Project description:Intratumor heterogeneity caused by genetic, phenotypic or functional differences between cancer cell subpopulations is a considerable clinical challenge. Understanding subpopulation dynamics is therefore central for both optimization of existing therapy and for development of new treatment. The aim of this study was to isolate subpopulations from a primary tumor and by comparing molecular characteristics of these subpopulations, find explanations to their differing tumorigenicity. Cell subpopulations from two patient derived in vivo models of primary breast cancer, ER+ and ER-, were identified. EpCAM+ cells from the ER+ model gave rise to tumors independently of stroma cell support. The tumorigenic fraction was further divided based on SSEA-4 and CD24 expression. Both markers were expressed in ER+ breast cancer biopsies. FAC-sorted cells based on EpCAM, SSEA-4 and CD24 expression were subsequently tested for differences in functionality by in vivo tumorigenicity assay. Three out of four subpopulations of cells were tumorigenic and showed variable ability to recapitulate the marker expression of the original tumor. Whole genome expression analysis of the sorted populations disclosed high similarity in the transcriptional profiles between the tumorigenic populations. Comparing the non-tumorigenic vs the tumorigenic populations, 44 transcripts were, however, significantly differentially expressed. A subset of these, 26 identified and named genes, highly expressed in the non-tumorigenic population, predicted longer overall survival (N?=?737, p<0.0001) and distant metastasis free survival (DMFS) (N?=?1379, p<0.0001) when performing Kaplan-Meier survival analysis using the GOBO online database. The 26 gene set correlated with longer DMFS in multiple breast cancer subgroups. Copy number profiling revealed no aberrations that could explain the observed differences in tumorigenicity. This study emphasizes the functional variability among cell populations that are otherwise genomically similar, and that the risk of breast cancer recurrence can only be eliminated if the tumorigenic abilities in multiple cancer cell subpopulations are inhibited.

Project description:The cellular heterogeneity of one patient derived orthotopic breast cancer xenograft model (PDBCX) was investigated using flow cytometry , combined with assessment of in vivo tumorigenicity and whole genome expression profiling. Epithelial cell adhesion molecule (EpCAM) was revealed as a highly specific cell surface marker of the human tumor cell population in both xenografts. Based on expression patterns observed in primary tumor tissue, SSEA-4 and CD24 were chosen as markers to further subdivide the luminal tumor cells into four subpopulations. FACS sorting was used to isolate four cell subpopulations. Results: In vivo tumorigenicity assay showed that SSEA-4+/CD24+ cells were non-tumorigenic, while the three other subpopulations were tumorigenic. Tumors resulting from the SSEA-4+/CD24- subpopulation of luminal cancer cells, did not express CD24, while tumors arising from the SSEA-4-/CD24-, and SSEA-4-/CD24+ populations both recapitulated the original tumor containing all four subpopulations. Whole genome expression analysis revealed distinct transcriptional profiles, and 44 genes were significantly differentially expressed when comparing the tumorigenic vs non-tumorigenic populations. Several interesting genes putatively suppressing the cancer cells ability to initiate tumors in vivo were upregulated in the non-tumorigenic population. We here show that tumor initiating cells within one primary tumor evidently included more than one phenotype. Furthermore, with respect to cell surface marker expression, one of the subpopulations produced tumors unlike both the originating cells, and the original tumor. Discussion: Our results imply that subpopulations from one primary tumor can give rise to dissimilar daughter tumors. These tumors may not necessarily respond to the same targeted treatment, and thereby represent a therapy escape mechanism. This study highlights that to remove the risk of breast cancer recurrence, inhibition of the molecules critical for driving the tumor progression in several tumor cell subpopulations might be essential Gene expression was measured in four cell subpopulations isolated from Patient derived human luminal-like breast cancer xenograft. Four replicates from three subpopulations and three replicates from one subpopulation.

Project description:The cellular heterogeneity of one patient derived orthotopic breast cancer xenograft model (PDBCX) was investigated using flow cytometry , combined with assessment of in vivo tumorigenicity and whole genome expression profiling. Epithelial cell adhesion molecule (EpCAM) was revealed as a highly specific cell surface marker of the human tumor cell population in both xenografts. Based on expression patterns observed in primary tumor tissue, SSEA-4 and CD24 were chosen as markers to further subdivide the luminal tumor cells into four subpopulations. FACS sorting was used to isolate four cell subpopulations. Results: In vivo tumorigenicity assay showed that SSEA-4+/CD24+ cells were non-tumorigenic, while the three other subpopulations were tumorigenic. Tumors resulting from the SSEA-4+/CD24- subpopulation of luminal cancer cells, did not express CD24, while tumors arising from the SSEA-4-/CD24-, and SSEA-4-/CD24+ populations both recapitulated the original tumor containing all four subpopulations. Whole genome expression analysis revealed distinct transcriptional profiles, and 44 genes were significantly differentially expressed when comparing the tumorigenic vs non-tumorigenic populations. Several interesting genes putatively suppressing the cancer cells ability to initiate tumors in vivo were upregulated in the non-tumorigenic population. We here show that tumor initiating cells within one primary tumor evidently included more than one phenotype. Furthermore, with respect to cell surface marker expression, one of the subpopulations produced tumors unlike both the originating cells, and the original tumor. Discussion: Our results imply that subpopulations from one primary tumor can give rise to dissimilar daughter tumors. These tumors may not necessarily respond to the same targeted treatment, and thereby represent a therapy escape mechanism. This study highlights that to remove the risk of breast cancer recurrence, inhibition of the molecules critical for driving the tumor progression in several tumor cell subpopulations might be essential

Project description:The number of relevant and well-characterized cell lines and xenograft models for studying human breast cancer are few, and may represent a limitation for this field of research. With the aim of developing new breast cancer model systems for in vivo studies of hormone dependent and independent tumor growth, progression and invasion, and for in vivo experimental therapy studies, we collected primary mammary tumor specimens from patients, and implanted them in immunodeficient mice. Primary tumor tissue from 29 patients with breast cancer was implanted subcutaneously with matrigel in SCID mice, in the presence of continuous release of estradiol. The tumors were transferred into new animals when reaching a diameter of 15mm and engrafted tumors were harvested for morphological and molecular characterization from passage six. Further, gene expression profiling was performed using Agilent Human Whole Genome Oligo Microarrays, as well as DNA copy number analysis using Agilent Human Genome CGH 244K Microarrays. Of the 30 primary tumors implanted into mice (including two implants from the same patient), two gave rise to viable tumors beyond passage ten. One showed high expression levels of estrogen receptor-alpha protein (ER) while the other was negative. Histopathological evaluation of xenograft tumors was carried out at passage 10-12; both xenografts maintained the morphological characteristics of the original tumors (classified as invasive grade III ductal carcinomas). The genomic profile of the ER-positive xenograft tumor resembled the profile of the primary tumor, while the profile obtained from the ER-negative parental tumor was different from the xenograft. However, the ER-negative parental tumor and xenograft clustered on the same branch using unsupervised hierarchical clustering analysis on RNA microarray expression data of "intrinsic genes". A significant variation was observed in the expression of extracellular matrix (ECM)-related genes, which were found downregulated in the engrafted tumors compared to the primary tumor. By IHC and qRT-PCR we found that the downregulation of stroma-related genes was compensated by the overexpression of such molecules by the mouse host tissue. The two established breast cancer xenograft models showed different histopathological characteristics and profound diversity in gene expression patterns that in part can be associated to their ER status and here described as basal-like and luminal-like phenotype, respectively. These two new breast cancer xenografts represent useful preclinical tools for developing and testing of new therapies and improving our knowledge on breast cancer biology. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc.

Project description:Tumors that express estrogen receptor alpha (ER?+) comprise 75% of breast cancers in women. While treatments directed against this receptor have successfully lowered mortality rates, many primary tumors initially or later exhibit resistance. The paucity of murine models of this "luminal" tumor subtype has hindered studies of factors that promote their pathogenesis and modulate responsiveness to estrogen-directed therapeutics. Since epidemiologic studies closely link prolactin and the development of ER?+ tumors in women, we examined characteristics of the aggressive ER?+ and ER?- carcinomas which develop in response to mammary prolactin in a murine transgenic model (neu-related lipocalin- prolactin (NRL-PRL)). To evaluate their relationship to clinical tumors, we determined phenotypic relationships among these carcinomas, other murine models of breast cancer, and features of luminal tumors in women.We examined a panel of prolactin-induced tumors for characteristics relevant to clinical tumors: histotype, ER?/progesterone receptor (PR) expression and estrogen responsiveness, Activating Protein 1 (AP-1) components, and phosphorylation of signal transducer and activator of transcription 5 (Stat5), extracellular signal regulated kinase (ERK) 1/2 and AKT. We compared levels of transcripts in the ER?-associated "luminal" signature that defines this subtype of tumors in women and transcripts enriched in various mammary epithelial lineages to other well-studied genetically modified murine models of breast cancer. Finally, we used microarray analyses to compare prolactin-induced ER?+ and ER?- tumors, and examined responsiveness to estrogen and the anti-estrogen, Faslodex, in vivo.Prolactin-induced carcinomas were markedly diverse with respect to histotype, ER?/PR expression, and activated signaling cascades. They constituted a heterogeneous, but distinct group of murine mammary tumors, with molecular features of the luminal subtype of human breast cancer. In contrast to morphologically normal and hyperplastic structures in NRL-PRL females, carcinomas were insensitive to ER?-mediated signals. These tumors were distinct from mouse mammary tumor virus (MMTV)-neu tumors, and contained elevated transcripts for factors associated with luminal/alveolar expansion and differentiation, suggesting that they arose from physiologic targets of prolactin. These features were shared by ER?+ and ER?- tumors, suggesting a common origin, although the former exhibited transcript profiles reflecting greater differentiation.Our studies demonstrate that prolactin can promote diverse carcinomas in mice, many of which resemble luminal breast cancers, providing a novel experimental model to examine the pathogenesis, progression and treatment responsiveness of this tumor subtype.

Project description:Hypoxia is linked to disease progression and poor prognosis in several cancers, including breast cancer. Cancer cells can encounter acute, chronic, and/or intermittent periods of oxygen deprivation and it is poorly understood how the different breast cancer subtypes respond to such hypoxia regimes. Here, we assessed the response of representative cell lines for the luminal and basal A subtype to acute (24 h) and chronic hypoxia (5 days). High throughput targeted transcriptomics analysis showed that HIF-related pathways are significantly activated in both subtypes. Indeed, HIF1⍺ nuclear accumulation and activation of the HIF1⍺ target gene CA9 were comparable. Based on the number of differentially expressed genes: (i) 5 days of exposure to hypoxia induced a more profound transcriptional reprogramming than 24 h, and (ii) basal A cells were less affected by acute and chronic hypoxia as compared to luminal cells. Hypoxia-regulated gene networks were identified of which hub genes were associated with worse survival in breast cancer patients. Notably, while chronic hypoxia altered the regulation of the cell cycle in both cell lines, it induced two distinct adaptation programs in these subtypes. Mainly genes controlling central carbon metabolism were affected in the luminal cells whereas genes controlling the cytoskeleton were affected in the basal A cells. In agreement, in response to chronic hypoxia, lactate secretion was more prominently increased in the luminal cell lines which were associated with the upregulation of the GAPDH glycolytic enzyme. This was not observed in the basal A cell lines. In contrast, basal A cells displayed enhanced cell migration associated with more F-actin stress fibers whereas luminal cells did not. Altogether, these data show distinct responses to acute and chronic hypoxia that differ considerably between luminal and basal A cells. This differential adaptation is expected to play a role in the progression of these different breast cancer subtypes.

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Differential in vivo tumorigenicity of distinct subpopulations from a luminal-like breast cancer model

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