Despite enormous expenditures and efforts by academic, government, and pharmaceutical institutions, most drugs that show promise against human breast cancer in preclinical testing in mice, fail to cure breast cancer in the clinic. There is a great need for improved drug response-predictive testing of human breast cancer in the preclinical setting to identify the best drug candidates. Based on novel insight gained in our laboratories, as a key first step we propose to correct the mouse endocrine environment to more adequately mimic the endocrine environment of breast cancer patients. Novel and independent insight from the two collaborating laboratories suggest that prolactin acts as a modulator of drug sensitivity in human breast cancer. Prolactin receptors are expressed, often at elevated levels, in a majority of human breast cancers. However, current mouse models are inadequate since mouse prolactin prevents activation of human prolactin receptors. Thus, current predictive testing of drugs against human breast cancer is performed on human breast cancer lines selected for growth under prolactin-free conditions. We will now test the role of prolactin as a modulator of breast cancer drug sensitivity and biology. For this study, a mouse model that expresses physiological levels of human prolactin has been genetically engineered for more accurate predictive testing of drugs on human breast cancer xenotransplants. The central hypothesis is that PRL receptor signaling, through its effects on mammary cell survival, growth, and differentiation, modulates sensitivity of breast cancer cells to anti-tumor agents. Consistent with this, we further hypothesize that mice, in which endogenous mouse prolactin has been replaced with physiological levels of human prolactin, will restore prolactin receptor signaling in human breast cancer xenotransplants and provide a more relevant endocrine environment for improved prediction of clinical responsiveness of breast cancer to therapeutic agents. Finally, we hypothesize that the hPRL expressing mice will allow us to establish new and transplantable breast cancer lines that more closely resemble primary breast human cancer than existing metastasis-derived tumor cell lines. If successful, the new mouse model would be available for testing of a broad number of human breast cancer drug candidates, with the potential for more reliable prediction of clinical efficacy. In addition, successful transplantation of primary breast cancer tissue with epithelial and stromal components will pave the road to a new personalized medicine approach to treatment of breast cancer patients.

Public Health Relevance

Most drugs that work when tested on human breast cancer in mice, fail to cure breast cancer in humans. There is a great need to improve the ability to predict whether candidate breast cancer drugs will work in patients. To this end, we have developed a new mouse model with a hormone environment that more closely resembles that of breast cancer patients. We will test the hypothesis that the new mouse represents an improved preclinical model for more accurate predictive testing of breast cancer drug candidates.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA118740-04
Application #
8014944
Study Section
Tumor Cell Biology Study Section (TCB)
Program Officer
Sathyamoorthy, Neeraja
Project Start
2008-04-07
Project End
2013-01-31
Budget Start
2011-02-01
Budget End
2012-01-31
Support Year
4
Fiscal Year
2011
Total Cost
$313,385
Indirect Cost
Name
Thomas Jefferson University
Department
Microbiology/Immun/Virology
Type
Schools of Medicine
DUNS #
053284659
City
Philadelphia
State
PA
Country
United States
Zip Code
19107
Sato, T; Tran, T H; Peck, A R et al. (2014) Prolactin suppresses a progestin-induced CK5-positive cell population in luminal breast cancer through inhibition of progestin-driven BCL6 expression. Oncogene 33:2215-24
Sato, Takahiro; Tran, Thai H; Peck, Amy R et al. (2013) Global profiling of prolactin-modulated transcripts in breast cancer in vivo. Mol Cancer 12:59
Lin, Wan-chi; Rajbhandari, Nirakar; Liu, Chengbao et al. (2013) Dormant cancer cells contribute to residual disease in a model of reversible pancreatic cancer. Cancer Res 73:1821-30
Yang, Ning; Liu, Chengbao; Peck, Amy R et al. (2013) Prolactin-Stat5 signaling in breast cancer is potently disrupted by acidosis within the tumor microenvironment. Breast Cancer Res 15:R73
Peck, Amy R; Witkiewicz, Agnieszka K; Liu, Chengbao et al. (2012) Low levels of Stat5a protein in breast cancer are associated with tumor progression and unfavorable clinical outcomes. Breast Cancer Res 14:R130
Arendt, Lisa M; Rugowski, Debra E; Grafwallner-Huseth, Tara A et al. (2011) Prolactin-induced mouse mammary carcinomas model estrogen resistant luminal breast cancer. Breast Cancer Res 13:R11
Sato, Takahiro; Neilson, Lynn Moretti; Peck, Amy R et al. (2011) Signal transducer and activator of transcription-3 and breast cancer prognosis. Am J Cancer Res 1:347-55
Peck, Amy R; Witkiewicz, Agnieszka K; Liu, Chengbao et al. (2011) Loss of nuclear localized and tyrosine phosphorylated Stat5 in breast cancer predicts poor clinical outcome and increased risk of antiestrogen therapy failure. J Clin Oncol 29:2448-58
Zhang, Qian; Sakamoto, Kazuhito; Liu, Chengbao et al. (2011) Cyclin D3 compensates for the loss of cyclin D1 during ErbB2-induced mammary tumor initiation and progression. Cancer Res 71:7513-24
Tran, Thai Hong; Lin, Justin; Sjolund, Ashley Brooke et al. (2010) Protocol for constructing tissue arrays by cutting edge matrix assembly. Methods Mol Biol 664:45-52

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