RNA sequencing of 15 patient derived cSCC cell lines
RNA-seq (gene expression) · human · 15 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
- Cutaneous squamous cell carcinomaThis series is part of our curated briefing on it.
- Samples
- 15 samples: 5 × IC vs 5 × T vs 3 × METGroups 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
- The landscape of long noncoding RNA during cutaneous squamous cell carcinoma progressionThe British journal of dermatology · 2025
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 GSE266912_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 PRJNA1108706 and SRA study SRP506186. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 13 samples.
How we read this: 3 replicated groups read from 15 sample titles; they account for 13 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.
- GSM8256370 IC12 IC
- GSM8256371 IC18 IC
- GSM8256372 IC19 IC
- GSM8256373 IC1MET
- GSM8256374 IC1 IC
- GSM8256375 IC8 IC
- GSM8256376 MET1 MET
- GSM8256377 MET2 MET
- GSM8256378 MET4 MET
- GSM8256379 PM1
- GSM8256380 T10 T
- GSM8256381 T11 T
- GSM8256382 T2 T
- GSM8256383 T8 T
- GSM8256384 T9 T
- GSE252347 RNA-Seq of human cutaneous squamous cell carcinoma cell lines and normal human epidermal keratinocytes. 12 samples same disease briefing · shares lines
- GSE300270 Loss of WWOX Drives Cutaneous Squamous Cell Carcinoma (cSCC) through Regulating EMT 24 samples same disease briefing · shares cscc
- GSE284467 Multi-omic Sequencing of Intermediate to High-Risk Cutaneous Squamous Cell Carcinoma Identifies Critical Genes and Expression Patterns Associated with Disease and Poor Outcomes 75 samples same disease briefing
- GSE319969 Spatial and Bulk Transcriptomic Profiling Defines the Molecular Evolution of Cutaneous Squamous Cell Carcinoma and Reveals Stage-Specific Biomarkers of Clinical Relevance [RNA-Seq] 24 samples same disease briefing
- GSE314399 The human Flower isoform hFWE4 facilitates cornification in cutaneous squamous cell carcinoma 23 samples same disease briefing
- GSE326341 Characterization of a Human Cutaneous Squamous Cell Carcinoma Xenograft Mouse Model 20 samples same disease briefing
- GSE260920 Loss of DUSP1 expression creates a cold tumor microenvironment in cutaneous squamous cell carcinoma 17 samples same disease briefing
- GSE200334 Single cell transcriptomes of genetic landscape from actinic keratosis to cutaneous squamous cell carcinoma 14 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.