Distinct CD8+ T cell dynamics associate with response to neoadjuvant cancer immunotherapies
RNA-seq (gene expression) · human · 180 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
- Head and neck cancerThis series is part of our curated briefing on it.
- Samples
- 180 samples: 180 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
- Distinct CD8(+) T cell dynamics associate with response to neoadjuvant cancer immunotherapiesCancer cell · 2025
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 GSE288199_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 PRJNA1216557 and SRA study SRP560370. 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 180 sample titles: 180 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.
- GSM8761106 HN01 Pre Gene expression data
- GSM8761107 HN01 Pre CITE-Seq expression data
- GSM8761108 HN01 Pre TCR-Seq data
- GSM8761109 HN01 Post Gene expression data
- GSM8761110 HN01 Post CITE-Seq expression data
- GSM8761111 HN01 Post TCR-Seq data
- GSM8761112 HN02 Pre Gene expression data
- GSM8761113 HN02 Pre CITE-Seq expression data
- GSM8761114 HN02 Pre TCR-Seq data
- GSM8761115 HN02 Post Gene expression data
- GSM8761116 HN02 Post CITE-Seq expression data
- GSM8761117 HN02 Post TCR-Seq data
- GSM8761118 HN03 Pre Gene expression data
- GSM8761119 HN03 Pre CITE-Seq expression data
- GSM8761120 HN03 Pre TCR-Seq data
- GSM8761121 HN03 Post Gene expression data
- GSM8761122 HN03 Post CITE-Seq expression data
- GSM8761123 HN03 Post TCR-Seq data
- GSM8761124 HN04 Pre Gene expression data
- GSM8761125 HN04 Pre CITE-Seq expression data
- GSM8761126 HN04 Pre TCR-Seq data
- GSM8761127 HN04 Post Gene expression data
- GSM8761128 HN04 Post CITE-Seq expression data
- GSM8761129 HN04 Post TCR-Seq data
- GSM8761130 HN05 Pre Gene expression data
- GSM8761131 HN05 Pre CITE-Seq expression data
- GSM8761132 HN05 Pre TCR-Seq data
- GSM8761133 HN05 Post Gene expression data
- GSM8761134 HN05 Post CITE-Seq expression data
- GSM8761135 HN05 Post TCR-Seq data
- GSM8801565 HN06 Post Gene expression data
- GSM8801566 HN06 Post CITE-Seq expression data
- GSM8801567 HN06 Post TCR-Seq data
- GSM8801568 HN07 Post Gene expression data
- GSM8801569 HN07 Post CITE-Seq expression data
- GSM8801570 HN07 Post TCR-Seq data
- GSM8801571 HN08 Post Gene expression data
- GSM8801572 HN08 Post CITE-Seq expression data
- GSM8801573 HN08 Post TCR-Seq data
- GSM8801574 HN09 Pre Gene expression data
+ 140 more — browse all 180 samples with per-sample file links →
- GSE162738 Immune gene signatures in oropharyngeal cancers are associated with inverse prognosis by HPV-status 51 samples same disease briefing · shares associate
- 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 associate
- 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
- GSE181919 Single-cell transcriptome profiling of the stepwise progression of head and neck cancer 37 samples same disease briefing
- GSE145057 Establishment of a human tongue cancer organoid biobank enables early diagnosis, prognosis, and identification of therapeutic targets 25 samples same disease briefing
- GSE179424 Gigaxonin as a prognistic marker of human cancer 4 samples same disease briefing
- GSE164690 Investigating Immune and Non-Immune Cell Interactions in Head and Neck Tumors by Single-Cell RNA Sequencing 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.