Expression data from CD133+ and CD133- glioma cells
Ontology highlight
ABSTRACT: Given the very substantial heterogeneity of most human cancers, it is likely that most cancer therapeutics will be active in only a small fraction of any population of patients. As such, the development of new therapeutics, coupled with methods to match a therapy with the individual patient, will be critical to achieving significant gains in disease outcome. One such opportunity is the use of expression signatures to identify key oncogenic phenotypes that can serve not only as biomarkers but also as a means of identifying therapeutic compounds that might specifically target these phenotypes. Given the potential importance of targeting tumors exhibiting a stem-like phenotype, we have developed an expression signature that reflects common biological aspects of various stem-like characteristics. The Consensus Stemness Ranking (CSR) signature is upregulated in cancer stem cell enriched samples, at advanced tumor stages and is associated with poor prognosis in multiple cancer types. Using two independent computational approaches we utilized the CSR signature to identify clinically useful compounds that could target the CSR phenotype. In vitro assays confirmed selectivity of several predicted compounds including topoisomerase inhibitors and resveratrol towards breast cancer cell lines that exhibit a high-CSR phenotype. Importantly, the CSR signature could predict clinical response of breast cancer patients to a neoadjuvant regimen that included a CSR-specific agent. Collectively, these results suggest therapeutic opportunities to target the CSR phenotype in a relevant cohort of cancer patients. CD133+ and CD133- cells were separated from two glioma xenograft tumors. Both CD133+ and CD133- glioma cells were cultured in serum-free media for 48 hours in the presence of absence of laminin.
Project description:Given the very substantial heterogeneity of most human cancers, it is likely that most cancer therapeutics will be active in only a small fraction of any population of patients. As such, the development of new therapeutics, coupled with methods to match a therapy with the individual patient, will be critical to achieving significant gains in disease outcome. One such opportunity is the use of expression signatures to identify key oncogenic phenotypes that can serve not only as biomarkers but also as a means of identifying therapeutic compounds that might specifically target these phenotypes. Given the potential importance of targeting tumors exhibiting a stem-like phenotype, we have developed an expression signature that reflects common biological aspects of various stem-like characteristics. The Consensus Stemness Ranking (CSR) signature is upregulated in cancer stem cell enriched samples, at advanced tumor stages and is associated with poor prognosis in multiple cancer types. Using two independent computational approaches we utilized the CSR signature to identify clinically useful compounds that could target the CSR phenotype. In vitro assays confirmed selectivity of several predicted compounds including topoisomerase inhibitors and resveratrol towards breast cancer cell lines that exhibit a high-CSR phenotype. Importantly, the CSR signature could predict clinical response of breast cancer patients to a neoadjuvant regimen that included a CSR-specific agent. Collectively, these results suggest therapeutic opportunities to target the CSR phenotype in a relevant cohort of cancer patients. Refer to individual Series. This SuperSeries is composed of the following subset Series: GSE24578: Basal gene expression of breast cancer cell lines GSE24716: Expression data from CD133+ and CD133- glioma cells
Project description:Given the very substantial heterogeneity of most human cancers, it is likely that most cancer therapeutics will be active in only a small fraction of any population of patients. As such, the development of new therapeutics, coupled with methods to match a therapy with the individual patient, will be critical to achieving significant gains in disease outcome. One such opportunity is the use of expression signatures to identify key oncogenic phenotypes that can serve not only as biomarkers but also as a means of identifying therapeutic compounds that might specifically target these phenotypes. Given the potential importance of targeting tumors exhibiting a stem-like phenotype, we have developed an expression signature that reflects common biological aspects of various stem-like characteristics. The Consensus Stemness Ranking (CSR) signature is upregulated in cancer stem cell enriched samples, at advanced tumor stages and is associated with poor prognosis in multiple cancer types. Using two independent computational approaches we utilized the CSR signature to identify clinically useful compounds that could target the CSR phenotype. In vitro assays confirmed selectivity of several predicted compounds including topoisomerase inhibitors and resveratrol towards breast cancer cell lines that exhibit a high-CSR phenotype. Importantly, the CSR signature could predict clinical response of breast cancer patients to a neoadjuvant regimen that included a CSR-specific agent. Collectively, these results suggest therapeutic opportunities to target the CSR phenotype in a relevant cohort of cancer patients.
Project description:CD133 has been widely used for identification and isolation of cancer stem cells in tumors although its role as a marker for cancer stem cell is still controversial . We isolated the CD133+ and CD133- cells from SW620 human colon cancer cell line and compared their biological characteristics, such as tumorigenicity,drug sensitivity, etc. Our study revealed that CD133+ SW620 cells were more tumorigenic and resistant to anti-cancer drugs. Correspondingly, they displayed different gene expression profile. However, it was observed that CD133- cells and CD133+ cells could mutually convert, indicating that CD133 expression was under dynamic and reversible regulations which might impose significant infulence on cells behaviors. Thus, our data challenge the role of CD133 as a marker for cancer stem cell. There are two populations with distinct expression of CD133 in SW620 human colon cancer cell line. Microarray assays were employed to investigate the differentially expressed genes between the two populations, which may possess different tumorigenetic potential and sensitivity to anti-cancer drugs. CD133+ and CD133- cells were isolated from human colon cancer SW620 cell line by magnetic cell sorting system. The clones from sorted CD133+ or CD133- populations were established. Clone cells were expanded and were further purified by using CD133 cell isolation kit before microarray assays.
Project description:Given the very substantial heterogeneity of most human cancers, it is likely that most cancer therapeutics will be active in only a small fraction of any population of patients. As such, the development of new therapeutics, coupled with methods to match a therapy with the individual patient, will be critical to achieving significant gains in disease outcome. One such opportunity is the use of expression signatures to identify key oncogenic phenotypes that can serve not only as biomarkers but also as a means of identifying therapeutic compounds that might specifically target these phenotypes. Given the potential importance of targeting tumors exhibiting a stem-like phenotype, we have developed an expression signature that reflects common biological aspects of various stem-like characteristics. The Consensus Stemness Ranking (CSR) signature is upregulated in cancer stem cell enriched samples, at advanced tumor stages and is associated with poor prognosis in multiple cancer types. Using two independent computational approaches we utilized the CSR signature to identify clinically useful compounds that could target the CSR phenotype. In vitro assays confirmed selectivity of several predicted compounds including topoisomerase inhibitors and resveratrol towards breast cancer cell lines that exhibit a high-CSR phenotype. Importantly, the CSR signature could predict clinical response of breast cancer patients to a neoadjuvant regimen that included a CSR-specific agent. Collectively, these results suggest therapeutic opportunities to target the CSR phenotype in a relevant cohort of cancer patients. This SuperSeries is composed of the SubSeries listed below.
Project description:Given the very substantial heterogeneity of most human cancers, it is likely that most cancer therapeutics will be active in only a small fraction of any population of patients. As such, the development of new therapeutics, coupled with methods to match a therapy with the individual patient, will be critical to achieving significant gains in disease outcome. One such opportunity is the use of expression signatures to identify key oncogenic phenotypes that can serve not only as biomarkers but also as a means of identifying therapeutic compounds that might specifically target these phenotypes. Given the potential importance of targeting tumors exhibiting a stem-like phenotype, we have developed an expression signature that reflects common biological aspects of various stem-like characteristics. The Consensus Stemness Ranking (CSR) signature is upregulated in cancer stem cell enriched samples, at advanced tumor stages and is associated with poor prognosis in multiple cancer types. Using two independent computational approaches we utilized the CSR signature to identify clinically useful compounds that could target the CSR phenotype. In vitro assays confirmed selectivity of several predicted compounds including topoisomerase inhibitors and resveratrol towards breast cancer cell lines that exhibit a high-CSR phenotype. Importantly, the CSR signature could predict clinical response of breast cancer patients to a neoadjuvant regimen that included a CSR-specific agent. Collectively, these results suggest therapeutic opportunities to target the CSR phenotype in a relevant cohort of cancer patients.
Project description:As many other tumors, a subset of gliobastoma is thought to be maintained by a restricted population of cancer cells, stem-like cells that express CD133 transmembrane protein. Expression levels of CD133 gene has been linked to a poor prognostic molecular subgroup and is not overexpressed by the PDGF-driven proneural group. Thus, the significance of CD133+ cells for gliomagenesis of the proneural group is undetermined. In addition, the role of the CD133 protein remains elusive and controversial, which results from the difficult isolation of CD133+ cells that has largely relied on the use of antibodies to ill-defined glycosylated epitopes of CD133. Here, we used a knockin lacZ reporter mouse, Prom1lacZ/+, to track Prom1+ cells in the brain and found that Prom1 (prominin1, murine CD133 homologue) is expressed by cells that co-express markers characteristic of neuronal, glial and vascular lineage phenotype. In proneural tumors derived from injection of RCAS-PDGF into the brain of tv-a;Ink4a-Arf-/- Prom1lacZ/+ mice, Prom1+ cells co-express markers for astrocytes and endothelial cells. Therefore, we characterize the tumor propagation in a murine model and found that the mice co-transplanted with Prom1 endothelium and proneural tumor spheres cells had significant tumor burden and vascular proliferation (angiogenesis). Specific genes in Prom1 endothelium are identified that code for endothelial signaling modulators that most likely support proneural tumor progression and can be potential targets for anti-angiogenic therapy. Cells were sorted via FACS to obtain a population of CD31+CD133- cells and a population of CD31+CD133+ cells. Total RNA was extracted from each population and gene expression was assayed on Affymetrix Mouse 430 2.0 arrays with one array per cell population.
Project description:To identify candidate genes involved in enhanced tumorigenicity of CD133+ liver tumor-initiating cells Affymetrix Human Genome U133 Plus GeneChip 2.0 HCC cell line Huh7 was sorted into CD133+ and CD133- populations by flow cytometry
Project description:To identify candidate genes involved in enhanced tumorigenicity of CD133+ liver tumor-initiating cells Affymetrix Human Genome U133 Plus GeneChip 2.0 HCC cell line PLC8024 was sorted into CD133+ and CD133- populations by flow cytometry
Project description:Cancer stem cells (CSCs) that display tumor-initiating properties have recently been identified. We herein identify and characterize CSCs in human uterine carcinosarcoma, a highly aggressive and therapy-resistant gynecologic malignancy, which is considered to be of mesodermal origin. FU-MMT-1, a cell-line, which was established by us (Emoto M, Cancer 1992) from a patient with uterine carcinosarcoma, was evaluated. FU-MMT-1 contained a high population of CD133, CD44, CD90, and CD29 positive cells. Using the magnetic bead cell separation method, we isolated CD133+ cells, which predominantly form spheres in culture. These CD133+ cells form transplantable tumors in vivo. A qRT-PCR analysis of the genes implicated in stem cell maintenance revealed that CD133+ cells express significantly higher levels of OCT4, NANOG, and BMI-1 than CD133M-oM-<M- cells. Moreover, CD133+ cells showed a high expression of PAX2 and WNT4, which are the essential genes in Mullerian duct formation. The tumor derived from CD133+ cells replicated vimentin, ERM-NM-1, ERM-NM-2, and PR expressionsM-cM-^@M-^@of the parent tumor. These findings suggest that CD133+ FU-MMT-1 cells have the characteristics of CSCs and Mullerian mesenchymal progenitors. CD133+ and CD133- population of FU-MMT-1 cells were analyzed by microarray.
Project description:Expression from CD133+ cells isolated from adult human exocrine tissue was compared to a CD133-depleted cell population Islet-depleted exocrine tissue from three independent adult human cadaveric pancreata were cultured for four days in Miami media 1A. Following trypsinization, cells were isolated using anti-CD133 immunomagnetic beads to >95% CD133+. CD133-negative cells were further depleted of CD133+ cells to <1% CD133+.