Transcriptional profiling of a breast cancer cell line panel using RNAseq technology
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE48213 | GEO | 2013/08/20
SECONDARY ACCESSION(S): PRJNA210428
REPOSITORIES: GEO
Similar Datasets
Project description:56 breast cancer cell lines were profiled to identify patterns of gene expression associated with subtype and response to therapeutic compounds. Cell lines were profiled in their baseline, unperturbed state.
2013-08-20 | E-GEOD-48213 | biostudies-arrayexpress
Project description: Not available
| S-ECPF-GEOD-48213 | biostudies-other
Project description:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients.
2014-09-18 | GSE53418 | GEO
Project description:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients. Gene expression was measured for 32 ovarian cancer cell lines using the GeneChip Human Exon 1.0 ST Array (Affymetrix). Morphological subtypes were assigned based on cell morphology, size, growth pattern and proliferation rate during culturing of the cell lines.
2014-09-18 | E-GEOD-53418 | biostudies-arrayexpress
Project description:Purpose: The purpose of this experiment was to determine the time point following activation at which greatest transcriptional differences in metabolic genes were observed between primary human CD4+ T cells treated with metformin + 2-deoxyglucose combination regimen and cells treated with vehicle. Methods: Targeted RNA-Seq data was generated from primary human CD4+ T cell mRNA using a Qiagen custom designed panel of metabolic genes and the Illumina TruSeq stranded mRNA prep. Results: We obtained differential gene expression between metformin + 2-deoxyglucose and vehicle-treated cells using the DESeq2 app in Illumina Basespace for a set of metabolic genes during different time points following activation, and found the greatest changes at 24hr.
2020-06-15 | GSE144352 | GEO
Project description:Microarrays have revolutionized breast cancer (BC) research by enabling studies of gene expression on a transcriptome-wide scale. Recently, RNA-Sequencing (RNA-Seq) has emerged as an alternative for precise readouts of the transcriptome. To date, no study has compared the ability of the two technologies to quantify clinically relevant individual genes and microarray-derived gene expression signatures (GES) in a set of BC samples encompassing the known molecular BC's subtypes. To accomplish this, the RNA from 57 BCs representing the four main molecular subtypes (triple negative, HER2 positive, luminal A, luminal B), was profiled with Affymetrix HG-U133 Plus 2.0 chips and sequenced using the Illumina HiSeq 2000 platform. The correlations of three clinically relevant BC genes, six molecular subtype classifiers, and a selection of 21 GES were evaluated.
2014-11-21 | GSE43358 | GEO
Project description: Not available
| S-EPMC6107498 | biostudies-other
Project description:A panel of twelve breast cancer cell lines (ATCC) were exposed to 0, 1 or 10 nM 17β-estradiol (E2) for 16 hours. Cells were maintained in DMEM/F12 1:1 (DF) supplemented with 10% or 20% fetal calf serum (FCS) or 20% FCS and 0.01 mg/ml insulin. Two days before experiments, cells were seeded in 60 mm plates in DF with charcoal stripped phenol red-free serum supplemented with non-essential amino-acids and pen/strep, at a density such that 75%-90% confluence was obtained by the time of harvesting. Medium was refreshed 24 hours before exposure to 1 nM E2, 10 nM E2 or DMSO (control) for 16h. Subsequently cells were harvested and RNA was extracted using the Nucleospin RNA isolation kit (Macherey-Nagel).
2019-06-01 | GSE127760 | GEO
Project description:mRNA breast cancer cell lines were profiled to study the function of hsa-mir-221 and hsa-mir-222. MCF7 cell lines were profiled after treatment with mir-221/222 mimics, and compared to profiles with transfection controls. Similarly, MDA-MB-231 cell lines were profiled after treatment with mir-221/222 inhibitors, and compared to profiles with transfection controls. Since ESR1 is a predicted target of mir-221/222 we also profiled MCF7 cell lines after disrupting ESR1 with an siRNA. Other breast cancer cell lines are provided because all cell lines were normalized together. Keywords: breast cancer, cell line, hsa-mir-221, hsa-mir-222, ESR1
2008-12-01 | GSE10890 | GEO
Project description:Analysis of Diffuse Large B-Cell Lymphoma (DLBCL) OCI-LY3 cell line treated with 14 different known drugs at 2 different concentrations and profiled at 6, 12 and 24 hrs after treatment. We used this gene expression data to design a challenge where participants were required to develop methods to predict activity of compound pairs using gene expression profile following single compound treatment, drug response curve of each compound and baseline genetic profile of OCI-LY3 cell line. GeneChip HT HG-U219 array plates were used to analyze gene expression changes induced by treatment with 14 drug compounds in OCI-Ly3 cells at 6, 12 and 24h. 3 replicates were analyxed for each drug/time combination. Vehicle (DMSO)-treated control samples were used for comparison with each replicate. Altogether 282 samples were analyzed in this study.
2014-09-25 | E-GEOD-51068 | biostudies-arrayexpress