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Status |
Public on Jul 28, 2019 |
Title |
Breast adenocarcinoma cell line MCF7 – Long Term Estrogen Deprived (LTED) – rep3 |
Sample type |
RNA |
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Source name |
Breast adenocarcinoma
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Organism |
Homo sapiens |
Characteristics |
treatment: Long Term Estrogen Deprived MCF7 cells cell type: LTED
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Treatment protocol |
MCF7- and LTED cells were maintained in sterol-deprived medium in phenol red–free RPMI1640 medium containing 10% dextran charcoal-stripped (DCC) FBS and 2 mmol/L glutamine (DCC medium). MCF7+ cells were grown as MCF7+ and LTED in the presence of 1 nM 17β-oestradiol (E2, Sigma).
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Growth protocol |
MCF7 and LTED human breast cancer cells were obtained from ATCC and cultured in phenol free-red RPMI 1640 medium supplemented with 10% foetal bovine serum and 2 mmol/L glutamine. Cells were short tandem repeat tested, amplified, stocked, routinely subjected to mycoplasma testing and once thawed were kept in culture for a maximum of 20 passages.
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Extracted molecule |
total RNA |
Extraction protocol |
Total RNA (including microRNA) was extracted using miRNeasy (Qiagen) according to the manufacturer’s instructions.
|
Label |
Cy3
|
Label protocol |
RNA labeling was performed in accordance to manufacturer’s indications.
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Hybridization protocol |
RNA hybridization was performed in accordance to manufacturer’s indications.
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Scan protocol |
Arrays were scanned with Agilent Technologies Scanner G2505C. Numerical raw values were obtained using Feature Extraction 10.7.3.1 software (Agilent Technologies). Grid: 028004_D_F_20140813. Protocol: GE1_107_Sep09
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Description |
Gene expression of Long Term Estrogen Deprived MCF7 cells (LTED)
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Data processing |
Data were normalized and analyzed using GeneSpring GX v.14.8 software (Agilent Technologies). Data transformation was applied to set all the negative raw values at 1.0, then the quantile normalization was applied. A filter on low gene expression was used to keep only the probes expressed in at least one sample.
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Submission date |
Oct 08, 2018 |
Last update date |
Jul 30, 2019 |
Contact name |
Matteo Ramazzotti |
E-mail(s) |
matteo.ramazzotti@unifi.it
|
Organization name |
University of Florence
|
Department |
Experimental and Clinical Biomedical Sciences
|
Street address |
viale Morgagni 50
|
City |
Firenze |
ZIP/Postal code |
50134 |
Country |
Italy |
|
|
Platform ID |
GPL14550 |
Series (2) |
GSE120929 |
Amino acids availability and subsequent metabolic reprogramming sustain endocrine resistance in breast cancer (mRNA) |
GSE120931 |
Amino acids availability and subsequent metabolic reprogramming sustain endocrine resistance in breast cancer |
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