Measles oncolytic virus as an immunotherapy for recurrent/refractory pediatric medulloblastoma and atypical teratoid rhabdoid tumor: results from PNOC005
Single-cell RNA-seq · human · 84 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Topic
- MedulloblastomaThis series is part of our curated briefing on it.
- Samples
- 84 samples: 84 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
- Measles Oncolytic Virus as an Immunotherapy for Recurrent/Refractory Pediatric Medulloblastoma and Atypical Teratoid/Rhabdoid Tumor: Results from PNOC005Clinical 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 GSE294901_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1252019. 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 84 sample titles: 84 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.
- GSM8928015 PNOC005-01_D00, RNAexome
- GSM8928016 PNOC005-01_D01, RNAexome
- GSM8928017 PNOC005-01_D04, RNAexome
- GSM8928018 PNOC005-01_D07, RNAexome
- GSM8928019 PNOC005-01_D14, RNAexome
- GSM8928020 PNOC005-01_D28, RNAexome
- GSM8928021 PNOC005-05_D00, RNAexome
- GSM8928022 PNOC005-05_D01, RNAexome
- GSM8928023 PNOC005-05_D04, RNAexome
- GSM8928024 PNOC005-05_D07, RNAexome
- GSM8928025 PNOC005-05_D14, RNAexome
- GSM8928026 PNOC005-05_D28, RNAexome
- GSM8928027 PNOC005-06_D00, RNAexome
- GSM8928028 PNOC005-06_D01, RNAexome
- GSM8928029 PNOC005-06_D04, RNAexome
- GSM8928030 PNOC005-06_D07, RNAexome
- GSM8928031 PNOC005-06_D14, RNAexome
- GSM8928032 PNOC005-06_D28, RNAexome
- GSM8928033 PNOC005-13_D00, RNAexome
- GSM8928034 PNOC005-13_D14, RNAexome
- GSM8928035 PNOC005-13_D28, RNAexome
- GSM8928036 PNOC005-08_D00, bulkRNA
- GSM8928037 PNOC005-08_D01, bulkRNA
- GSM8928038 PNOC005-08_D04, bulkRNA
- GSM8928039 PNOC005-08_D14, bulkRNA
- GSM8928040 PNOC005-08_D28, bulkRNA
- GSM8928041 PNOC005-09_D00, bulkRNA
- GSM8928042 PNOC005-09_D14, bulkRNA
- GSM8928043 PNOC005-09_D28, bulkRNA
- GSM8928044 PNOC005-12_D00, bulkRNA
- GSM8928045 PNOC005-12_D01, bulkRNA
- GSM8928046 PNOC005-12_D04, bulkRNA
- GSM8928047 PNOC005-12_D07, bulkRNA
- GSM8928048 PNOC005-12_D14, bulkRNA
- GSM8928049 PNOC005-12_D28, bulkRNA
- GSM8928050 PNOC005-14_D00, bulkRNA
- GSM8928051 PNOC005-14_D01, bulkRNA
- GSM8928052 PNOC005-14_D04, bulkRNA
- GSM8928053 PNOC005-14_D07, bulkRNA
- GSM8928054 PNOC005-14_D14, bulkRNA
+ 44 more — browse all 84 samples with per-sample file links →
- GSE269909 Divergent medulloblastoma chromatin states disclose KDM2B as a selective dependency [RNA-Seq] 50 samples same disease briefing · shares medulloblastoma
- GSE323995 CReP-mediated control of eIF2a phosphorylation is a central node in high-risk medulloblastoma [RNA-Seq 3] 48 samples same disease briefing · shares medulloblastoma
- GSE253557 Single-nuclei RNA-Seq profiles from Group 3 and Group 4 medulloblastomas [scRNA-Seq] 39 samples same disease briefing · shares medulloblastoma
- GSE318970 Metabolic Dependencies in Medulloblastoma Reflect Underlying Cellular Origins 33 samples same disease briefing · shares medulloblastoma
- GSE229150 The transcription factor LHX2 mediates and enhances oncogenic BMP signaling in medulloblastoma 30 samples same disease briefing · shares medulloblastoma
- GSE241602 Dynamic Chromatin Alteration Induces Oncogenic Hijacking by Nuclear Factor I Family Proteins for Medulloblastoma Progression 30 samples same disease briefing · shares medulloblastoma
- GSE206899 Prtg+ve Rhombic Lip Ventricular Zone Stem Cells Initiate and Maintain Group 3 Medulloblastoma. 24 samples same disease briefing · shares medulloblastoma
- GSE267469 Dual targeting of processive transcription for Myc-driven circuitry in medulloblastoma [RNA-seq] 24 samples same disease briefing · shares medulloblastoma
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.