run_metadata: 69559

This data as json

rowid	run.accession	experiment.accession	sample.accession	study.accession	bioproject	study.title	study.alias	study.type	study.abstract	study.attributes	study.PMIDs	sample.description	sample.title	sample.alias	sample.centername	sample.attributes	GEOsample.title	GEOsample.dataprocessing	GEOsample.source	GEOsample.treatmentprotocol	GEOsample.extractprotocol	GEOsample.growthprotocol	GEOsample.characteristics	GEOsample.accession	experiment.title	experiment.alias	experiment.library_name	experiment.design_description	experiment.library_construction_protocol	experiment.attributes	experiment.library_strategy	experiment.library_source	experiment.library_selection	experiment.library_layout	experiment.platform	experiment.instrument_model	experiment.spot_descriptor	experiment.study_ref	run.title	run.attributes	run.filename	run.semantic_name	run.total_bases	run.total_spots	run.alias	run.read_lengths	run.base_counts	run.r1_length	run.r2_length	run.r3_length	run.r4_length	run.Acount	run.Ccount	run.Gcount	run.Tcount	run.Ncount	run.experiment	run.pool_member	submission.accession	submission.srasource	submission.bioprojectsource	seqdetective.n_mates	seqdetective.mapping_rate.mate1	seqdetective.mapping_rate.mate2	seqdetective.nofeature_rate.mate1	seqdetective.nofeature_rate.mate2	seqdetective.sparsity.mate1	seqdetective.sparsity.mate2	seqdetective.pos_strand_rate.mate1	seqdetective.pos_strand_rate.mate2	seqdetective.readlen.mate1	seqdetective.readlen.mate2	seqdetective.judgement.mate1	seqdetective.judgement.mate2	seqdetective.judgement.reason	platform_family	instrument_generation	read_bias	selection_class	prep_kit	sc_or_bulk	tech_class	technology	tech_variant	submission.bioprojectsource.country	earliest_date	devstage_curation	devstage_curation_coarse	tissue_curation	tissue_curation_coarse
69559	SRR18901603	SRX14979859	SRS12729750	SRP371883	PRJNA831276	Lipid droplets are a metabolic vulnerability in melanoma	GSE201378	Transcriptome Analysis	Melanoma exhibits numerous transcriptional cell states including neural crest like cells as well as pigmented melanocytic cells. How these different cell states relate to distinct tumorigenic phenotypes remains unclear. Here we use a zebrafish melanoma model to identify a transcriptional program linking the melanocytic cell state to a dependence on lipid droplets the specialized organelle responsible for lipid storage. Single cell RNA sequencing of these tumors show a concordance between genes regulating pigmentation and those involved in lipid and oxidative metabolism. This state is conserved across human melanoma cell lines and patient tumors. This melanocytic state demonstrates increased fatty acid uptake an increased number of lipid droplets and dependence upon fatty acid oxidative metabolism. Genetic and pharmacologic suppression of lipid droplet production is sufficient to disrupt cell cycle progression and slow melanoma growth in vivo. Because the melanocytic cell state is linked to poor outcomes in patients these data indicate a metabolic vulnerability in melanoma that depends on the lipid droplet organelle. Overall design: Expression profiling by high throughput sequencing of zebrafish melanoma		pubmed:37268606		TEAZ scRNAseq	GSM6062264		source name:Skin\|tissue:Skin\|cell type:melanoma	TEAZ scRNAseq	Data was processed using R version 4.0.5 and Seurat version 4.0.2. Cells with fewer than 200 unique genes and mitochondrial genes above 30% were filtered. Expression data was normalized using SCTransform with principal component analysis and UMAP dimensionality reduction performed at default parameters. Clustering was performed using the Seurat function FindClusters with resolution of 0.4. Cluster annotation for zebrafish cell type specific marker genes as done previously using FindAllMarkers. Counts matrix derived from Seurat Data was processed using R version 4.0.5 and Seurat version 4.0.2. Cells with fewer than 200 unique genes and mitochondrial genes above 30% were filtered. Expression data was normalized using SCTransform with principal component analysis and UMAP dimensionality reduction performed at default parameters. Clustering was performed using the Seurat function FindClusters with resolution of 0.4. Cluster annotation for zebrafish cell type specific marker genes as done previously using FindAllMarkers. Assembly: GRCz11	Skin		Zebrafish tumors were dissected and dissociated for encapsulation Library preparation and sequencing were done by the Single Cell Research Initiative and Integrated Genomics Organization at MSKCC. For cell encapsulation and library preparation droplet based scRNA seq was performed on approximately 5900 cells using the Chromium Single Cell 3’ Library and Gel Bead Kit v3 and Chromium Single Cell 3’ Chip G 10x Genomics into a single v3 reaction. GEM generation and library preparation were performed according to manufacturer instructions. Libraries were sequenced on a NovaSeq6000. Sequencing parameters: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 51 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger 6.0.2.		tissue:Skin\|cell type:melanoma	GSM6062264	GSM6062264: TEAZ scRNAseq; Danio rerio; RNA Seq	GSM6062264 r1	GSM6062264	1	Zebrafish tumors were dissected and dissociated for encapsulation Library preparation and sequencing were done by the Single Cell Research Initiative and Integrated Genomics Organization at MSKCC. For cell encapsulation and library preparation droplet based scRNA seq was performed on approximately 5900 cells using the Chromium Single Cell three prime Library and Gel Bead Kit v3 and Chromium Single Cell three prime Chip G 10x Genomics into a single v3 reaction. GEM generation and library preparation were performed according to manufacturer instructions. Libraries were sequenced on a NovaSeq6000. Sequencing parameters: Read1 28 cycles i5 10 cycles i7 10 cycles Read2 90 cycles. Sequencing depth was approximately 51 000 reads per cell. Sequencing data was aligned to our reference zebrafish genome using CellRanger 6.0.2.		RNA-Seq	TRANSCRIPTOMIC SINGLE CELL	cDNA	PAIRED	ILLUMINA	Illumina NovaSeq 6000		SRP371883		loader:fastq load.py	2544_PTEN_combined_IGO_11963_4_S2_L002_R1_001.fastq.gz 2544_PTEN_combined_IGO_11963_4_S2_L002_R2_001.fastq.gz	fastq fastq	9122357880.0	76019649.0	GSM6062264 r2	0:29 1:91	A:2521047948;C:2056950129;G:2200048731;T:2343919901;N:391171	29	91			2521047948	2056950129	2200048731	2343919901	391171	SRX14979859	SRS12729750	SRA1408865	Richard M. White, Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center	Richard M. White, Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center	2	0.00471	0.87992	0.00196	0.14374	0.99255	0.78476	0.35593	0.54484	29	91	T	B	sc-like readlen	illumina	novaseq_era	unknown	cdna_unspecified	unknown	sc	single_cell_droplet	10x		United States	2022-04-23	Undetermined	Undetermined	Skin	Surface Structure