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Alterations in chromosome spatial compartmentalization classify prostate cancer progression [array]

ABSTRACT: Through a systematic analysis of chromosome conformation capture in a cohort of cells that model cancer progression, San Martin et.al. find that rearrangement of the 3D genome structure in prostate cancer is a potential mechanism for disease exacerbation and that genome-wide compartment identity can classify cancer according to progression

ORGANISM(S): Homo sapiens

PROVIDER: GSE172098 | GEO | 2021/05/01

REPOSITORIES: GEO

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Alterations in chromosome spatial compartmentalization classify prostate cancer progression [Hi-C]

Project description:Through a systematic analysis of chromosome conformation capture in a cohort of cells that model cancer progression, San Martin et.al. find that rearrangement of the 3D genome structure in prostate cancer is a potential mechanism for disease exacerbation and that genome-wide compartment identity can classify cancer according to progression

2021-05-01 | GSE172097 | GEO

Alterations in chromosome spatial compartmentalization classify prostate cancer progression.

Project description:Alterations in chromosome spatial compartmentalization classify prostate cancer progression.

| PRJNA722007 | ENA

Alterations in chromosome spatial compartmentalization classify prostate cancer progression [array]

Project description:Alterations in chromosome spatial compartmentalization classify prostate cancer progression [array]

| PRJNA722012 | ENA

Alterations in chromosome spatial compartmentalization classify prostate cancer progression [Hi-C]

Project description:Alterations in chromosome spatial compartmentalization classify prostate cancer progression [Hi-C]

| PRJNA722011 | ENA

Alterations in chromosome spatial compartmentalization classify prostate cancer progression.

Project description:This SuperSeries is composed of the SubSeries listed below.

2021-05-01 | GSE172099 | GEO

Transcription profiling of mouse transgenic tumors driven by Her or Ras

Project description:previously published mouse data; Pubmed IDS: 12754511, 12839964 Experiment Overall Design: see Black, EP, et.al., Cancer Res. 2003 Jul 1;63(13):3716-23 and Huang, E., et.al. Nat Genet. 2003 Jun;34(2):226-30.

2008-06-12 | E-GEOD-3158 | biostudies-arrayexpress

Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets

Project description:Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets

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Transcription profiling of human growing breast cancer cell lines

Project description:Gene expression analysis on growing breast cancer cell lines. Experiment Overall Design: see Bild, A. et.al.

2008-06-12 | E-GEOD-3156 | biostudies-arrayexpress

Integration of metabolic activation with a predictive toxicogenomics signature to classify genotoxic versus nongenotoxic chemicals in human TK6 cells

Project description:The use of integrated approaches in genetic toxicology, including the incorporation of gene expression data to determine the molecular pathways involved in the response, is becoming more common. In a companion paper, a genomic biomarker was developed in human TK6 cells to classify chemicals as genotoxic or non-genotoxic. Because TK6 cells are not metabolically competent, we set out to broaden the utility of the biomarker for use with chemicals requiring metabolic activation. Specifically, chemical exposures were conducted in the presence of rat liver S9. The ability of the biomarker to classify genotoxic (benzo[a]pyrene, BaP; aflatoxin B1, AFB1) and non-genotoxic (dexamethasone, DEX; phenobarbital, PB) agents correctly was evaluated. Cells were exposed to increasing chemical concentrations for 4h and collected 0h, 4h and 20h post-exposure. Relative survival, apoptosis, and micronucleus frequency were measured at 24h. Transcriptome profiles were measured with Agilent microarrays. Statistical modeling and bioinformatics tools were applied to classify each chemical using the genomic biomarker. BaP and AFB1 were correctly classified as genotoxic at the mid- and high concentrations at all three time points, whereas DEX was correctly classified as non-genotoxic at all concentrations and time points. The high concentration of PB was misclassified at 24h, suggesting that cytotoxicity at later time points may cause misclassification. The data suggest that the use of S9 does not impair the ability of the biomarker to classify genotoxicity in TK6 cells. Finally, we demonstrate that the biomarker is also able to accurately classify genotoxicity using a publicly available dataset derived from human HepaRG cells.

2015-04-15 | GSE58782 | GEO

Integration of metabolic activation with a predictive toxicogenomics signature to classify genotoxic versus nongenotoxic chemicals in human TK6 cells [BaP]

2015-04-15 | GSE51172 | GEO

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