GEO series
Response-Adaptive Surgical Timing in neoadjuvant immunotherapy demonstrates enhanced pathologic treatment response in Head and Neck Squamous Cell Carcinoma
GSE281729
Homo sapiens (human)
RNA-seq (gene expression)
67 samples
Submitted 2024/11/20
Platform GPL24676
At a glance
RNA-seq (gene expression) · human · 67 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
- 67 samples: 67 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
- Response-Adaptive Surgical Timing in Neoadjuvant Immunotherapy Demonstrates Enhanced Pathologic Treatment Response in Head and Neck Squamous Cell CarcinomaClinical cancer research : an official journal of the American Association for Cancer Research · 2025
Summary (written by the submitters)
Abstract: Purpose: We evaluated whether IDO-inhibitor BMS986205 (IDOi) + PD-1 inhibitor nivolumab enhanced T-cell activity and augmented immune-mediated antitumor responses in untreated, resectable HNSCC. We employed response-adaptive surgical timing to identify responders to immunotherapy and enhance their response. Patients and Methods: Patients with HNSCC were 3:1 randomized to receive nivolumab with or without BMS986205 PO daily (NCT03854032).
Read the full summary ↓
In the combination arm, BMS986205 was initiated 7 days prior to nivolumab. Patients were stratified by HPV status. Response-adaptive surgical timing involved response assessment by radiographic criteria 4 weeks after nivolumab in both arms. Non-responders underwent surgical resection, while responders received 4 more weeks of randomized therapy before surgery. Biomarker analysis utilized pathologic treatment response (pTR) and RNA sequencing. Results: Forty-two patients were enrolled, and the addition of IDOi to nivolumab did not result in greater rate of radiographic response (p=0.909). Treatment was well-tolerated with only 2 (5%) patients experiencing grade 3 immune-related adverse events. The addition of IDO-inhibitor augmented rates of pTR in patients with high baseline IDO RNA expression (p<0.05). Response-adaptive surgical timing demonstrated reliability in differentiating pathologic responders versus non-responders (p=0.009). A pretreatment NK cell signature, PD-L1 status, and IFN-g expression in the HPV– cohort correlated with response. HPV+ cohort found B-cell and CAF signatures predictive of response/non-response. Conclusions: Response-adaptive surgical timing enhanced treatment response. IDO-inhibitor BMS986205 augmented pTR in patients with high IDO1-expression in baseline samples, indicating a need for identifying and targeting resistant nodes to immunotherapy. HPV-status-dependent signatures predicting response to immunotherapy in HNSCC warrant further study.
Published in
Mastrolonardo EV, Nunes KL, Llerena P et al.
· Clinical cancer research : an official journal of the American Association for Cancer Research 2025
· PMID 39585339
· doi:10.1158/1078-0432.CCR-24-0037
This dataset
Download · which file do I need?
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.
1 · Just have a look
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.
2 · Re-analyse it
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE281729_RAW.tar (it can run to tens of gigabytes).
3 · Start from the raw reads
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 PRJNA1185379 and SRA study SRP544813. Searching any of these in the dataset finder brings you back here.
Study design
67 samples, each with a distinct title — no replicated groups
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 67 sample titles: 67 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.
Samples in this study
- GSM8627028 NI_TJ3_01_1 [Tumor] [Baseline]
- GSM8627029 NI_TJ3_01_3 [Tumor] [Surgery] [Primary Path Response_minor Respoder]
- GSM8627030 NI_TJ3_02_1 [Tumor] [Baseline]
- GSM8627031 NI_TJ3_02_2 [Tumor] [Surgery] [Primary Path Response_minor Responder]
- GSM8627032 NI_TJ3_04_1 [Tumor] [Baseline]
- GSM8627033 NI_TJ3_04_2 [Tumor] [Surgery] [Primary Path Response_Complete Responder]
- GSM8627034 NI_TJ3_06_1 [Tumor] [Baseline]
- GSM8627035 NI_TJ3_06_3 [Tumor] [Surgery] [Primary Path Response_Non-Responder]
- GSM8627036 NI_TJ3_08_1 [Tumor] [Baseline]
- GSM8627037 NI_TJ3_08_2 [Tumor] [Surgery] [Primary Path Response_minor Respoder]
- GSM8627038 NI_TJ3_09_1 [Tumor] [Baseline] [Not a matched pair.]
- GSM8627039 NI_TJ3_11_1 [Tumor] [Baseline] [Not a matched pair.]
- GSM8627040 NI_TJ3_12_1 [Tumor] [Baseline]
- GSM8627041 NI_TJ3_12_2 [Tumor] [Surgery] [Primary Path Response_Non-Responder]
- GSM8627042 NI_TJ3_13_1 [Tumor] [Baseline]
- GSM8627043 NI_TJ3_13_2 [Tumor] [Surgery] [Primary Path Response_Respoder]
- GSM8627044 NI_TJ3_15_1 [Tumor] [Baseline]
- GSM8627045 NI_TJ3_15_2 [Tumor] [Surgery] [Primary Path Response_Respoder]
- GSM8627046 NI_TJ3_16_1 [Tumor] [Baseline]
- GSM8627047 NI_TJ3_16_4 [Tumor] [Surgery] [Primary Path Response_Complete Respoder]
- GSM8627048 NI_TJ3_17_1 [Tumor] [Baseline]
- GSM8627049 NI_TJ3_17_2 [Tumor] [Surgery] [Primary Path Response_Complete Respoder]
- GSM8627050 NI_TJ3_19_1 [Tumor] [Baseline]
- GSM8627051 NI_TJ3_19_3 [Tumor] [Surgery] [Primary Path Response_Respoder]
- GSM8627052 NI_TJ3_20_1 [Tumor] [Baseline]
- GSM8627053 NI_TJ3_20_2 [Tumor] [Surgery] [Primary Path Response_Non-Responder]
- GSM8627054 NI_TJ3_22_1 [Tumor] [Baseline]
- GSM8627055 NI_TJ3_22_2 [Tumor] [Surgery] [Primary Path Response_Respoder]
- GSM8627056 NI_TJ3_23_1 [Tumor] [Baseline]
- GSM8627057 NI_TJ3_23_3 [Tumor] [Surgery] [Primary Path Response_minor Respoder]
- GSM8627058 NI_TJ3_24_1 [Tumor] [Baseline]
- GSM8627059 NI_TJ3_24_2 [Tumor] [Surgery] [Primary Path Response_Non-Responder]
- GSM8627060 NI_TJ3_27_1 [Tumor] [Baseline]
- GSM8627061 NI_TJ3_27_2 [Tumor] [Surgery] [Primary Path Response_Non-Respoder]
- GSM8627062 NI_TJ3_28_1 [Tumor] [Baseline]
- GSM8627063 NI_TJ3_28_2 [Tumor] [Surgery] [Primary Path Response_Non-Respoder]
- GSM8627064 NI_TJ3_29_1 [Tumor] [Baseline]
- GSM8627065 NI_TJ3_29_3 [Tumor] [Surgery] [Primary Path Response_Complete Respoder]
- GSM8627066 NI_TJ3_31_1 [Tumor] [Baseline] [Not a matched pair.]
- GSM8627067 NI_TJ3_33_1 [Tumor] [Baseline]
+ 27 more — browse all 67 samples with per-sample file links →
More Head and neck cancer datasets
- 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
- GSE164690 Investigating Immune and Non-Immune Cell Interactions in Head and Neck Tumors by Single-Cell RNA Sequencing 51 samples same disease briefing
- GSE181919 Single-cell transcriptome profiling of the stepwise progression of head and neck cancer 37 samples same disease briefing
- 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
- GSE145057 Establishment of a human tongue cancer organoid biobank enables early diagnosis, prognosis, and identification of therapeutic targets 25 samples same disease briefing
- GSE182227 Cellular states are coupled to genomic and viral heterogeneity in HPV-related oropharyngeal carcinoma 24 samples same disease briefing
Share this dataset
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.