Expression profiling of 22Rv1, DU145, LNCaP and PC3 prostasphere cultures at day 0, 4, 8 and 12
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Roberto Portillo Lara
PROVIDER: E-GEOD-77615 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
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.
2016-02-06 | E-GEOD-77612 | biostudies-arrayexpress
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.
2016-02-06 | E-GEOD-77614 | biostudies-arrayexpress
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.
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Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
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