Using a Stem Cell-Based Signature to Guide Therapeutic Selection in Cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Joseph Nevins
PROVIDER: E-GEOD-24717 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
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. 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.
2010-10-16 | E-GEOD-24716 | biostudies-arrayexpress
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.
2010-10-08 | GSE24578 | GEO
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.
2010-10-16 | GSE24717 | GEO
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.
2010-10-16 | GSE24716 | GEO
Project description:To demonstrate CD133+CD44+ and CD133+CD44- subpopulations of hepatocellular carcinoma as distinct subgroups, we have employed whole genome microarray expression profiling as a discovery platform to reveal the gene profiles of different subgroups and identify genes responsible for the enhanced metastatic potentials of CD133+CD44+ tumor cells. CD133+CD44+ and CD133+CD44- tumor cells were isolated from three human metastatic hepatocellular carcinoma specimens. A 76-gene consensus signature was identified that distinguished between CD133+CD44+ and CD133+CD44- subgroups. CD133+CD44+ and CD133+CD44- subgroups from different patients were well clustered as two distinct classes according to this signature, and many genes in this signature were reported involved in tumor metastasis. Expression of four genes (CCL4, DKK3, CCR5 and MMP12) from this signature was confirmed in another three metastatic HCC specimens by real-time PCR. CD133+CD44+ and CD133+CD44- subpopulations of hepatocellular carcinoma were isolated from three metastatic hepatocellular carcinoma specimens by flow cytometry. A total of 30K to 50K cells for each subgroup was obtained for each microarray.
2010-12-28 | E-GEOD-26321 | biostudies-arrayexpress
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.
2010-07-29 | E-GEOD-23295 | biostudies-arrayexpress
Project description:Nine heterogeneous melanoma cell lines including D10 and WM115 were studied for cancer stem cell characteristics in vitro. D10 cell line was the only cell line expressing the cancer stem cell marker CD133. Thus, gene expression profiling on CD133+ and CD133- D10 cells was carried out using Affymetrix GeneChips Human Genome U133A 2.0.
2013-01-17 | E-MEXP-3542 | biostudies-arrayexpress
Project description:BACKGROUND: Several in vitro assays have been used to identify “cancer stem cells” (CSC), including expression of cell surface markers and Hoechst dye efflux properties. However, each of these methods has potential pitfalls that complicate interpretation of the results. Focusing on colon cancers (CC), the CD133 antigen has been proposed as a marker of colon CSC. However, conflicting results have been reported in the literature indicating the need of a systematic analysis of CSC within CC and a complete validation of markers for the isolation of these cells. AIMS: Aim of this study was to confirm that CD133 expression is a valid method for isolating CSC in CC and verify if other antigens can increase the specificity of this marker for isolating CSC in CC. METHODS: CD133+ and CD133- cells were isolated from different human CC lines (CaCo-2, HT29, LOVO, HCT-116) by FACS sorter and the tumor-initiating potential of CD133+ cells was assessed in vitro, by soft-agar colony formation assay, and in vivo, upon transplantation into nude mice. Furthermore, the gene expression profile of CD133+ versus CD133- CaCo-2 cells was compared by the means of microarray analysis. Then, in the effort to identify a common “tumor stem cell” signature for CC, the most relevant transcripts resulting from gene expression profiling on CD133+ cells was assessed by real-time PCR on SP-fraction isolated by FACS sorter from the same CC cell lines. Finally, we deplete CD133 expression in the CaCo-2 cell line by the means of siRNA and verified by Western Blot analysis whether there was a functional correlation between CD133 and the target genes. Moreover, CaCo-2 and HCT116 cells were exposed to sodium butyrate (NaBu) for 72h. Colon cells differentiation was assessed by Alkaline phosphatase activity and expression of CD133 and target genes was tested by western blot. RESULTS: We confirmed that only CD133+ cells have a tumor-initiating potential in vitro and in vivo. Furthermore, microarray analysis of CD133+ versus CD133- CaCo-2 cells revealed a significant overexpression of various transcripts involved in cell proliferation, invasion and stemness in CD133+ cell fraction. Comparison of the transcripts by real-time PCR revealed that the genes of Endothelin-1 (END-1) and NR4A2 are highly expressed in both CD133 + cells and in SP fractions. Finally, when we deplete CD133 expression in Caco-2cells by siRNA, we observed a significant attenuation of END-1 and NR4A2 expression, thus demonstrating that CD133 is involved in the transcriptional regulation of these genes. Interestingly, we also showed that the expression of all three genes was inversely correlated with cell differentiation status as demonstrated by the fact that their expression decreases in a time- and dose-dependent manner after differentiation induced by NaBu. CONCLUSION: Overall, this study confirms the role of CD133antigen as CSC marker and showed for the first time the existence of a functional relationship between CD133, END-1 and NR4A2 expression, hypothesizing that CD133 is involved in the transcriptional regulation of these gene. Microarray analysis was performed on CD133+ and CD133- sorted CACO-2 cells. For both fractions, cells were sorted three independent times. Sample preparation was performed according to Affymetrix recommendations. A total of 6 arrays were hybridized, including 3 CD133+ replicates and 3 CD133- replicates.
2011-01-04 | E-GEOD-24747 | biostudies-arrayexpress
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.
2013-12-31 | E-GEOD-43931 | biostudies-arrayexpress
Project description:Advanced colon cancer is characterized by drug resistance and a poor prognosis. In these patients tumor-propagating cells appear to be largely resistant against various targeted drugs including ErbB-inhibitors. The cell surface antigen prominin-1 (CD133) has recently been identified as a potential marker of colon cancer stem cells. The purpose of this study was to define mRNA expression patterns in CD133+ and CD133- HCT116 cells. To define mRNA expression patterns in CD133+ and CD133- HCT116 cells, gene array analysis were performed using genome-wide human U133 2.0 plus GeneChips (Affymetrix, Santa Clara, CA, USA). 3 repetitions of CD133+ HCT116 cells and 3 repetitions of CD133- HCT116 cells were performed. Robust Multichip Average (RMA) signal extraction and normalization were performed.
2012-05-21 | E-GEOD-38049 | biostudies-arrayexpress