GEO series

PP2A Regulates Senescence and Immunogenicity in Medulloblastoma

GSE302307 Mus musculus (mouse) Single-cell RNA-seq 24 samples Submitted 2026/04/11 Platform GPL24676Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 24 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: Mus musculus (mouse)
Topic: MedulloblastomaThis series is part of our curated briefing on it.
Samples: 24 samples: 8 conditions, mostly in triplicateGroups 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: Protein phosphatase 2A regulates senescence and immunogenicity in medulloblastoma modelsThe Journal of clinical investigation · 2026

Summary (written by the submitters)

Medulloblastoma (MB) is the most common malignant pediatric brain tumor. Current treatments carry significant morbidity, and prognosis remains poor in subgroups with TP53 mutations or relapse, underscoring the need for new therapeutic strategies. Senescence is a tumor-suppressive program disrupted in MB. We hypothesized that restoring senescence through p53-independent mechanisms could be therapeutic.

Read the full summary ↓

Here, we identify Protein Phosphatase 2A (PP2A) as a key regulator of senescence in MB. Genetic ablation of the PP2A catalytic subunit (PP2Ac) or knockdown of the regulatory subunit PP2A-B56α induces robust senescence in TP53-mutant MB models. Senescent PP2Ac-deficient cells show increased MHC-I expression and enhanced immunogenicity. In a syngeneic orthotopic model, PP2Ac loss prolongs survival in an immune- and CD8-dependent manner, indicating enhanced immune-mediated tumor clearance. Analysis of MB patient datasets links senescence signatures with improved survival, and integrative single-cell analysis reveals reduced PP2A activity in immunogenic senescent clusters. Although the PP2A inhibitor LB-100 is under clinical investigation, it fails to cross the blood-brain barrier. To overcome this, we developed a lipid nanoparticle (LNP) formulation delivering siRNA against PP2Ac. LNP-siPP2Ac efficiently silences PP2Ac in vitro and, when locally delivered in vivo, extends survival and increases tumor MHC-I expression. These findings establish PP2A as a central modulator of senescence and immunogenicity in MB and support a therapeutic strategy that induces tumor cell senescence and enhances anti-tumor immunity for treatment of MB.

Published in

Protein phosphatase 2A regulates senescence and immunogenicity in medulloblastoma models

Ho WS, Mondal I, Liu J et al. · The Journal of clinical investigation 2026 · PMID 42085538 · doi:10.1172/JCI196753

This dataset

Open GSE302307 in finder → Find more RNA-seq datasets → Medulloblastoma landscape →

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.

Series matrix ↓

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 GSE302307_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

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.

Raw reads on ENA ↗

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 PRJNA1289839 and SRA study SRP600913. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42085538) ↗

Study design

8 conditions, mostly in triplicate

D425_PP2A_KO_NT ×3 D425_PP2A_KO_RT ×3 D425_PP2A_WT_NT ×3 D425_PP2A_WT_RT ×3 SJ_PP2A_WT ×3 SJ_PP2A_KO ×3 CTD_PP2A_WT ×3 CTD_PP2A_KO ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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

GSM9101642 D425_PP2A_KO_NT_rep1 D425_PP2A_KO_NT
GSM9101643 D425_PP2A_KO_NT_rep2 D425_PP2A_KO_NT
GSM9101644 D425_PP2A_KO_NT_rep3 D425_PP2A_KO_NT
GSM9101645 D425_PP2A_KO_RT_rep1 D425_PP2A_KO_RT
GSM9101646 D425_PP2A_KO_RT_rep2 D425_PP2A_KO_RT
GSM9101647 D425_PP2A_KO_RT_rep3 D425_PP2A_KO_RT
GSM9101648 D425_PP2A_WT_NT_rep1 D425_PP2A_WT_NT
GSM9101649 D425_PP2A_WT_NT_rep2 D425_PP2A_WT_NT
GSM9101650 D425_PP2A_WT_NT_rep3 D425_PP2A_WT_NT
GSM9101651 D425_PP2A_WT_RT_rep1 D425_PP2A_WT_RT
GSM9101652 D425_PP2A_WT_RT_rep2 D425_PP2A_WT_RT
GSM9101653 D425_PP2A_WT_RT_rep3 D425_PP2A_WT_RT
GSM9101654 SJ_PP2A_WT_rep1 SJ_PP2A_WT
GSM9101655 SJ_PP2A_WT_rep2 SJ_PP2A_WT
GSM9101656 SJ_PP2A_WT_rep3 SJ_PP2A_WT
GSM9101657 SJ_PP2A_KO_rep1 SJ_PP2A_KO
GSM9101658 SJ_PP2A_KO_rep2 SJ_PP2A_KO
GSM9101659 SJ_PP2A_KO_rep3 SJ_PP2A_KO
GSM9581751 CTD_PP2A_WT_rep1 CTD_PP2A_WT
GSM9581752 CTD_PP2A_WT_rep2 CTD_PP2A_WT
GSM9581753 CTD_PP2A_WT_rep3 CTD_PP2A_WT
GSM9581754 CTD_PP2A_KO_rep1 CTD_PP2A_KO
GSM9581755 CTD_PP2A_KO_rep2 CTD_PP2A_KO
GSM9581756 CTD_PP2A_KO_rep3 CTD_PP2A_KO

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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.