data ArrayExpress/E-GEOD-73121

data/ArrayExpress/E-GEOD-73121/E-GEOD-73121.idf.txt

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+Comment[ArrayExpressAccession]	E-GEOD-73121
+MAGE-TAB Version	1.1					
+Public Release Date	2015-09-18
+Investigation Title	Single-cell transcriptome profiling for metastatic renal cell carcinoma patient-derived cells [RNA-seq]					
+Comment[Submitted Name]	Single-cell transcriptome profiling for metastatic renal cell carcinoma patient-derived cells [RNA-seq]
+Experiment Description	Clear cell renal cell carcinoma (ccRCC) initiated from the renal epithelium is the most prevalent histological type of adult kidney cancers. Dissecting intratumoral heterogeneity (ITH) of ccRCC has leveraged to extend our knowledge on how primary tumors harboring driver mutations evolve and spread to other sites. The cellular fractions within and across the primary (pRCC) and metastatic RCC (mRCC) are heterogeneous in both their genetic and biological features determining the variability in clinical aggressiveness and sensitivity to the therapy. To achieve sustainable therapeutic benefit with targeted agents in mRCC, the effective target should focus on signaling pathways that are related to driver mutations occurred early in the clonal evolution of the disease and thus should be common to primary tumor and metastatic sites. Considering that extensive genetic heterogeneity may result in drug response variability among patients and treatment resistance, the tailored strategies for metastatic RCC is urgently needed. Here, we analyze single-cell RNA-seq (scRNA-seq) data from a matched primary RCC (pRCC) and lung metastasis (mRCC) to dissect ITH at the highest resolution to date with the objective of discovering the better therapeutic regimen. In order to identify successful clonal propagation from patient to PDX samples and understand pathogenesis from primary to metastatic RCC, we performed whole-exome sequencing (WES, n=4) and matched aCGH (n=4) on bulk tumor samples. And we utilized single-cell RNA sequencing (scRNA-seq) to model and dissect functional heterogeneity acroass primary and metastatic RCC tumors. We checked whether of capturing live one cell, not more cells, in microfluidics by fluorescent microscopic observation. To construct RNA sequencing libraries, we performed further quality controls including adequate quantities and qualities of amplified transcriptomes respectively from single cells. Tumor cells from the parental mRCC (n=34), PDX-mRCC (n=36) and PDX-pRCC (n=46) were finally analyzed in this study after filtering out poor quality cells.					
+Term Source Name	ArrayExpress	EFO
+Term Source File	http://www.ebi.ac.uk/arrayexpress/	http://www.ebi.ac.uk/efo/efo.owl				
+Person Last Name	Kim	Kim	Lee	Lee	Joo	Park
+Person First Name	Kyu-Tae	Kyu-Tae	Hye	Hae-Ock	Kyeung	Woong-Yang
+Person Mid Initials			W		M	
+Person Email	geo@ncbi.nlm.nih.gov					
+Person Affiliation	Samsung Medical Center					
+Person Address	Samsung Genome Institute, Samsung Medical Center, Irwon-Ro 81, Seoul, South Korea					
+Person Roles	submitter					
+Protocol Name	P-GSE73121-3	P-GSE73121-2	P-GSE73121-1			
+Protocol Description	For PDX samples, RNA-seq reads only mapped to the mouse genome reference (mm10) were removed. Then, sequencing reads were aligned to the human genome reference (hg19) together with splice junction information of each sample using the 2-pass mode of STAR_2.4.0d (Dobin et al., Bioinformatics 2012). Transcripts Per Million (TPM) was quantified by implementing RSEM v1.2.18 (Li et al., BMC Bioinformatics 2011) in default mode with Genecode v.19 annotation. Genome_build: hg19 Supplementary_files_format_and_content: Each row of the tab-delimited text file includes ENSEMBL gene ID,ENSEMBL transcript ID, transcript length, effective_length, expected_count, TPM, FPKM for samples.	In order to isolate single-cells and amplify initial RNA content enough to transcriptome sequencing, we adopted the C1TM Single-Cell Auto Prep System (Fluidigm, CA, USA) with the SMARTer kit (Clontech, CA, USA). Cells were captured on the C1 chip (17-25 μm) and determined as a live single cell by fluorescence microscopic observation. Quantity and quality of amplified cDNAs from individual single cells were checked by Qubit® 2.0 Fluorometer (Life Technologies, CA, USA) and 2100 Bioanalyzer (Agilent Inc., CA, USA). RNAs from bulk cell samples were also amplified using a SMARTer kit with 10 ng of starting material. For WES, gDNAs were prepared using QIAamp® DNA Mini kit (QIAGEN, CA, USA). Exome sequencing was carried using the SureSelect XT Human All Exon V5 kit (Agilent Inc., CA, USA), according to the manufacturer’s standard protocol. Libraries were prepared using the Nextera XT DNA Sample Prep Kit (Illumina, CA, USA) following the manufacturer’s instruction, assayed the quantity and quality, pooled, and then sequenced on the HiSeq 2500 (Illumina) using the 100bp paired-end mode of the TruSeq Rapid PE Cluster kit and TruSeq Rapid SBS kit (Illumina) at the Samsung Genome Institute (Seoul, Korea). Sequencing of the exome library was carried out on the HiSeq 2500 (Illumina, CA, USA) using the 100bp paired-end mode of the TruSeq Rapid PE Cluster kit and TruSeq Rapid SBS kit (Illumina) at the Samsung Genome Institute (Seoul, Korea).	This study was carried out in accordance with the principles of the Declaration of Helsinki, and approved by The Samsung Medical Center (Seoul, Korea) Institutional Review Board (IRB) (no. 2010-04-004). A participant in this study gave written informed consent for research and publication of the results. Animal experiments were conducted in accordance with the Institute for Laboratory Animal Research Guide for the Care and Use of Laboratory Animals and within the protocols approved by the appropriate IRB at the Samsung Medical Center. After validating the origin of each xenograft by short tandem repeat DNA fingerprinting, sacrified tumor tissues together with prepared patient metastasis tumor samples were dissociated to implement C1™ Single-Cell Auto Prep System.			
+Protocol Type	normalization data transformation protocol	nucleic acid library construction protocol	growth protocol			
+Experimental Factor Name	cell source	cell type				
+Experimental Factor Type	cell source	cell type				
+Comment[SecondaryAccession]	GSE73121					
+Comment[GEOReleaseDate]	2015-09-18					
+Comment[ArrayExpressSubmissionDate]	2015-09-17					
+Comment[GEOLastUpdateDate]	2015-09-20					
+Comment[AEExperimentType]	RNA-seq of coding RNA					
+Comment[SecondaryAccession]	SRP063840					
+Comment[SequenceDataURI]	http://www.ebi.ac.uk/ena/data/view/SRR2431343-SRR2431463					
+SDRF File	E-GEOD-73121.sdrf.txt