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DrugMap: A quantitative pan-cancer analysis of cysteine ligandability (RNA-Seq)

GSE256466 Homo sapiens (human) Single-cell RNA-seq 69 samples Submitted 2024/04/24 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 69 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
69 samples: 21 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
DrugMap: A quantitative pan-cancer analysis of cysteine ligandabilityCell · 2024
Summary (written by the submitters)
SOX10 is a lineage-restricted transcription factor important for melanoma proliferation and survival. Our data demonstrate that SOX10 genetic depletion by CRISPR/Cas9 significantly impaired melanoma proliferation. We chose 7 different melanoma, all of which exhibited growth dependency on SOX10 with different levels. To define the SOX10 transcriptional signature shared with different SOX10-dependent melanoma, we performed bulk RNA-seq on 7 melanoma transfected with siSOX10 or siControl.
Read the full summary ↓
Each melanoma cell line was plated and transfected with each siRNA to deplete SOX10 protein expression. After 72 hrs, cells were lysed with Buffer TCL(QIAGEN) supplemented with 2-ME and stored at -80C until use. Libraries from each cell line were made with the modified Smart-seq2 protocol. Each replicate was uniquely barcoded and all the samples were pooled for sequencing. (2) We developed a chemical probe (SH-0029) that covalently engages SOX10. To examine the effect of SH-0029 on SOX10 target genes, SOX10-dependent SKMEL5 melanoma were plated and treated with SH-0029, SH-0105 (a control probe), or DMSO(vehicle) for 48h. Total RNA was extracted with NucleoSpin RNA extraction kit (MACHEREY-NAGEL) and mRNA was subsequently purified with poly dT-attached magnetic beads. We found that downregulated genes induced by SH-0029 treatment strongly overlapped with those by SOX10 genetic depletion, suggesting that SOX10 covalent ligand controls SOX10 transcriptional network.
Published in
DrugMap: A quantitative pan-cancer analysis of cysteine ligandability
Takahashi M, Chong HB, Zhang S et al. · Cell 2024 · PMID 38653237 · doi:10.1016/j.cell.2024.03.027
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE256466_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1079745 and SRA study SRP491378. Searching any of these in the dataset finder brings you back here.

Study design
21 conditions, mostly in triplicate
C_13_F10 ×6 C_16_H03 ×6 SK_MEL2_siSOX10_B ×3 SK_MEL28_siSOX10_C ×3 U257_siSOX10_E ×3 I_DMSO ×3 I_13_F10 ×3 I_16_H03 ×3 +22 more

Supports a between-group comparison across 60 samples.

How we read this: 21 replicated groups read from 69 sample titles; they account for 60 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 29 more — browse all 69 samples with per-sample file links →

Datasets on a similar topic

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