Engineering a novel HSV-1 strain for oncolytic therapy of solid tumors
RNA-seq (gene expression) · human · 16 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
- 16 samples: 4 × GBM12 cells, PBS vs 4 × GBM12 cells, OncoD vs 4 × GBM28 cells, PBS vs 4 × GBM28 cells, OncoDGroups 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
- Engineering a novel HSV-1 strain for oncolytic therapy of solid tumorsMolecular therapy. Oncology · 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 GSE288846_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 PRJNA1219598 and SRA study SRP561772. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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.
- GSM8776750 GBM12 cells, PBS-1 GBM12 cells, PBS
- GSM8776751 GBM12 cells, PBS-2 GBM12 cells, PBS
- GSM8776752 GBM12 cells, PBS-3 GBM12 cells, PBS
- GSM8776753 GBM12 cells, PBS-4 GBM12 cells, PBS
- GSM8776754 GBM12 cells, OncoD-1 GBM12 cells, OncoD
- GSM8776755 GBM12 cells, OncoD-2 GBM12 cells, OncoD
- GSM8776756 GBM12 cells, OncoD-3 GBM12 cells, OncoD
- GSM8776757 GBM12 cells, OncoD-4 GBM12 cells, OncoD
- GSM8776758 GBM28 cells, PBS-1 GBM28 cells, PBS
- GSM8776759 GBM28 cells, PBS-2 GBM28 cells, PBS
- GSM8776760 GBM28 cells, PBS-3 GBM28 cells, PBS
- GSM8776761 GBM28 cells, PBS-4 GBM28 cells, PBS
- GSM8776762 GBM28 cells, OncoD-1 GBM28 cells, OncoD
- GSM8776763 GBM28 cells, OncoD-2 GBM28 cells, OncoD
- GSM8776764 GBM28 cells, OncoD-3 GBM28 cells, OncoD
- GSM8776765 GBM28 cells, OncoD-4 GBM28 cells, OncoD
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- GSE222556 Neoadjuvant PARPi or Chemotherapy in Ovarian Cancer Informs Targeting Effector Treg Cells for Homologous-Recombination-Deficient Tumors [10x scRNA-seq] 67 samples shares therapy
- GSE271689 Enhancing Immunotherapy Outcomes: Spatial Multi-Omics Predictive Models for Non-Small Cell Lung Cancer 586 samples shares therapy
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- GSE222557 Neoadjuvant PARPi or Chemotherapy in Ovarian Cancer Informs Targeting Effector Treg Cells for Homologous-Recombination-Deficient Tumors 148 samples shares therapy
- GSE330098 Multi-tissue microphysiological system captures integrated responses to nutritional overload and metabolic therapy 108 samples shares therapy
- GSE253173 Coupling of response biomarkers between tumour and peripheral blood in patients undergoing chemoimmunotherapy II 100 samples shares therapy
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.