GEO series

In vivo CRISPR screens identify dual functions of DNMT3A in mediating tumor immune evasion

GSE338899 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/07/31 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 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: Mus musculus (mouse)
Samples: 12 samples: 3 × sgDnmt_3a vs 3 × sgNTC vs 3 × CD8 T Cells Zymosterol vs 3 × CD8 T Cells ControlGroups 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.

Summary (written by the submitters)

Cancer immunotherapy has achieved remarkable clinical efficacy across multiple cancers, but it remains ineffective for most patients and the resistance mechanisms remain elusive. Epigenetic regulators play pivotal roles in both tumorigenesis and the modulation of antitumor immunity. Here, we performed in vivo CRISPR-Cas9 screens targeting epigenetic regulators and identified DNMT3A as a key driver of tumor immune evasion, exerting its effects through both methyltransferase activity-dependent and -independent mechanisms.

Read the full summary ↓

Mechanistically, DNMT3A repressed the expression of TNFRSF1A and TNFRSF1B in a methyltransferase activity-dependent manner, enabling tumor cells to evade TNFα-induced killing. Importantly, DNMT3A exerted an additional noncanonical function by interacting with NFYA to activate cholesterol biosynthesis-related genes. This led to the accumulation of zymosterol in the tumor interstitial fluid, which directly impaired SREBP2 cleavage and enhanced HMGCR degradation in CD8⁺ T cells. Consequently, zymosterol-mediated suppression of cholesterol biosynthesis in CD8⁺ T cells compromised their activation and antitumor effector functions. Targeting DNMT3A’s multifaceted functions with antisense oligonucleotides (ASOs) effectively overcame resistance to immune checkpoint blockade (ICB) therapy. Collectively, our findings uncover a dual role of DNMT3A in tumor immune evasion and establish it as an integrated epigenetic and metabolic checkpoint, thus providing a potential target for immunotherapy.

This dataset

Open GSE338899 in finder → Find more mouse RNA-seq datasets →

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 GSE338899_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: 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 PRJNA1496334 and SRA study SRP718589. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × sgDnmt_3a vs 3 × sgNTC vs 3 × CD8 T Cells Zymosterol vs 3 × CD8 T Cells Control

Supports a between-group comparison across 12 samples.

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

GSM9884429 sgDnmt_3a_1 sgDnmt_3a
GSM9884430 sgDnmt_3a_2 sgDnmt_3a
GSM9884431 sgDnmt_3a_3 sgDnmt_3a
GSM9884432 sgNTC_1 sgNTC
GSM9884433 sgNTC_2 sgNTC
GSM9884434 sgNTC_3 sgNTC
GSM9884435 CD8 T Cells Zymosterol_1 CD8 T Cells Zymosterol
GSM9884436 CD8 T Cells Zymosterol_2 CD8 T Cells Zymosterol
GSM9884437 CD8 T Cells Zymosterol_3 CD8 T Cells Zymosterol
GSM9884438 CD8 T Cells Control_1 CD8 T Cells Control
GSM9884439 CD8 T Cells Control_2 CD8 T Cells Control
GSM9884440 CD8 T Cells Control_3 CD8 T Cells Control

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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.