Post-treatment peripheral-blood T cells from HNSCC patients undergoing neoadjuvant immunotherapy treatment.
Single-cell RNA-seq · human · 22 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)
- Topic
- Head and neck cancerThis series is part of our curated briefing on it.
- Samples
- 22 samples: 22 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.
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 GSE296867_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: 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 PRJNA1261848 and SRA study SRP584589. 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 22 sample titles: 22 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.
- GSM8978873 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 1B
- GSM8978874 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 2B
- GSM8978875 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 5B
- GSM8978876 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 8B
- GSM8978877 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 12B
- GSM8978878 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 14B
- GSM8978879 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 17B
- GSM8978880 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 18B
- GSM8978881 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 19B
- GSM8978882 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 20B
- GSM8978883 scRNA-seq of post-treatment peripheral-blood T cells from HNSCC patients; 21B
- GSM8978884 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 1B
- GSM8978885 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 2B
- GSM8978886 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 5B
- GSM8978887 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 8B
- GSM8978888 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 12B
- GSM8978889 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 14B
- GSM8978890 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 17B
- GSM8978891 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 18B
- GSM8978892 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 19B
- GSM8978893 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 20B
- GSM8978894 scVDJ-seq of post-treatment peripheral-blood T cells from HNSCC patients; 21B
- GSE114446 Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines 33 samples same disease briefing · shares hnscc
- GSE185965 Single cell RNA sequencing of head and neck squamous carcinoma (HNSCC) patient sample 3 samples same disease briefing · shares hnscc
- GSE132627 RNA-seq analysis of CD276-high/EpCAM+ cells from HNSCC patient-derived-xenograft 2 samples same disease briefing · shares hnscc
- GSE172146 Aberrant translation regulation by METTL1/WDR4-mediated tRNA N7-methylguanosine modification drives HNSCC progression 28 samples same disease briefing · shares hnscc
- GSE173161 Comparative analysis of gene expression after Oct4 or Scrambled siRNA knockdown in HNSCC cell lines 18 samples same disease briefing · shares hnscc
- GSE103322 Single cell RNA-seq analysis of head and neck cancer 5901 samples same disease briefing
- GSE139324 Immune landscape of viral- and carcinogen-drived head and neck cancer 63 samples same disease briefing
- GSE162738 Immune gene signatures in oropharyngeal cancers are associated with inverse prognosis by HPV-status 51 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.