Dataset Information

A phenotypic mouse model of basaloid breast tumors.

ABSTRACT: Chemotherapeutic strategies that target basal-like breast tumors are difficult to design without understanding their cellular and molecular basis. Here, we induce tumors in mice by carcinogen administration, creating a phenocopy of tumors with the diagnostic and functional aspects of human triple negative disease (including EGFR expression/lack of erbB, estrogen-independent growth and co-clustering of the transcriptome with other basaloid models). These tumor strains are a complement to established mouse models that are based on mutations in Brca1 and/or p53. Tumors comprise two distinct cell subpopulations, basal and luminal epithelial cells. These cell fractions were purified by flow cytometry, and only basal cell fractions found to have tumor initiating activity (cancer stem cells). The phenotype of serially regenerated tumors was stable, and irrespective of tumor precursor cell. Tumors were passaged entirely in vivo and serial generations tested for their phenotypic stability. The relative chemo-sensitivity of basal and luminal cells were evaluated. Upon treatment with anthracycline, tumors were effectively de-bulked, but recurred; this correlated with maintenance of a high rate of basal cell division throughout the treatment period. Thus, these tumors grow as robust cell mixtures of basal bipotential tumor initiating cells alongside a luminal majority, and the cellular response to drug administration is dominated by the distinct biology of the two cell types. Given the ability to separate basal and luminal cells, and the discovery potential of this approach, we propose that this mouse model could be a convenient one for preclinical studies.

SUBMITTER: Kim S

PROVIDER: S-EPMC3276569 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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A phenotypic mouse model of basaloid breast tumors.

Kim Soyoung S Roopra Avtar A Alexander Caroline M CM

PloS one 20120209 2

Chemotherapeutic strategies that target basal-like breast tumors are difficult to design without understanding their cellular and molecular basis. Here, we induce tumors in mice by carcinogen administration, creating a phenocopy of tumors with the diagnostic and functional aspects of human triple negative disease (including EGFR expression/lack of erbB, estrogen-independent growth and co-clustering of the transcriptome with other basaloid models). These tumor strains are a complement to establis ...[more]

PMID: 22347416

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Project description:There is a paradox offered up by the cancer stem cell hypothesis. How are the mixed populations that are characteristic of heterogeneous solid tumors maintained at constant proportion, given their high, and different, mitotic indices? In this study, we evaluate a well-characterized mouse model of human basaloid tumors (induced by the oncogene Wnt1), which comprise mixed populations of mammary epithelial cells resembling their normal basal and luminal counterparts. We show that these cell types are substantially inter-dependent, since the MMTV LTR drives expression of Wnt1 ligand in luminal cells, whereas the functional Wnt1-responsive receptor (Lrp5) is expressed by basal cells, and both molecules are necessary for tumor growth. There is a robust tumor initiating activity (tumor stem cell) in the basal cell population, which is associated with the ability to differentiate into luminal and basal cells, to regenerate the oncogenic paracrine signaling cell pair. However, we found an additional tumor stem cell activity in the luminal cell population. Knowing that tumors depend upon Wnt1-Lrp5, we hypothesized that this stem cell must express Lrp5, and found that indeed, all the stem cell activity could be retrieved from the Lrp5-positive cell population. Interestingly, this reflects post-transcriptional acquisition of Lrp5 protein expression in luminal cells. Furthermore, this plasticity of molecular expression is reflected in plasticity of cell fate determination. Thus, in vitro, Wnt1-expressing luminal cells retro-differentiate to basal cell types, and in vivo, tumors initiated with pure luminal cells reconstitute a robust basal cell subpopulation that is indistinguishable from the populations initiated by pure basal cells. We propose this is an important proof of concept, demonstrating that bipotential tumor stem cells are essential in tumors where oncogenic ligand-receptor pairs are separated into different cell types, and suggesting that Wnt-induced molecular and fate plasticity can close paracrine loops that are usually separated into distinct cell types.

Project description:Transgenic mouse tumor models have the advantage of facilitating controlled in vivo oncogenic perturbations in a common genetic background. This provides an idealized context for generating transcriptome-based diagnostic models while minimizing the inherent noisiness of high-throughput technologies. However, the question remains whether models developed in such a setting are suitable prototypes for useful human diagnostics. We show that latent factor modeling of the peripheral blood transcriptome in a mouse model of breast cancer provides the basis for using computational methods to link a mouse model to a prototype human diagnostic based on a common underlying biological response to the presence of a tumor.We used gene expression data from mouse peripheral blood cell (PBC) samples to identify significantly differentially expressed genes using supervised classification and sparse ANOVA. We employed these transcriptome data as the starting point for developing a breast tumor predictor from human peripheral blood mononuclear cells (PBMCs) by using a factor modeling approach.The predictor distinguished breast cancer patients from healthy individuals in a cohort of patients independent from that used to build the factors and train the model with 89% sensitivity, 100% specificity and an area under the curve (AUC) of 0.97 using Youden's J-statistic to objectively select the model's classification threshold. Both permutation testing of the model and evaluating the model strategy by swapping the training and validation sets highlight its stability.We describe a human breast tumor predictor based on the gene expression of mouse PBCs. This strategy overcomes many of the limitations of earlier studies by using the model system to reduce noise and identify transcripts associated with the presence of a breast tumor over other potentially confounding factors. Our results serve as a proof-of-concept for using an animal model to develop a blood-based diagnostic, and it establishes an experimental framework for identifying predictors of solid tumors, not only in the context of breast cancer, but also in other types of cancer.

Dataset Information

A phenotypic mouse model of basaloid breast tumors.

Publications

A phenotypic mouse model of basaloid breast tumors.

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