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RNA-sequencing of primary human glioblastoma resected tissue before and after a personalized, neoantigen-based vaccine plus poly-ICLC (NeoVax); tissues from a Phase 1 clinical trial

GSE237936 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/04/12 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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)
Samples
12 samples: 3 × Subject_1_pre_NeoVax_region vs 3 × Subject_2_pre_NeoVax_region vs 2 × Subject_3_pre_NeoVax_region vs 2 × Subject_4_pre_NeoVax_regionGroups 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
Integrating Multisector Molecular Characterization into Personalized Peptide Vaccine Design for Patients with Newly Diagnosed GlioblastomaClinical cancer research : an official journal of the American Association for Cancer Research · 2024
Summary (written by the submitters)
Glioblastoma (GBM) patient outcomes remain low despite surgery, radiation, and chemotherapy. There are few immunotherapy options due to the lack of tumor immunogenicity. Several clinical trials have reported promising results with cancer vaccines, although most trials have used single tumor region sequencing to identify targetable antigens.
Read the full summary ↓
This approach limits the antigen pool due to the heterogeneity of GBM tumors. We have implemented multisector sequencing to identify targetable neoantigens across the GBM tumor landscape that were then incorporated into personalized peptide vaccines called NeoVax. Here, we report the findings of four subjects enrolled on the trial. Following NeoVax, we observed a clonal expansion of CD8+ T cells in the peripheral blood that, when expanded in vitro, were reactive to, on average, half of the NeoVax neoantigens tested by IFN-g ELISPOT, including BRAF V600E in one subject. A post-NeoVax tumor biopsy was resected from one subject and also showed evidence of infiltrating CD8+ T cell clonal expansion. Although the patients enrolled in this trial did not achieve remission, this pilot study demonstrates the feasibility of NeoVax and the importance of multisector sampling for neoantigen screening.
Published in
Integrating Multisector Molecular Characterization into Personalized Peptide Vaccine Design for Patients with Newly Diagnosed Glioblastoma
Johanns TM, Garfinkle EAR, Miller KE et al. · Clinical cancer research : an official journal of the American Association for Cancer Research 2024 · PMID 38639919 · doi:10.1158/1078-0432.CCR-23-3077
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 GSE237936_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 PRJNA997267 and SRA study SRP450776. Searching any of these in the dataset finder brings you back here.

Study design
3 × Subject_1_pre_NeoVax_region vs 3 × Subject_2_pre_NeoVax_region vs 2 × Subject_3_pre_NeoVax_region vs 2 × Subject_4_pre_NeoVax_region

Supports a between-group comparison across 10 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 10 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.

Samples in this study
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