Project description:Breast cancer research is hampered by difficulties in obtaining and studying primary human breast tissue, and by the lack of in vivo preclinical models that reflect patient tumor biology accurately. To overcome these limitations, we propagated a cohort of human breast tumors grown in the epithelium-free mammary fat pad of SCID/Beige and NOD/SCID/IL2γ-receptor null (NSG) mice, under a series of transplant conditions. Both models yielded stably transplantable xenografts at comparably high rates (~23% and ~19%, respectively). Of the conditions tested, xenograft take rate was highest in the presence of a low-dose estradiol pellet. Overall, 32 stably transplantable xenograft lines were established, representing unique 25 patients. Most tumors yielding xenografts were “triple-negative” (ER-PR-HER2+) (n=19). However, we established lines from three ER-PR-HER2+ tumors, one ER+PR-HER2-, one ER+PR+HER2- and one “triple-positive” (ER+PR+HER2+) tumor. Serially passaged xenografts show biological consistency with the tumor of origin, are phenotypic stability across multiple transplant generations at the histological, transcriptomic, proteomic, and genomic levels, and show comparable treatment responses. Xenografts representing 12 patients, including two ER+ lines, showed metastasis to the mouse lung. These models thus serve as a renewable, quality-controlled tissue resource for preclinical studies investigating treatment response and metastasis. The study was designed to determine how stable patient-derived xenografts are across multiple transplant generations in mice, and to determine how closely xenografts established with pre-treatment samples cluster with xenografts established with post-treatment samples. Overall, pre-treatment and post-treatment samples derived from the same patient cluster together, and multiple transplant generations of xenografts derived from an individual patient cluster together.
Project description:Progesterone receptors (PR) are co-expressed in over half of estrogen receptor (ER) positive breast cancers and predict positive response to endocrine therapy. PR can directly and globally modify ER action to attenuate tumor growth. However, whether this suppression occurs solely through PR-ER interactions remains unknown. We assessed tumor growth in two highly ER and PR positive breast cancer patient-derived xenografts (PDX) and found that natural and synthetic progestins potently antagonize the mitogenic effects of estrogens. Here we probed the genome-wide mechanisms by which this occurs. Chronic progestin treatment reversed expression of up to half of estrogen up- and downregulated genes at the transcript level. However, fewer than a quarter of ER DNA binding events were altered by progesterone. The PR cistrome showed an interesting bimodal distribution. In the first group, more than half of PR binding sites were co-occupied by ER, with a propensity for both receptors to coordinately gain or lose binding in the presence of progesterone. In the second group, PR, but not ER, was associated with a large fraction of RNA polymerase III (Pol III)-transcribed tRNA genes regardless of hormone treatment. Furthermore, PR formed a physical association with the Pol III holoenzyme. Select tRNAs with colocalization of PR and POLR3A at their promoters were reduced in tumors grown with estrogen plus progestin compared to estrogen alone. These data uncover a mechanism in solid tumors by which PR modulates the bioavailability of translational molecules that are necessary for robust tumor growth, which could indirectly impede ER action.
Project description:Dysregulated choline metabolism is a well-known feature of breast cancer, but the underlying mechanisms are not fully understood. In this study, the metabolomic and transcriptomic characteristics of a large panel of human breast cancer xenograft models were mapped, with focus on choline metabolism. Methods: Tumor specimens from 34 patient-derived xenograft models were collected and divided in two. One part was examined using high-resolution magic angle spinning (HR-MAS) MR spectroscopy while another part was analysed using gene expression microarrays. Expression data of genes encoding proteins in the choline metabolism pathway were analysed and correlated to the levels of choline (Cho), phosphocholine (PCho) and glycerophosphocholine (GPC) using Pearson’s correlation analysis. For comparison purposes, metabolic and gene expression data were collected from human breast tumors belonging to corresponding molecular subgroups. Results: Most of the xenograft models were classified as basal-like (N=19) or luminal B (N=7). These two subgroups showed significantly different choline metabolic and gene expression profiles. The luminal B xenografts were characterized by a high PCho/GPC ratio while the basal-like xenografts were characterized by highly variable PCho/GPC ratio. Also, Cho, PCho and GPC levels were correlated to expression of several genes encoding proteins in the choline metabolism pathway, including choline kinase alpha (CHKA) and glycerophosphodiester phosphodiesterase domain containing 5 (GDPD5). These characteristics were similar to those found in human tumor samples. Discussion: The higher PCho/GPC ratio found in luminal B compared with most basal-like breast cancer xenograft models and human tissue samples do not correspond to results observed from in vitro studies. It is likely that microenvironmental factors play a role in the in vivo regulation of choline metabolism. Cho, PCho and GPC were correlated to different choline pathway-encoding genes in luminal B compared with basal-like xenografts, suggesting that regulation of choline metabolism may vary between different breast cancer subgroups. The concordance between the metabolic and gene expression profiles from xenograft models with breast cancer tissue samples from patients indicates that these xenografts are representative models of human breast cancer and represent relevant models to study tumor metabolism in vivo. Gene expression was measured in 30 human breast cancer xenografts, one sample from each model