Extracellular matrix-myCAF signatures correlate with resistance to neoadjuvant aPD-L1 immune checkpoint inhibition with durvalumab + metformin in HPV+ HNSCC
RNA-seq (gene expression) · human · 18 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
- 18 samples: 18 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
- Extracellular Matrix-MYCAF Signatures Correlate with Resistance to Neoadjuvant aPD-L1 Immune Checkpoint Inhibition with Durvalumab + Metformin in HPV+ HNSCCClinical cancer research : an official journal of the American Association for Cancer Research · 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 GSE306800_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 PRJNA1312367 and SRA study SRP614547. 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 18 sample titles: 18 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.
- GSM9209498 TJU19_1 [Tumor] [HPVpos] [Baseline] [pre-treatment] [First of 2 time points]
- GSM9209499 TJU19_2 [Tumor] [HPVpos] [Surgery] [post treatment] [Second of 2 time points] [Primary Path Response_minor Respoder]
- GSM9209500 TJU02_1 [Tumor] [HPVpos] [Baseline] [pre-treatment] [First of 2 time points]
- GSM9209501 TJU02_2 [Tumor] [HPVpos] [Surgery] [post treatment] [Second of 2 time points] [Primary Path Response_minor Respoder]
- GSM9209502 TD36_1 [Tumor] [HPVpos] [Baseline] [pre-treatment] [First of 2 time points]
- GSM9209503 TD36_2 [Tumor] [HPVpos] [Surgery] [post treatment] [Second of 2 time points] [Primary Path Response_minor Respoder]
- GSM9209504 TJU16_1 [Tumor] [HPVpos] [Baseline] [pre-treatment] [First of 2 time points]
- GSM9209505 TJU16_2 [Tumor] [HPVpos] [Surgery] [post treatment] [Second of 2 time points] [Primary Path Response_minor Respoder]
- GSM9209506 TD5_1 [Tumor] [HPVpos] [Baseline] [pre-treatment] [First of 2 time points]
- GSM9209507 TD5_2 [Tumor] [HPVpos] [Surgery] [post treatment] [Second of 2 time points] [Primary Path Response_minor Respoder]
- GSM9209508 TJU10_1 [Tumor] [HPVpos] [Baseline] [pre-treatment] [First of 2 time points]
- GSM9209509 TJU10_2 [Tumor] [HPVpos] [Surgery] [post treatment] [Second of 2 time points] [Primary Path Response_Nonrespoder]
- GSM9209510 TJU11_1 [Tumor] [HPVpos] [Baseline] [pre-treatment] [First of 2 time points]
- GSM9209511 TJU11_2 [Tumor] [HPVpos] [Surgery] [post treatment] [Second of 2 time points] [Primary Path Response_Nonrespoder]
- GSM9209512 TD23_1 [Tumor] [HPVpos] [HPVpos] [Baseline] [pre-treatment] [First of 2 time points]
- GSM9209513 TD23_2 [HPVpos] [Tumor] [Surgery] [post treatment] [Second of 2 time points] [Primary Path Response_Nonrespoder]
- GSM9209514 TD43_1 [HPVpos] [Tumor] [Baseline] [pre-treatment] [First of 2 time points]
- GSM9209515 TD43_2 [HPVpos] [Tumor] [Surgery] [post treatment] [Second of 2 time points] [Primary Path Response_Nonrespoder]
- GSE162738 Immune gene signatures in oropharyngeal cancers are associated with inverse prognosis by HPV-status 51 samples same disease briefing · shares hpv, signatures
- 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, resistance
- GSE182227 Cellular states are coupled to genomic and viral heterogeneity in HPV-related oropharyngeal carcinoma 24 samples same disease briefing · shares hpv
- 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
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.