Project description:Cancer stem cells (CSCs) drive prostate cancer (PCa) progression and metastasis. These cells exhibit remarkable self-renewal, chemoresistant and invasive potentials, and are thought to participate in the changes in cellular architecture that lead to epithelial-to-mesenchymal transition (EMT). Conventional therapies fail to eliminate CSCs, which results in tumor recurrence and progression to castration resistant PCa (CRPC). Recent evidence suggests that castration itself can induce EMT, which could potentiate the â??stemnessâ?? and number of CSCs within the tumor. Hence, there is an urgent need for EMT- and CSC-targeted therapies that could prevent progression to CRPC. 22Rv1, DU145, LNCaP, and PC3 cells were grown under sphere-forming conditions standardized in our lab. We have previously demonstrated that these enriched PCa cell lines exhibit phenotypic characteristics associated with CSCs in vivo. Over-expression of the stem-associated CD133 biomarker was determined via flow cytometric analysis. Total RNA was isolated from CD133+ prostasphere-derived cells. Gene expression profiling was carried out using the nCounter NanoString system and three different CodeSets associated with cancer or stem cells. Functional annotation was performed using the over-representation analysis tool from ConsensusPathDB. Functional annotation analysis of upregulated transcripts suggests that prostasphere-derived cells undergo a transcriptional reprogramming that triggers a major phenotypic shift. These changes are similar to the mesenchymal shift associated with EMT that drives PCa progression to CRPC. Each cell line exhibited distinct expression profiles that are presented and analyzed individually. Furthermore, our analysis revealed over-represented pathways that were common to all cell lines, which are related to the MAPK/ERK, PI3K/AKT, Notch, and Wnt stem cell fate signaling networks. Transcriptional analysis of induced CSCs not only offers insight into their underlying pathophysiology, but can also be used as a platform for the discovery of therapeutic targets for CSC-specific intervention. In this contribution, we present a flexible in vitro platform for the identification of functionally relevant therapeutic targets, using cell samples with low numbers of malignant stem/progenitors that were enriched in vitro. This approach represents a novel and effective strategy that can be used in the development of therapeutic strategies, which could ultimately be tailored to the biology of individual patients. 22Rv1, DU145, LNCaP and PC3 prostasphere cultures were sampled on Day 4 (P 2), Day 8 (P 3) and Day 12 (P 4), and compared relative to parental monolayers on Day 0 of culture (P 1). Three independent measurements were carried out for monolayers at Day 0 using the CancerReference Kit. Day 12 prostaspheres were enzymatically dissociated and sorted via MACS using the Anti-CD133/2 (293C3)-PE Antibody (Miltenyi) into CD133+ and CD133- fractions. Total RNA was extracted from CD133+ cells and analyzed using the nCounter GX Cancer Reference kit, the Stem Cell panel and the custom made ITESM CodeSet from NanoString Technologies. This series contains the Cancer Reference kit data.

Project description:Cancer stem cells (CSCs) drive prostate cancer (PCa) progression and metastasis. These cells exhibit remarkable self-renewal, chemoresistant and invasive potentials, and are thought to participate in the changes in cellular architecture that lead to epithelial-to-mesenchymal transition (EMT). Conventional therapies fail to eliminate CSCs, which results in tumor recurrence and progression to castration resistant PCa (CRPC). Recent evidence suggests that castration itself can induce EMT, which could potentiate the âstemnessâ and number of CSCs within the tumor. Hence, there is an urgent need for EMT- and CSC-targeted therapies that could prevent progression to CRPC. 22Rv1, DU145, LNCaP, and PC3 cells were grown under sphere-forming conditions standardized in our lab. We have previously demonstrated that these enriched PCa cell lines exhibit phenotypic characteristics associated with CSCs in vivo. Over-expression of the stem-associated CD133 biomarker was determined via flow cytometric analysis. Total RNA was isolated from CD133+ prostasphere-derived cells. Gene expression profiling was carried out using the nCounter NanoString system and three different CodeSets associated with cancer or stem cells. Functional annotation was performed using the over-representation analysis tool from ConsensusPathDB. Functional annotation analysis of upregulated transcripts suggests that prostasphere-derived cells undergo a transcriptional reprogramming that triggers a major phenotypic shift. These changes are similar to the mesenchymal shift associated with EMT that drives PCa progression to CRPC. Each cell line exhibited distinct expression profiles that are presented and analyzed individually. Furthermore, our analysis revealed over-represented pathways that were common to all cell lines, which are related to the MAPK/ERK, PI3K/AKT, Notch, and Wnt stem cell fate signaling networks. Transcriptional analysis of induced CSCs not only offers insight into their underlying pathophysiology, but can also be used as a platform for the discovery of therapeutic targets for CSC-specific intervention. In this contribution, we present a flexible in vitro platform for the identification of functionally relevant therapeutic targets, using cell samples with low numbers of malignant stem/progenitors that were enriched in vitro. This approach represents a novel and effective strategy that can be used in the development of therapeutic strategies, which could ultimately be tailored to the biology of individual patients. 22Rv1, DU145, LNCaP and PC3 prostasphere cultures were sampled on Day 4 (P 2), Day 8 (P 3) and Day 12 (P 4), and compared relative to parental monolayers on Day 0 of culture (P 1). Three independent measurements were carried out for monolayers at Day 0 using the CancerReference Kit. were sampled Day 12 prostaspheres were enzymatically dissociated and sorted via MACS using the Anti-CD133/2 (293C3)-PE Antibody (Miltenyi) into CD133+ and CD133- fractions. Total RNA was extracted from CD133+ cells and analyzed using the nCounter GX Cancer Reference kit, the Stem Cell panel and the custom made ITESM CodeSet from NanoString Technologies. This series contains data for the ITESM CodeSet.

Project description:Cancer stem cells (CSCs) drive prostate cancer (PCa) progression and metastasis. These cells exhibit remarkable self-renewal, chemoresistant and invasive potentials, and are thought to participate in the changes in cellular architecture that lead to epithelial-to-mesenchymal transition (EMT). Conventional therapies fail to eliminate CSCs, which results in tumor recurrence and progression to castration resistant PCa (CRPC). Recent evidence suggests that castration itself can induce EMT, which could potentiate the âstemnessâ and number of CSCs within the tumor. Hence, there is an urgent need for EMT- and CSC-targeted therapies that could prevent progression to CRPC. 22Rv1, DU145, LNCaP, and PC3 cells were grown under sphere-forming conditions standardized in our lab. We have previously demonstrated that these enriched PCa cell lines exhibit phenotypic characteristics associated with CSCs in vivo. Over-expression of the stem-associated CD133 biomarker was determined via flow cytometric analysis. Total RNA was isolated from CD133+ prostasphere-derived cells. Gene expression profiling was carried out using the nCounter NanoString system and three different CodeSets associated with cancer or stem cells. Functional annotation was performed using the over-representation analysis tool from ConsensusPathDB. Functional annotation analysis of upregulated transcripts suggests that prostasphere-derived cells undergo a transcriptional reprogramming that triggers a major phenotypic shift. These changes are similar to the mesenchymal shift associated with EMT that drives PCa progression to CRPC. Each cell line exhibited distinct expression profiles that are presented and analyzed individually. Furthermore, our analysis revealed over-represented pathways that were common to all cell lines, which are related to the MAPK/ERK, PI3K/AKT, Notch, and Wnt stem cell fate signaling networks. Transcriptional analysis of induced CSCs not only offers insight into their underlying pathophysiology, but can also be used as a platform for the discovery of therapeutic targets for CSC-specific intervention. In this contribution, we present a flexible in vitro platform for the identification of functionally relevant therapeutic targets, using cell samples with low numbers of malignant stem/progenitors that were enriched in vitro. This approach represents a novel and effective strategy that can be used in the development of therapeutic strategies, which could ultimately be tailored to the biology of individual patients. 22Rv1, DU145, LNCaP and PC3 prostasphere cultures were sampled on Day 4 (P 2), Day 8 (P 3) and Day 12 (P 4), and compared relative to parental monolayers on Day 0 of culture (P 1). Three independent measurements were carried out for monolayers at Day 0 using the CancerReference Kit. Day 12 prostaspheres were enzymatically dissociated and sorted via MACS using the Anti-CD133/2 (293C3)-PE Antibody (Miltenyi) into CD133+ and CD133- fractions. Total RNA was extracted from CD133+ cells and were analyzed using the nCounter GX Cancer Reference kit, the Stem Cell panel and the custom made ITESM CodeSet (14 genes associated with prostate cancer) from NanoString Technologies. This series contains data for the Stem Cell panel.

Project description:Background - Hepatocellular carcinomas (HCCs) are heterogeneous tumors with respect to etiology, cell of origin and biology. The course of the disease is unpredictable and is in part dependent on the tumor microenvironment. One of the microenvironmental factors is hypoxia, which is known to promote aggressiveness in other malignant tumors. We hypothesized that certain regions in HCC exist with chronic hypoxia and a characteristic gene expression pattern. Moreover, during the development of HCC there is an important contribution of this chronic hypoxia on prognosis via this gene expression. Until now, most research has been performed in acute hypoxic models (< 24 hours). Methods – Human hepatoblastoma cells HepG2 were cultured in either normoxic (20% O2) or hypoxic (2% O2) conditions for 72 hrs, the time it takes to adapt to chronic hypoxia. After 3 days the cells were harvested and analyzed by microarray technology. The highly significant differentially expressed genes were selected and used to assess the clinical value of our in vitro chronic hypoxia gene signature in four published patient studies. Three of these independent microarray studies on HCC patients were used as training sets to determine a minimal prognostic gene set and one study was used for validation. Gene expression analysis and correlation with clinical outcome was assessed with the bioinfomatic method of Goeman et al (). Results – In the HepG2 cells, 3592 genes were differentially expressed in cells cultured at 2% oxygen for 72 hrs. Out of these, 265 showed a high significant change (2-fold change and p=0.0001). The level of gene expression after 72 hrs was different from the acute hypoxic response (during the first 24 hours) and represented chronicity. Using computational methods we identified 7 out of the 265 highly significant genes that showed correlation with prognosis in all three different training sets and this was independently validated in a 4th dataset. With our approach we could include the largest number of HCC patients in one single study. Conclusion – We identified a 7-gene signature, which is associated with chronic hypoxia and predicts prognosis in patients with HCC. In the future this signature could be used as a diagnostic tool. In addition, chronic hypoxia gene expression information can be used in the search for new therapeutic targets. Two conditions were compared and each sample has a biological replicate. Samples are hybridized in dye-swap, resulting in 4 hybridizations.

Project description:Studies of normal human mammary gland development and function have mostly relied on cell culture, limited surgical specimens, and rodent models. Although RNA extracted from human milk has been used to assay the mammary transcriptome non-invasively, the transcriptome derived from the milk fat layer has not been compared with the mammary-derived transcriptome nor have sources of RNA been quantified in milk. In this study the effects of milk collection and processing on RNA quality and origin were assessed in humans and rhesus macaques. Total RNA in milk was quantitated in acridine orange-stained milk using an automated whole slide scanner and custom-built Globulator software. Total RNA extracted from milk fat, cells in milk, and mammary biopsies of lactating rhesus macaques were compared using RNA sequencing and analysis. Compared with human milk, milk from macaques contained similar amounts of RNA-containing cytoplasmic crescents, but more cells. Total RNA extracted from milk fractions was also evaluated for factors that affect RNA quality. Degradation of RNA extracted from human milk fat was positively correlated with geographic distance from collection site, storage time, and sample type. There were no differences in RNA degradation in macaque milk collected after 10 min or 4 hr accumulation, suggesting that degradation of RNA extracted from milk fat may not occur in the mammary gland. Using RNA-Seq, RNA extracted from macaque milk fat and cells in milk more accurately represented RNA from mammary epithelial cells (cells that produce milk) than did RNA from mammary tissue. Mammary epithelium-specific transcripts were more abundant in macaque milk fat whereas adipose or stroma-specific transcripts were more abundant in mammary tissue. Functional analyses confirmed the validity of milk as a source of RNA from mammary epithelial cells. Analysis of highly abundant putative microRNAs in macaque milk fat revealed a potentially novel non-coding RNA species that is conserved in humans. RNA extracted from the milk fat during lactation accurately portrayed the RNA profile of milk-producing mammary epithelial cells. However, this sample type clearly requires protocols that minimize RNA degradation. Transcript profiles from milk cells, milk fat, and mammary tissue from 6 lactating rhesus macaques at 30 and 90 days lactation; 34 samples run in triplicate

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