Abstract
Despite improved detection and reduction of breast cancer-related deaths over the recent decade, breast cancer remains the second leading cause of cancer death for women in the US, with 39,510 women expected to succumb to metastatic disease in 2012 alone (American Cancer Society, Cancer Facts &Figures 2012. Atlanta: American Cancer Society; 2012). Continued efforts in classification of breast cancers based on gene expression profiling and genomic sequencing have revealed an underlying complexity and molecular heterogeneity within the disease that continues to challenge therapeutic interventions. To successfully identify and translate new treatment regimens to the clinic, it is imperative that our preclinical models recapitulate this complexity and heterogeneity. In this review article, we discuss the recent advances in development and classification of patient-derived human breast tumor xenograft models that have the potential to facilitate the next phase of drug discovery for personalized cancer therapy based on the unique driver signaling pathways in breast tumor subtypes.
Highlights
Despite improved detection and reduction of breast cancer-related deaths over the recent decade, breast cancer remains the second leading cause of cancer death for women in the US, with 39,510 women expected to succumb to metastatic disease in 2012 alone
Only recently have technological advances allowed comparison of xenografted tumors to primary patient tumors at a level previously unobtainable, allowing the subtype classification of patient-derived xenograft (PDX) tumors. New technologies such as intravital microscopy show unique conserved morphology and vascularization compared to injected cell lines, allowing prediction and optimization of therapeutic strategies based on tumor biology
Personalized medicine is intended to select subsets of patients that will most likely respond to treatment regimens, reducing morbidity and mortality from ineffective treatments
Summary
CGH, comparative genomic hybridization; ER, estrogen receptor; HER2, human epidermal growth factor receptor-2; IHC, immunohistochemistry; NOD, non-obese diabetic; NSG, NOD/SCID/IL2γ-receptor null; PR, progesterone receptor; SCID, severe combined immunodeficiency; TG, transplant generation; TN, triple negative; TNBC, triple negative breast cancer. Generating PDXs with humanized stroma components can improve the evaluation of microenvironmental influences on treatment response for a limited number of models [32], technical challenges of matching each tumor with its own stromal components currently precludes generation of large cohorts for preclinical testing. These models lack an intact immune system, which can play both a prohibitive and activating role in tumor development and therapeutic response (reviewed in [33]). Well-defined genetically engineered mouse models that represent the heterogeneity and complexity of tumor etiology, such as TP53 null tumor models, will be essential in evaluating immunological
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