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EZH2 loss promotes gastric squamous cell carcinoma [RNA-seq]

GSE254316 Mus musculus (mouse) RNA-seq (gene expression) 22 samples Submitted 2025/05/18 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 22 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
22 samples
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)
Gastric Squamous Cell Carcinoma (GSCC) is a rare subtype of gastric cancer with unique histopathology while gastric adenosquamous carcinoma (GASC), which partially shares features of GSCC, is more frequent. Both GSCC and GASC have poor prognosis but the molecular mechanisms underlying these malignancies are unknown. Here, we performed genomics analyses of eleven GSCC samples and found that epigenetic regulation genes were among the most frequently mutated genes.
Read the full summary ↓
Among them was Enhancer of zeste homolog 2 (EZH2), which was also significantly downregulated in GASC, compared to gastric adenocarcinoma (GAC). Ezh2 loss led to squamous feature both in gastric organoids in vitro and in vivo. Importantly, Ezh2 deficiency, together with Trp53 and Pten loss, both of which were also frequently mutated in GSCC, gave rise to full-blown GSCC in mice. Mechanistically, we found that Ezh2 could repress the expression of Transcription factor AP-2 gamma (Tfap2c), a transcription factor with the ability to initiate epidermal squamous differentiation, through H3K27 methylation. Disruption of Tfap2c reversed Ezh2 loss-driven GSCC into GAC and reduced its resistance to chemo treatment. Our study revealed the mechanisms of GSCC/GASC tumorigenesis and shed light on future treatment.
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 GSE254316_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 PRJNA1069735 and SRA study SRP486142. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 22 more — browse all 22 samples with per-sample file links →

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