analyses of mammary tumors arising from MMTV-PyVT mice. To this end, mammary tumors were obtained at 6, 9, 12, and 16 weeks of age for histology and whole-mount analyses. We conducted whole-exome sequencing to identify constitutional and tumor-specific mutations, and genetic variants were identified using the GRCm38/mm10 mouse reference genome. Using hematoxylin and eosin analysis and whole-mount carmine alum staining, we demonstrated the progressive proliferation and invasion of mammary tumors. Frameshift insertions/deletions (indels) were noted in the Muc4. Mammary tumors showed small indels and nonsynonymous single-nucleotide variants but no somatic structural alterations or copy number variations. In summary, we validated MMTV-PyVT transgenic mice as a multistage model for mammary carcinoma development and progression. Our characterization may be used as a reference for guidance in future research.

The Viral Origin of Human Breast Cancer: From the Mouse Mammary Tumor Virus (MMTV) to the Human Betaretrovirus (HBRV)

A Human Betaretrovirus (HBRV) has been identified in humans, dating as far back as about 4500 years ago, with a high probability of it being acquired by our species around 10,000 years ago, following a species jump from mice to humans. HBRV is the human homolog of the MMTV (mouse mammary tumor virus), which is the etiological agent of murine mammary tumors. The hypothesis of a HMTV (human mammary tumor virus) was proposed about 50 years ago, and has acquired a solid scientific basis during the last 30 years, with the demonstration of a robust link with breast cancer and with PBC, primary biliary cholangitis. This article summarizes most of what is known about MMTV/HMTV/HBRV since the discovery of MMTV at the beginning of last century, to make evident both the quantity and the quality of the research supporting the existence of HBRV and its pathogenic role. Here, it is sufficient to mention that scientific evidence includes that viral sequences have been identified in breast-cancer samples in a worldwide distribution, that the complete proviral genome has been cloned from breast cancer and patients with PBC, and that saliva contains HBRV, as a possible route of inter-human infection. Controversies that have arisen concerning results obtained from human tissues, many of them outdated by new scientific evidence, are critically discussed and confuted.

Annexin A1 Is Required for Efficient Tumor Initiation and Cancer Stem Cell Maintenance in a Model of Human Breast Cancer

Simple Summary

Triple-negative breast cancer (TNBC) has a poor outcome compared to the other major breast cancer subtypes and new therapies are needed. We sought to clarify the functions of a ubiquitous protein, Annexin A1, in the development and progression of TNBC. We found that Annexin A1 expression correlated with poor patient prognosis in basal-like breast tumors and also in the basal like-2 subset of TNBCs. Stable knockdown of Annexin A1 attenuated the growth of SUM149 xenografts, which model basal-like 2 tumors. In a polyoma middle T antigen-driven allograft model of breast cancer, Annexin A1 depletion markedly delayed tumor formation, induced epithelial to mesenchymal transition and upregulated basal markers. Finally, loss of Annexin A1 resulted in the loss of a discrete CD24⁺/Sca1⁻ population containing putative tumor-initiating cells. Collectively, our data demonstrate a novel cell-autonomous role for Annexin A1 in the promotion of tumor-forming capacity in certain TNBC tumors.

Abstract

Triple-negative breast cancer (TNBC) has a poor outcome compared to other breast cancer subtypes, and new therapies that target the molecular alterations driving tumor progression are needed. Annexin A1 is an abundant multi-functional Ca²⁺ binding and membrane-associated protein. Reported roles of Annexin A1 in breast cancer progression and metastasis are contradictory. Here, we sought to clarify the functions of Annexin A1 in the development and progression of TNBC. The association of Annexin A1 expression with patient prognosis in subtypes of TNBC was examined. Annexin A1 was stably knocked down in a panel of human and murine TNBC cell lines with high endogenous Annexin A1 expression that were then evaluated for orthotopic growth and spontaneous metastasis in vivo and for alterations in cell morphology in vitro. The impact of Annexin A1 knockdown on the expression of genes involved in mammary epithelial cell differentia tion and epithelial to mesenchymal transition was also determined. Annexin A1 mRNA levels correlated with poor patient prognosis in basal-like breast tumors and also in the basal-like 2 subset of TNBCs. Unexpectedly, loss of Annexin A1 expression had no effect on either primary tumor growth or spontaneous metastasis of MDA-MB-231_HM xenografts, but abrogated the growth rate of SUM149 orthotopic tumors. In an MMTV-PyMT driven allograft model of breast cancer, Annexin A1 depletion markedly delayed tumor formation in both immuno-competent and immuno-deficient mice and induced epithelial to mesenchymal transition and upregulation of basal markers. Finally, loss of Annexin A1 resulted in the loss of a discrete CD24⁺/Sca1⁻ population containing putative tumor initiating cells. Collectively, our data demonstrate a novel cell-autonomous role for Annexin A1 in the promotion of tumor-forming capacity in a model of human breast cancer and suggest that some basal-like TNBCs may require high endogenous tumor cell Annexin A1 expression for continued growth.

Insights from transgenic mouse models of PyMT-induced breast cancer: recapitulating human breast cancer progression in vivo

Breast cancer is associated with the second highest cancer-associated deaths worldwide. Therefore, understanding the key events that determine breast cancer progression, modulation of the tumor-microenvironment and metastasis, which is the main cause of cancer-associated death, are of great importance. The mammary specific polyomavirus middle T antigen overexpression mouse model (MMTV-PyMT), first published in 1992, is the most commonly used genetically engineered mouse model (GEMM) for cancer research. Mammary lesions arising in MMTV-PyMT mice follow similar molecular and histological progression as human breast tumors, making it an invaluable tool for cancer researchers and instrumental in understanding tumor biology. In this review, we will highlight key studies that demonstrate the utility of PyMT derived GEMMs in understanding the molecular basis of breast cancer progression, metastasis and highlight its use as a pre-clinical tool for therapeutic discovery.

Low E2F2 activity is associated with high genomic instability and PARPi resistance

The E2F family, classically known for a central role in cell cycle, has a number of emerging roles in cancer including angiogenesis, metabolic reprogramming, metastasis and DNA repair. E2F1 specifically has been shown to be a critical mediator of DNA repair; however, little is known about DNA repair and other E2F family members. Here we present an integrative bioinformatic and high throughput drug screening study to define the role of E2F2 in maintaining genomic integrity in breast cancer. We utilized in vitro E2F2 ChIP-chip and over expression data to identify transcriptional targets of E2F2. This data was integrated with gene expression from E2F2 knockout tumors in an MMTV-Neu background. Finally, this data was compared to human datasets to identify conserved roles of E2F2 in human breast cancer through the TCGA breast cancer, Cancer Cell Line Encyclopedia, and CancerRx datasets. Through these methods we predict that E2F2 transcriptionally regulates mediators of DNA repair. Our gene expression data supports this hypothesis and low E2F2 activity is associated with a highly unstable tumor. In human breast cancer E2F2, status was also correlated with a patient's response to PARP inhibition therapy. Taken together this manuscript defines a novel role of E2F2 in cancer progression beyond cell cycle and could impact patient treatment.

Metastasis-Specific Gene Expression in Autochthonous and Allograft Mouse Mammary Tumor Models: Stratification and Identification of Targetable Signatures

Breast cancer metastasis is a leading cause of cancer-related death of women in the United States. A hurdle in advancing metastasis-targeted intervention is the phenotypic heterogeneity between primary and secondary lesions. To identify metastasis-specific gene expression profiles we performed RNA-sequencing of breast cancer mouse models; analyzing metastases from models of various drivers and routes. We contrasted the models and identified common, targetable signatures. Allograft models exhibited more mesenchymal-like gene expression than genetically engineered mouse models (GEMM), and primary culturing of GEMM-derived metastatic tissue induced mesenchymal-like gene expression. In addition, metastasis-specific transcriptomes differed between tail vein and orthotopic injection of the same cell line. Gene expression common to models of spontaneous metastasis included sildenafil response and nicotine degradation pathways. Strikingly, in vivo sildenafil treatment significantly reduced metastasis by 54%, while nicotine significantly increased metastasis by 46%. These data suggest that (i) actionable metastasis-specific pathways can be readily identified, (ii) already available drugs may have great potential to alleviate metastatic incidence, and (iii) metastasis may be influenced greatly by lifestyle choices such as the choice to consume nicotine products. In summary, while mouse models of breast cancer metastasis vary in ways that must not be ignored, there are shared features that can be identified and potentially targeted therapeutically. IMPLICATIONS: The data we present here exposes critical variances between preclinical models of metastatic breast cancer and identifies targetable pathways integral to metastatic spread. VISUAL OVERVIEW: http://mcr.aacrjournals.org/content/molcanres/18/9/1278/F1.large.jpg.

Normal mammary gland development after MMTV-Cre mediated conditional PAK4 gene depletion

p21-activated kinases (PAKs) are serine/threonine kinases functioning as downstream effectors of the small GTPases Rac1 and Cdc42. Members of the PAK family are overexpressed in human breast cancer, but their role in mammary gland development is not fully explored. Here we examined the functional role of PAK4 in mammary gland development by creating a mouse model of MMTV-Cre driven conditional PAK4 gene depletion in the mammary gland. The PAK4 conditional knock-out mice were born healthy, with no observed developmental deficits. Mammary gland whole-mounts revealed no defects in ductal formation or elongation of the mammary tree through the fat pad. PAK4 gene depletion also did not alter proliferation and invasion of the mammary epithelium in young virgin mice. Moreover, adult mice gave birth to healthy pups with normal body weight upon weaning. This implies that MMTV-Cre induced gene depletion of PAK4 in mice does not impair normal mammary gland development and thereby provides an in vivo model that can be explored for examination of the potential function of PAK4 in breast cancer.

How to Choose a Mouse Model of Breast Cancer, a Genomic Perspective

Human breast cancer is a heterogeneous disease with numerous subtypes that have been defined through immunohistological, histological, and gene expression patterns. The diversity of breast cancer has made the study of its various underlying causes complex. To facilitate the examination of particular facets of breast cancer, mouse models have been generated, ranging from carcinogen induced models to genetically engineered mice. While mouse models have been generated to mimic the initiating event, including p53 loss, BRCA loss, or overexpression of HER2 / Neu / erbB2, other genomic events are often not well characterized. However, these secondary genetic events are often critical to the mouse tumor evolution, subtype, and outcome, just as they are in human breast cancer. As such, these other genomic events are a critical component of what models are chosen to study specific subtypes of human breast cancer. Here we review the genomic analyses that have been completed for various genetically engineered mouse models, how they compare to human breast cancer, and detail how this information can be used in choosing a mouse model for analysis.

PAK4 suppresses RELB to prevent senescence-like growth arrest in breast cancer

Overcoming cellular growth restriction, including the evasion of cellular senescence, is a hallmark of cancer. We report that PAK4 is overexpressed in all human breast cancer subtypes and associated with poor patient outcome. In mice, MMTV-PAK4 overexpression promotes spontaneous mammary cancer, while PAK4 gene depletion delays MMTV-PyMT driven tumors. Importantly, PAK4 prevents senescence-like growth arrest in breast cancer cells in vitro, in vivo and ex vivo, but is not needed in non-immortalized cells, while PAK4 overexpression in untransformed human mammary epithelial cells abrogates H-RAS-V12-induced senescence. Mechanistically, a PAK4 – RELB - C/EBPβ axis controls the senescence-like growth arrest and a PAK4 phosphorylation residue (RELB-Ser151) is critical for RELB-DNA interaction, transcriptional activity and expression of the senescence regulator C/EBPβ. These findings establish PAK4 as a promoter of breast cancer that can overcome oncogene-induced senescence and reveal a selective vulnerability of cancer to PAK4 inhibition.

Oncogene induced senescence protects cells from unrestricted growth and cancer. Here, the authors show that PAK4 overrides this senescence in breast cancer cells through phosphorylation of RELB, thereby inhibiting transcription of the senescence regulator C/EBPβ.

Integrated analyses of murine breast cancer models reveal critical parallels with human disease

Mouse models have an essential role in cancer research, yet little is known about how various models resemble human cancer at a genomic level. Here, we complete whole genome sequencing and transcriptome profiling of two widely used mouse models of breast cancer, MMTV-Neu and MMTV-PyMT. Through integrative in vitro and in vivo studies, we identify copy number alterations in key extracellular matrix proteins including collagen 1 type 1 alpha 1 (COL1A1) and chondroadherin (CHAD) that drive metastasis in these mouse models. In addition to copy number alterations, we observe a propensity of the tumors to modulate tyrosine kinase-mediated signaling through mutation of phosphatases such as PTPRH in the MMTV-PyMT mouse model. Mutation in PTPRH leads to increased phospho-EGFR levels and decreased latency. These findings underscore the importance of understanding the complete genomic landscape of a mouse model and illustrate the utility this has in understanding human cancers.

Mouse models are an essential tool in breast cancer research. Here, the authors present the genomic and transcriptomic profiles of two widely used mouse models, revealing parallels with the human disease specifically with metastasis and treatment response.

Feasibility of analyzing DNA copy number variation in breast cancer tumor specimens from 1950 to 2010: how old is too old?

PURPOSE

The purpose of the study was to assess the feasibility of quantifying long-term trends in breast tumor DNA copy number variation (CNV) profiles.

METHODS

We evaluated CNV profiles in formalin-fixed paraffin-embedded (FFPE) tumor specimens from 30 randomly selected Kaiser Permanente Northern California health plan women members diagnosed with breast cancer from 1950 to 2010. Assays were conducted for five cases per decade who had available tumor blocks and pathology reports.

RESULTS

As compared to the tumors from the 1970s to 2000s, the older tumors dating back to the 1950s and 1960s were much more likely to (1) fail quality control, and (2) have fewer CNV events (average 23 and 31 vs. 58 to 69), fewer CNV genes (average 5.1 and 3.7k vs. 8.1 to 10.3k), shorter CNV length (average 2,440 and 3,300k vs. 5,740 to 9,280k), fewer high frequency Del genes (37 and 25% vs. 54 to 76%), and fewer high frequency high_Amp genes (20% vs. 56 to 73%). On average, assay interpretation took an extra 60 min/specimen for cases from the 1960s versus 20 min/specimen for the most recent tumors.

CONCLUSIONS

Assays conducted in the mid-2010s for CNVs may be feasible for FFPE tumor specimens dating back to the 1980s, but less feasible for older specimens.

Using gene expression data to direct breast cancer therapy: evidence from a preclinical trial

The heterogeneity both within and between breast cancers presents a significant clinical challenge for both diagnosis and therapy. This heterogeneity is present at all levels of analysis in breast cancer, ranging from genomic to metabolomic. A function of this heterogeneity is that numerous signaling networks are activated, and while treatment of one arm may be initially effective, this allows the tumor to be poised to evolve a resistance mechanism. Here we review the classification of breast cancers and discuss therapy of hormone positive, HER2 positive, and triple negative breast cancers. Model systems for breast cancer are examined allowing for a preclinical trial using a personalized medicine approach to be tested. This preclinical trial was based solely on cell signaling pathway activation and effectively and specifically blocked tumor growth in a preclinical model system.

Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers

Human breast cancer has been characterized by extensive transcriptional heterogeneity, with dominant patterns reflected in the intrinsic subtypes. Mouse models of breast cancer also have heterogeneous transcriptomes and we noted that specific histological subtypes were associated with particular subsets. We hypothesized that unique sets of genes define each tumor histological type across mouse models of breast cancer. Using mouse models that contained both gene expression data and expert pathologist classification of tumor histology on a sample by sample basis, we predicted and validated gene expression signatures for Papillary, EMT, Microacinar and other histological subtypes. These signatures predict known histological events across murine breast cancer models and identify counterparts of mouse mammary tumor types in subtypes of human breast cancer. Importantly, the EMT, Adenomyoepithelial, and Solid signatures were predictive of clinical events in human breast cancer. In addition, a pan-cancer comparison revealed that the histological signatures were active in a variety of human cancers such as lung, oral, and esophageal squamous tumors. Finally, the differentiation status and transcriptional activity implicit within these signatures was identified. These data reveal that within tumor histology groups are unique gene expression profiles of differentiation and pathway activity that stretch well beyond the transgenic initiating events and that have clear applicability to human cancers. As a result, our work provides a predictive resource and insights into possible mechanisms that govern tumor heterogeneity.

Triple-negative breast cancer and the potential for targeted therapy

Breast cancer is composed of several well-recognized subtypes including estrogen receptor, progesterone receptor and HER2 triple-negative breast cancer (TNBC). Without available targeted therapy options, standard of care for TNBC remains chemotherapy. It is of interest to note that TNBC tumors generally have better responses to chemotherapy compared with other subtypes. However, patients without complete response account for approximately 80% of TNBC. Mounting evidence suggests significant heterogeneity within the TNBC subtype, and studies have focused on genetic targets with high rates of altered expression. Recent studies suggest clear possibilities for benefits from targeted therapy in TNBC. In this review, we summarize studies of targeted therapy, including within mouse models, and discuss their applications in the development of combinatorial treatments to treat TNBC.