|
| Status |
Public on Apr 21, 2015 |
| Title |
Human BT474 breast cancer cell line under trastuzumab treatment |
| Sample type |
SRA |
| |
|
| Source name |
Cell line
|
| Organism |
Homo sapiens |
| Characteristics |
cell line: BT474
drug treatment: trastuzumab
cell type: HER2-positive breast cancer
resistance: no trastuzumab resistance
|
| Treatment protocol |
For treatment experiments, 2x105 cells were seeded in T25 flasks and cultivated as recommended by ATCC.
Cells were treated with 20 μg/ml trastuzumab (Roche Diagnostics GmbH, Penzberg, Germany) or grown in full growth media without inhibitors.
Cell pellets were harvested after 72 h. The cells were incubated in the standard media 24 h before addition of trastuzumab or fresh full growth media.
Resistant cells (BTR50) were developed by culturing parental cells (BT474) in the presence of 20/50 µg trastuzumab (Roche) for around six month.
Parental cells were cultured in parallel to resistant ones without addition of trastuzumab.
|
| Growth protocol |
The cells were grown in a monolayer and collected as a cell pellet after trypsin treatment. RNA was harvested from cell pellet using the miRNeasy kit (Qiagen).
The human breast cancer cell lines BT474 and HCC1954 were obtained from the American Type Culture Collection (ATCC). The BT474 was cultured in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum, 0.01 mg/ml of insulin and 1% penicillin/streptomycin.
The human breast cancer cell line HCC1954 was cultured in RPMI media (Gibco) supplemented with 10% fetal bovine serum (Gibco). The medium was supplemented with 1% penicillin/streptomycin (Gibco).
The cells were cultured at 37°C in an atmosphere containing 5% CO2. Cells were harvested with trypsin-ethylenediamine tetraacetic acid (EDTA) (0.5 g/L trypsin; 0.2 g/L EDTA; Sigma).
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was isolated from cell lines BT474, BTR50 and HCC1954 using the Trizol (Invitrogen) method according to the manufacturer's recommendations.
Afterwards, the samples were DNAse I (Sigma) treated in order to remove DNA contamination.
RNA quality was determined using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) microfluidic electrophoresis.
Only samples with comparable RNA integrity numbers were selected for deep sequencing.
Library preparation for RNA-Seq was performed using the TruSeq RNA Sample Preparation Kit (Illumina, Cat. N°RS-122-2002) starting from 800 ng of total RNA.
Accurate quantitation of cDNA libraries was performed by using the QuantiFluor™ dsDNA System (Promega).
The size range of final cDNA libraries was determined applying the DNA 1000 chip on the Bioanalyzer 2100 from Agilent (280 bp).
cDNA libraries were amplified and sequenced by using the cBot and HiSeq 2000 from Illumina (SR; 1x51 bp; 6 GB ca. 30-35 million reads per sample).
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 2000 |
| |
|
| Description |
BT474 plus trastuzumab
nexprs_bt474_bt474T.xls
|
| Data processing |
Sequence images were transformed with Illumina software BaseCaller to bcl files, which were demultiplexed to fastq files with CASAVA v1.8.2.
Quality check was done via FastQC (v0.10.1, Babraham Bioinformatics).
Sequenced reads were hard (first 5 bases) and soft (last bases) trimmed as well as trimmed for adaptor sequences via Flexbar v2.32, then mapped to the human reference genome (GRCh37, Gencode release 14) using STAR v2.3.0 with parameter --outFilterMismatchNmax 3.
Conversion of SAM to BAM files and corresponding sorting was done via SAMtools v0.1.18.
Counting the reads to each gene to the UCSC gtf gene annotation file (March 2012) was done via HTSeq python scripts (0.5.3p9, htseq-count).
Normalization to the library size, estimation of dispersions (method="blind", sharingMode="fit-only") and testing for differentially expressed (DE) genes based on a statistical test assuming negative binomial data distribution was computed via the DESeq (v1.12.1) R package.
Just genes exceeding 20 counts for at least one sample were kept for further analysis.
The numerator and denominator of fold changes (FC) were increased by one to account for zero values.
Significant genes were filtered to a minimum of 2xFC and fdr<0.05 with multiple testing correction according to Benjamini and Hochberg.
Genome_build: hg19
Supplementary_files_format_and_content: xls files include normalized count of reads for each gene and each pair of samples in the related statistical test.
|
| |
|
| Submission date |
Feb 13, 2014 |
| Last update date |
May 15, 2019 |
| Contact name |
Silvia von der Heyde |
| E-mail(s) |
silvia.heyde@gmail.com
|
| Organization name |
University Medical Center Göttingen
|
| Department |
Medical Statistics
|
| Street address |
Humboldtalle 32
|
| City |
Göttingen |
| ZIP/Postal code |
37073 |
| Country |
Germany |
| |
|
| Platform ID |
GPL11154 |
| Series (1) |
| GSE55005 |
mRNA profiling reveals determinants of trastuzumab efficiency in HER2-positive breast cancer |
|
| Relations |
| BioSample |
SAMN02641781 |
| SRA |
SRX470400 |
