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GSE46928
Homo sapiens
51 Downloadable Samples
Affymetrix Human Genome U133A Array (hgu133a)
Description
Gene Expression Profiling of Breast Cancer Patients with Brain Metastases Brain metastases confer the worst prognosis of breast cancer as no therapy exists that prevents or eliminates the cancer from spreading to the brain. We developed a new computational modeling method to derive specific downstream signaling pathways that reveal unknown target-disease connections and new mechanisms for specific cancer subtypes. The model enables us to reposition drugs based on available gene expression data of patients. We applied this model to repurpose known or shelved drugs for brain, lung, and bone metastases of breast cancer with the hypothesis that cancer subtypes have their own specific signaling mechanisms. To test the hypothesis, we addressed the specific CSBs for each metastasis that satisfy that (1) CSB proteins are activated by the maximal number of enriched signaling pathways specific to this metastasis, and (2) CSB proteins involve in the most differential expressed coding-genes specific to the specific breast cancer metastasis. The identified signaling networks for the three types of metastases contain 31, 15, and 18 proteins, respectively, and are used to reposition 15, 9, and 2 drug candidates for the brain, lung, and bone metastases of breast cancer. We performed in vitro and in vivo preclinical experiments as well as analysis on patient tumor specimens to evaluate the targets and repositioned drugs. Two known drugs, Sunitinib (FDA approved for renal cell carcinoma and imatinib-resistant gastrointestinal stromal tumor) and Dasatinib (FDA approved for chronic myelogenous leukemia (CML) after imatinib treatment and Philadelphia chromosome-positive acute lymphoblastic leukemia), were shown to prohibit the metastatic colonization in brain.
Publication Title
Novel modeling of cancer cell signaling pathways enables systematic drug repositioning for distinct breast cancer metastases.
Sample Metadata Fields
Time
View Samples- Homo sapiens
- 13 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Myelodysplastic Syndromes (MDSs) are a heterogeneous family of clonal disorders of hematopoietic stem cells characterized by ineffective hematopoiesis and frequently leukemia progression. To exlore how MDS develop into leukemia, we performed the transcriptional profiling of lesional cells and normal lymphoid cells from the MDS patients.
Publication Title
No associated publication
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 503 Downloadable Samples
Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95B Array (hgu95b), Affymetrix Human Genome U95C Array (hgu95c)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.
Sample Metadata Fields
Age, Specimen part, Race
View Samples- Homo sapiens
- 196 Downloadable Samples
- Affymetrix Human Genome U95C Array (hgu95c), Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95B Array (hgu95b)
Description
Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.
Publication Title
Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 181 Downloadable Samples
- Affymetrix Human Genome U95B Array (hgu95b), Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95C Array (hgu95c)
Description
Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.
Publication Title
Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 74 Downloadable Samples
- Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95C Array (hgu95c), Affymetrix Human Genome U95B Array (hgu95b)
Description
Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.
Publication Title
Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 52 Downloadable Samples
- Affymetrix Human Genome U95B Array (hgu95b), Affymetrix Human Genome U95C Array (hgu95c), Affymetrix Human Genome U95A Array (hgu95a)
Description
Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.
Publication Title
Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.
Sample Metadata Fields
Age, Specimen part, Race
View Samples- Homo sapiens
- 20 Downloadable Samples
- Affymetrix Human Genome U95 Version 2 Array (hgu95av2)
Description
Considerable variation in gene expression data from different DNA microarray platforms has been demonstrated. However, no characterization of the source of variation arising from labeling protocols has been performed. To analyze the variation associated with T7-based RNA amplification/labeling methods, aliquots of the Stratagene Human Universal Reference RNA were labeled using 3 eukaryotic target preparation methods and hybridized to a single array type (Affymetrix U95Av2). Variability was measured in yield and size distribution of labeled products, as well as in the gene expression results. All methods showed a shift in cRNA size distribution, when compared to un-amplified mRNA, with a significant increase in short transcripts for methods with long IVT reactions. Intra-method reproducibility showed correlation coefficients >0.99, while inter-method comparisons showed coefficients ranging from 0.94 to 0.98 and a nearly two-fold increase in coefficient of variation. Fold amplification for each method was positively correlated with the number of present genes. Two factors that introduced significant bias in gene expression data were observed: a) number of labeled nucleotides that introduces sequence dependent bias, and b) the length of the IVT reaction that introduces a transcript size dependent bias. This study provides evidence of amplification method dependent biases in gene expression data.
Publication Title
In vitro transcription amplification and labeling methods contribute to the variability of gene expression profiling with DNA microarrays.
Sample Metadata Fields
No sample metadata fields
View Samples- Rattus norvegicus
- 18 Downloadable Samples
- Affymetrix Rat Genome 230 2.0 Array (rat2302)
Description
Heterotopic cardiac transplants were constructed in male Wistar Furth (allograft donor) and ACI (host) rats. Rats were divided into three groups consisting of no treatment, treatment with a sub-therapeutic dose of cyclosporin A, and treated with combination of a sub-therapeutic dose of cyclosporin A and allochimeric peptide. The allografts were harvested at defined periods post-transplantation and RNA was harvested to monitor gene expression changes resulting from the various treatments in T-cells and in heart cells.
Publication Title
Intragraft gene expression profile associated with the induction of tolerance by allochimeric MHC I in the rat heart transplantation model.
Sample Metadata Fields
Sex, Specimen part
View Samples- Mus musculus, Homo sapiens
- 9 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Identical gene regulation patterns of T3 and selective thyroid hormone receptor modulator GC-1.
Sample Metadata Fields
Sex, Age, Specimen part, Cell line
View Samples