Metastatic Prostate Follow Up 2
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ABSTRACT:
PROVIDER: EGAS00001000756 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Validation/deeper sequencing for metastatic prostate cancer samples
| EGAS00001000730 | EGA
Project description:To identify genes with the potential target of differentially expressed miRNA in metastatic prostate cancer, we have employed whole genome microarray expression profiling. Transplantable metastatic versus a non-metastatic prostate cancer xenograft line, both derived from one patient’s primary cancer, were developed via sub-renal capsule grafting of cancer tissue into NOD/SCID mice. The same RNA samples from both lines were also used for miRNA sequencing. Overlapped genes of predicted targets of differentially expressed miRNAs and differentially expressed in microarray platform showed potential markers of combination of miRNA and gene in metastatic prostate cancer. Gene expression in metastatic/non-metastatic prostate cancer was measured. Same total RNA samples were used for small RNA library construction for miRNA sequencing. This submission represents the gene expression component of the study.
2012-03-11 | E-GEOD-28029 | biostudies-arrayexpress
Project description:To identify genes with the potential target of differentially expressed miRNA in metastatic prostate cancer, we have employed whole genome microarray expression profiling. Transplantable metastatic versus a non-metastatic prostate cancer xenograft line, both derived from one patient’s primary cancer, were developed via sub-renal capsule grafting of cancer tissue into NOD/SCID mice. The same RNA samples from both lines were also used for miRNA sequencing. Overlapped genes of predicted targets of differentially expressed miRNAs and differentially expressed in microarray platform showed potential markers of combination of miRNA and gene in metastatic prostate cancer.
2012-03-11 | GSE28029 | GEO
Project description:An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed revealing only 48-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors. Keywords: prostate cancer progression 13 individual benign prostate, primary and metastatic prostate cancer samples and 6 pooled samples from benign,primary or metastatic prostate cancer tissues.
2005-09-20 | E-GEOD-3325 | biostudies-arrayexpress
Project description:Validation/deeper sequencing for metastatic prostate cancer samples
| EGAD00001000989 | EGA
Project description:Validation/deeper sequencing for metastatic prostate cancer samples
| EGAD00001000988 | EGA
Project 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. Keywords: disease state analysis
2007-01-16 | GSE6605 | GEO
Project 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. Experiment Overall Design: 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.
2008-06-15 | E-GEOD-6605 | biostudies-arrayexpress
Project description:Purpose: Prostate cancer most frequently metastasizes to bone and is incurable. Metastatic prostate cancer cells thrive in bone through molecular regulation of surrounding bone stroma; however, it is unclear how non-metastatic vs. metastatic cancer differentially alter the bone cells. Since neutrophils are the most abundant stromal cell in bone, the goal of this study was to identify prostate cancer-induced transcriptomic changes in bone marrow neutrophils for comparison to non-metastatic prostate cancer cells.
2022-08-03 | GSE193468 | GEO
Project description:Many studies have shown that primary prostate cancers are multifocal1-3, and are composed of multiple genetically distinct cancer cell clones4-6. Whether or not multiclonal primary prostate cancers typically give rise to multiclonal or monoclonal prostate cancer metastases is largely unknown, although studies at single chromosomal loci are consistent with the latter. Here we show through a high-resolution genome-wide SNP and copy number survey that most if not all metastatic prostate cancers have monoclonal origins and maintain a unique signature copy number pattern of the parent cancer cell while also accumulating a variable number of separate subclonally sustained changes. We find no relationship between anatomic site of metastasis and genomic copy number change pattern. Taken together with past animal and cytogenetic studies of metastasis7, and recent single-locus genetic data in prostate and other metastatic cancers8-10, it appears that despite common genomic heterogeneity in primary cancers, most metastatic cancers arise from a single precursor cancer cell. Methodologically, this study establishes that genomic archeology of multiple anatomically separate metastatic cancers in individuals can be used to define the salient genomic features of a parent cancer clone of proven lethal metastatic phenotype.
2009-04-12 | GSE14996 | GEO