EGAS00001000730-sc-20140827 - samples
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ABSTRACT:
PROVIDER: EGAD00001000988 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Validation/deeper sequencing for metastatic prostate cancer samples
| EGAD00001000989 | EGA
Project description:Validation/deeper sequencing for metastatic prostate cancer samples
| EGAS00001000730 | EGA
Project description:Validation/deeper sequencing for metastatic prostate cancer samples
| EGAS00001000756 | EGA
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:We analyzed the protein-coding and non-coding gene expression profiles of 64 samples of prostate cancer primary tumors. All samples were collected between 1998 and 2001 with informed consent from patients subjected to radical prostatectomy at Hospital Sirio-Libanes in São Paulo. Selected patients were identified with clinical Stage T1-2 prostate cancer and no lymph node involvement, and received no adjuvant treatment after surgery as long as they remained recurrence-free. Biochemical recurrence was defined as an increase in patient blood PSA level to 0.2 ng per mL of blood at any time during the 5-year follow-up after prostatectomy. For this kind of experiment, also called self-self hybridization, the microarrays were cohybridized with each of Cy3- and Cy5-labeled cRNA replicates. This strategy has been used to derive intensity-dependent cutoffs to classify a gene as differentially expressed or divergent in comparative genomic hybridization (CGH) studies. The comparative analysis of constant fold change cutoffs and intensity-dependent ones has been extensively discussed, showing a superior performance of the intensity-dependent strategy. For the validation dataset processing, reference values obtained with the training dataset processin were applied to normalize the validation dataset. These values were: Average ranked intensities (quantile normalization), batch information (batch adjustment), and gene average and standard deviations (z-score transformation. Here we describe the validation of the gene expression profile comprised of 32 protein-coding mRNAs and 6 intronic non-coding RNAs (ncRNAs) in an independent set of 22 samples, 16 from recurrence-free patients and 6 recurrent patients. In order to compare the expression levels of training and independent validation samples, gene intensity levels of samples in the validation dataset were transformed using normalization factors that had been generated with the training dataset.
2011-06-15 | E-GEOD-18917 | biostudies-arrayexpress
Project description:We analyzed the protein-coding and non-coding gene expression profiles of 64 samples of prostate cancer primary tumors. All samples were collected between 1998 and 2001 with informed consent from patients subjected to radical prostatectomy at Hospital Sirio-Libanes in São Paulo. Selected patients were identified with clinical Stage T1-2 prostate cancer and no lymph node involvement, and received no adjuvant treatment after surgery as long as they remained recurrence-free. Biochemical recurrence was defined as an increase in patient blood PSA level to 0.2 ng per mL of blood at any time during the 5-year follow-up after prostatectomy. For this kind of experiment, also called self-self hybridization, the microarrays were cohybridized with each of Cy3- and Cy5-labeled cRNA replicates. This strategy has been used to derive intensity-dependent cutoffs to classify a gene as differentially expressed or divergent in comparative genomic hybridization (CGH) studies. The comparative analysis of constant fold change cutoffs and intensity-dependent ones has been extensively discussed, showing a superior performance of the intensity-dependent strategy. For the validation dataset processing, reference values obtained with the training dataset processin were applied to normalize the validation dataset. These values were: Average ranked intensities (quantile normalization), batch information (batch adjustment), and gene average and standard deviations (z-score transformation.
2011-06-15 | GSE18917 | GEO
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:This SuperSeries is composed of the following subset Series: GSE18916: Expression data from 42 prostate cancer samples - 16 recurrent and 26 recurrence-free GSE18917: Expression data from 22 prostate cancer samples - 6 recurrent and 16 recurrence-free from the validation dataset Refer to individual Series
2011-06-15 | E-GEOD-18918 | 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: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-6604 | biostudies-arrayexpress