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SMYD5 regulates mRNA translation to promote gastric adenocarcinoma (GAC)

GSE238257 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/03/01 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
Topic
Gastric cancerThis series is part of our curated briefing on it.
Samples
12 samples: 12 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
SMYD5 methylation of rpL40 links ribosomal output to gastric cancerNature · 2024
Summary (written by the submitters)
Dysregulated transcription due to disruption in histone lysine methylation dynamics is an established contributor to tumorigenesis. However, whether analogous pathologic epigenetic mechanisms act directly on the ribosome to advance oncogenesis is unclear. Here we find that trimethylation of the core ribosomal protein L40 at lysine 22 (rpL40K22me3) by the lysine methyltransferase (KMT) SMYD5 regulates mRNA translation output to promote gastric adenocarcinoma (GAC) malignant progression with lethal peritoneal ascites.
Read the full summary ↓
A biochemical-proteomic strategy identifies the mono-ubiquitin fusion protein partner rpL40 as the principal physiologic substrate of SMYD5 across diverse samples. Inhibiting the SMYD5-rpL40K22me3 axis in GAC cell lines reprograms protein synthesis to attenuate oncogenic gene expression signatures. SMYD5 and rpL40K22me3 are upregulated in GAC patient samples and negatively correlate with clinical outcomes. SMYD5 ablation in vivo in familial and sporadic mouse models of malignant GAC blocks metastatic disease including peritoneal carcinomatosis (PC). Suppressing SMYD5 methylation of rpL40 inhibits human cancer cell and patient-derived GAC xenograft growth and renders them hypersensitive to PI3K/mTOR inhibitors. Finally, combining SMYD5 depletion with PI3K/mTOR inhibition and CAR-T administration cures an otherwise lethal in vivo mouse model of aggressive GAC-derived PC. Together, our work uncovers a ribosome-based epigenetic mechanism that facilitates evolution of malignant GAC and nominates SMYD5 targeting as part of a potential cornerstone combination therapy to treat a deadly cancer.
Published in
SMYD5 methylation of rpL40 links ribosomal output to gastric cancer
Park J, Wu J, Szkop KJ et al. · Nature 2024 · PMID 39048817 · doi:10.1038/s41586-024-07718-0
This dataset
Open GSE238257 in finder → Find more human RNA-seq datasets → Gastric cancer 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 GSE238257_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 PRJNA998464 and SRA study SRP451430. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39048817) ↗
Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 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.

Samples in this study
More Gastric cancer datasets

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