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GSE22483
Homo sapiens
6 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Treatment of late passage (LP50) LNCaP cells with R1881 (androgen) and AR shRNA identified a gene program controlled by androgen receptor in the absence of androgen.
Publication Title
Hormone depletion-insensitivity of prostate cancer cells is supported by the AR without binding to classical response elements.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 30 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Using gene expression profiling we characterize the global effect of p53 on the TLR5-mediated transcription in MCF7 cells. We found that combined activation of p53 and TLR5 pathways synergistically increases expression of over 200 genes, mostly associated with immunity and inflammation. The synergy was observed in several human cancer cells and primary lymphocytes.
Publication Title
p53 amplifies Toll-like receptor 5 response in human primary and cancer cells through interaction with multiple signal transduction pathways.
Sample Metadata Fields
Cell line
View Samples- Drosophila melanogaster
- 8 Downloadable Samples
Illumina HiSeq 2000
Description
Heterochromatic position effect variegation (PEV) is the epigenetic disruption of genes expression near the new-formed eu-heterochromatic border. We characterized the inversion In(2)A4, demonstrating cis-acting PEV as well as trans-inactivation of the reporter transgenes on the opposite normal chromosome in combination with the inversion. Euchromatic breakpoint of In(2)A4 inversion was localized at 105 bp region (chr2L:21182214-21182318) of the second exon of the Mcm10 gene, the heterochromatic breakpoint is located at the block of dodecasatellite in 2L pericentromeric heterochromatin. In order to check the effects of heterochromatin on neighbor euchromatic genes and estimate the distance of inactivation spreading, we performed RNA-seq analysis of genes expression in larvae and adults females of genotypes A12/A12 (control) and In(2)A4/In(2)A4. Cis-influence of heterochromatin in the inversion causes not only repression, but also activation of genes, and the effects of heterochromatin are different at different developmental stages. Cis-actions affect only a few genes located near the heterochromatin Overall design: Comparison of genes expression in wild type and demonstrating PEV larvae and adults in two repeats each
Publication Title
Trans-inactivation: Repression in a wrong place.
Sample Metadata Fields
Sex, Subject
View Samples- Homo sapiens
- 36 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
E2F1 induces numerous genes, including transcription factors, upon activation. The transcription factors then further cooperates with E2F1 to regulate the target genes and enhance the transcriptional effect.
Publication Title
E2F1-Mediated Induction of NFYB Attenuates Apoptosis via Joint Regulation of a Pro-Survival Transcriptional Program.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 14 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
Effect of FOXO knockdown on E2F1-mediated transcription
Publication Title
FOXO transcription factors control E2F1 transcriptional specificity and apoptotic function.
Sample Metadata Fields
Specimen part, Cell line, Treatment
View Samples- Homo sapiens
- 24 Downloadable Samples
Affymetrix Human Genome U133A 2.0 Array (hgu133a2), Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
PrtT-regulated proteins secreted by Aspergillus fumigatus activate MAPK signaling in exposed A549 lung cells leading to necrotic cell death.
Sample Metadata Fields
Specimen part, Cell line, Treatment
View Samples- Homo sapiens
- 22 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
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.
Publication Title
Using a stem cell-based signature to guide therapeutic selection in cancer.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 14 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
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.
Publication Title
Using a stem cell-based signature to guide therapeutic selection in cancer.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 9 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2), Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Response of A549 cells treated with Aspergillus fumigatus wild type germinating conidia (WT_GC) or PrtT protease deficient mutant conidia (PrtT-GC) or inert acrylic 2-4 micron beads (Beads) for 8h
Publication Title
PrtT-regulated proteins secreted by Aspergillus fumigatus activate MAPK signaling in exposed A549 lung cells leading to necrotic cell death.
Sample Metadata Fields
Specimen part, Cell line, Treatment
View Samples- Homo sapiens
- 8 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
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.
Publication Title
Using a stem cell-based signature to guide therapeutic selection in cancer.
Sample Metadata Fields
Specimen part
View Samples