RNAseq of melanoma cells treated with the p300 inhibitor A-485
RNA-seq (gene expression) · human · 12 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Topic
- MelanomaThis series is part of our curated briefing on it.
- Samples
- 12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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
- p300 KAT Regulates SOX10 Stability and Function in Human MelanomaCancer research communications · 2024
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE254326_RAW.tar (it can run to tens of gigabytes).
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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1069748 and SRA study SRP486156. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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.
- GSM8037771 A375 DMSO R1 [A1]
- GSM8037772 A375 5 uM A-485, 24 h R1 [A2]
- GSM8037773 IPC-298 DMSO R1 [A3]
- GSM8037774 IPC-298 5 uM A-485, 24 h R1 [A4]
- GSM8037775 CO79 DMSO R1 [A5]
- GSM8037776 CO79 5 uM A-485, 24 h R1 [A6]
- GSM8037777 A375 DMSO R2 [A7]
- GSM8037778 A375 5 uM A-485, 24 h R2 [A8]
- GSM8037779 IPC-298 DMSO R2 [A9]
- GSM8037780 IPC-298 5 uM A-485, 24 h R2 [A10]
- GSM8037781 CO79 DMSO R2 [A11]
- GSM8037782 CO79 5 uM A-485, 24 h R2 [A12]
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- GSE230489 RNA-sequencing of cutaneous melanoma and non-small cell lung cancer biopsies 38 samples same disease briefing · shares melanoma
- GSE100797 Mutational and neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma 25 samples same disease briefing · shares melanoma
- GSE12391 Melanoma: comparison between common nevi, radial/vertical growth phase melanoma, metastases and dysplastic nevi 114 samples same disease briefing · shares melanoma
- GSE134459 Genome-wide maps of transcriptomic and epigenomic state in melanoma cell lines 73 samples same disease briefing · shares melanoma
- GSE123728 Clinical and Immunologic Activity of a Single Dose of Neoadjuvant PD-1 Blockade and Predictors of Clinical Outcomes in Resectable Melanoma 24 samples same disease briefing · shares melanoma
- GSE91061 Molecular portraits of tumor mutational and micro-environmental sculpting by immune checkpoint blockade therapy 109 samples same disease briefing
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.