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Sample GSM3320538

Query DataSets for GSM3320538

Status

Public on Mar 28, 2019

Title

PAC006 ACF 26

Sample type

SRA

Source name

patient-derived tumor xenografts (PDTX) model of pancreatic ductal adenocarcinoma (PDAC)

Organisms

Homo sapiens; Mus musculus

Characteristics

model: PAC006
treatment: Acriflavine

Treatment protocol

After the tumor reach a volume of 100-200 mm3, these mice were randomly divided into three groups with eight mice in each group; A) the control group that was treated with vehicle (0.9% NaCl) and the experimental groups was treated intraperitoneally for up to 28 days with B) Gemcitabine (50 mg/kg) injected twice a week. C) Acriflavine: schedule four doses of acriflavine were injected daily with a fixed dose of 5 mg/kg Monday to Thursday and single dose of 10 mg/kg on Friday for the weekend. At the end of the experiment or when the tumor volume reached the limit the tissue samples from each tumor were weighed, photographed and stored for histological analysis and molecular profiling.

Growth protocol

The development and characterization of the PDTX model has been described in detail by Hermans et al. 2016. Endoscopy, 48: 1016-1022.

Extracted molecule

total RNA

Extraction protocol

RNA from biological tissue samples was isolated with the RNeasy Kit (Qiagen, Chatsworth, CA) according to the manufacturer's instructions. The RNA quality and quantity were verified with a NanoDrop 1000 Spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). RNA sequencing and processing were performed by VIB Nucleomics Core (www.nucleomics.be).
Per sample, an amount of 500 ng of total RNA was used as input. Using the Illumina TruSeq® Stranded mRNA Sample Prep Kit (protocol version: Part # 15031047 Rev. E - October 2013) poly-A containing mRNA molecules were purified from the total RNA input using poly-T oligo-attached magnetic beads. In a reverse transcription reaction using random primers, RNA was converted into first strand cDNA and subsequently converted into double-stranded cDNA in a second strand cDNA synthesis reaction using DNA PolymeraseI and RNase H. The cDNA fragments were extended with a single ‘A’ base to the 3’ ends of the blunt-ended cDNA fragments after which multiple indexing adapters were ligated introducing different barcodes for each sample. Finally, enrichment PCR was carried out to enrich those DNA fragments that have adapter molecules on both ends and to amplify the amount of DNA in the library. Sequence-libraries of each sample were pooled and sequenced on an Illumina HiSeq 4000 full flow-cell (8 lanes) with a single read 50 kit (68 cycles, 2nM Pool + 1% PhiX v3) at the VIB Nucleomics core (www.nucleomics.be).

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 4000

Description

mRNA-seq
PolyA RNA
PAC006@ACF@26@S10
processed data file: RNAseqCounts-Human.txt
processed data file: RNAseqCounts-Mouse.txt

Data processing

Preprocessing: Low quality ends and adapter sequences were trimmed off from the Illumina reads with FastX 0.0.14 and Cutadapt 1.15 (HannonLab, 2010; Martin, 2011). Subsequently, small reads (length < 35 bp), polyA-reads (more than 90% of the bases equal A), ambiguous reads (containing N), low-quality reads (more than 50 % of the bases < Q25) and artifact reads (all but three bases in the read equal one base type) were filtered using FastX 0.0.14 and ShortRead 1.36.0 (Morgan et al., 2009). With Bowtie2 2.3.3.1 we identified and removed reads that align to phix_illumina (Langmead & Salzberg, 2012).
Xenome classification: The preprocessed reads were classified into human and mouse reads using Xenome (version 1.0.0; now part of the gossamer suite) which allows segregation of mixed reads as compared to two genome references (Conway et al. 2012). The reference genomes were from EnsEMBL website (i.e. GRCh38 for Human and GRCm38 for Mouse). With Xenome, 1.2-1.9% of the reads per sample were discarded due to ambiguity (ambigous_reads), cross-mapped reads (both_reads) or unclassifiable reads (neither_reads).
Mapping: The preprocessed human reads were aligned with STAR aligner v2.5.2b to the reference genome of Homo sapiens (GRCh38) (AD et al., 2013). Default STAR aligner parameter settings were used, except for ‘--outSAMprimaryFlag OneBestScore --twopassMode Basic --alignIntronMin 50 --alignIntronMax 500000 --outSAMtype BAM SortedByCoordinate’. Using Samtools 1.5, reads with a mapping quality smaller than 20 were removed from the alignments (Li et al., 2009).
Counting: The number of reads in the alignments that overlap with gene features were counted with featureCounts 1.5.3 (Liao et al., 2014). Following parameters were chosen: -Q 0 -s 2 -t exon -g gene_id. We removed genes for which all samples had less than 1 count-per-million. Raw counts were further corrected within samples for GC-content and between samples using full quantile normalization, as implemented in the EDASeq package from Bioconductor (Risso et al., 2011). One sample (PAC010@GEM@11@S17) has been identified as an outlier after summarization of the human samples and was discarded for the statistical comparisons.
Genome_build: GRCh38 (human) and GRCm38 (mouse)
Supplementary_files_format_and_content: Raw counts are in tab-delimited text files for each reference genome (RNAseqCounts_Mouse.txt for mouse and RNAseqCounts_Human.txt for human).

Submission date

Aug 06, 2018

Last update date

Mar 28, 2019

Contact name

Rekin's Janky

E-mail(s)

Nucleomics.Bioinformatics@vib.be

Organization name

VIB

Department

Nucleomics Core