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Sample GSM1660153

Query DataSets for GSM1660153

Status

Public on Sep 17, 2015

Title

Pr9.3.7

Sample type

SRA

Source name

lineage-confirmed PCa CTC

Organism

Homo sapiens

Characteristics

donor: Pr9
donor type: CRPC
enzalutamide: enzalutamide-naive (Group A)

Extracted molecule

total RNA

Extraction protocol

Samples that have “source name” above set to “candidate PCa CTC” or “lineage-confirmed PCa CTC” were extracted as follows. We applied the CTC-iChip (PMID: 23552373) to efficiently deplete normal hematopoietic cells from whole blood specimens. Cell surface staining of remaining unfixed cells for epithelial (EpCAM) and mesenchymal (CDH11) markers (PMID: 23845299), combined with absent staining for the common leukocyte marker CD45, was used to select candidate tumor cells for micromanipulation. Samples that have “source name” set to “primary PCa tumor” were frozen primary prostate cancer tissue samples from patients with localized prostate cancer who underwent prostatectomy, that were then sectioned and microdissected for >70% tumor content. Samples that have “source name” above set to “single cell from PCa cell line” were trypsinized into single-cell suspension and then micromanipulated. Only samples for which amplification was successful were submitted for sequencing. White blood cell samples from donor Pr23 were processed using the CTC-iChip and micromanipulated after staining for CD45. White blood cells from healthy donor HD1 were isolated from his blood using a micromanipulator, after enrichment of the mononuclear fraction using a BD Vacutainer CPT Cell Preparation Tube with Sodium Citrate and staining for CD45. For all samples RNA was extracted and amplified as in Tang, et. al. (PMID: 20203668).
Libraries were constructed as previously described (Tang, F., Barbacioru, C., Nordman, E., Li, B., Xu, N., Bashkirov, V.I., Lao, K., and Surani, M.A. (2010). RNA-Seq analysis to capture the transcriptome landscape of a single cell. Nat Protoc 5, 516-535). Briefly, to generate cDNA, samples were treated with reverse transcription master mix (0.05 uL RNase inhibitor, 0.07uL T4 gene 32 protein, and 0.33uL SuperScript III Reverse Transcriptase per 1X volume) and incubated on thermocycler at 50C for 30 minutes and 70C for 15 minutes. To remove free primer, 1.0uL of EXOSAP mix was added to each sample, which was incubated at 37C for 30 minutes and inactivated at 80C for 25 minutes. Next, a 3'-poly-A tail was added to the cDNA in each sample by incubating in master mix (0.6uL 10X PCR Buffer II, 0.36uL 25mM MgCl2, 0.18uL 100mM dATP, 0.3uL Terminal Transferase, 0.3uL RNase H, and 4.26uL H2O per 1X volume) at 37C for 15 minutes and inactivated at 70C for 10 minutes. A second strand cDNA was synthesis by dividing each sample into 4 and incubating in master mix (2.2uL 10X High Fidelity PCR Buffer, 1.76uL 2.5mM each dNTP, 0.066uL UP2 Primer at 100uM, 0.88uL 50mM MgSO4, 0.44uL Platinum Taq DNA Polymerase, and 13.654uL H2O per 1X volume) at 95C for 3 minutes, 50C for 2 minutes, and 72C for 10 minutes. DNA was sheared using a Covaris S2 system and then prepared for ABI 5500XL library construction with end polishing, size selection of 200-500 bp using AMPure XP, ABI barcode adaptor ligation, amplification and purification with AMPure XP, and then pooling of barcoded samples for emulsion PCR wiht template beads preparation. Samples were then loaded per protocol on the ABI 5500XL.
RNA-Seq using oligo-dT cDNA synthesis and amplification of cDNA libraries using custom universal PCR primers

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

AB 5500xl Genetic Analyzer

Description

single cell in lysis buffer

Data processing

Color space reads were aligned using tophat version 2.0.4 and bowtie1 version 0.12.7 with the no-novel-juncs argument set with human genome version hg19 and transcriptome defined by the hg19 knownGene table from genome.ucsc.edu.
Reads that did not align or aligned to multiple locations in the genome were discarded.
The hg19 table knownToLocusLink from genome.ucsc.edu was used to map, if possible, each aligned read to the gene who's exons the read had aligned to. The reads count for each gene was the number of reads that were so mapped to that gene.
The read count was divided by the total number of reads that were mapped to any gene and multiplied by one million to form the reads-per-million (rpm) count.
Genome_build: hg19
Supplementary_files_format_and_content: The readCounts.txt file gives the read counts described above for each sample (columns) and gene (rows).

Submission date

Apr 16, 2015

Last update date

May 15, 2019

Contact name

Ben S. Wittner

E-mail(s)

wittner.ben@mgh.harvard.edu

Organization name

Massachusetts General Hospital

Department

Center for Cancer Research