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Small-molecule Inhibition of METTL3 Suppresses Tumor Growth and Promotes Neuroblastoma Differentiation [RNA-Seq Decay]

GSE240581 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2024/04/10 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 48 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)
Samples
48 samples: 20 conditions, mostly in duplicateGroups 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
Small-molecule inhibition of the METTL3/METTL14 complex suppresses neuroblastoma tumor growth and promotes differentiationCell reports · 2024
Summary (written by the submitters)
The N6-methyladenosine (m6A) RNA modification is an important regulator of gene expression. m6A is deposited by a methyltransferase complex that includes methyltransferase-like 3 (METTL3) and methyltransferase-like 14 (METTL14). High levels of METTL3 and METTL14 drive the growth of many types of adult cancer, and METTL3/METTL14 inhibitors are emerging as new anticancer agents.
Read the full summary ↓
However, little is known about the m6A epitranscriptome or the role of the METTL3/METTL14 complex in neuroblastoma, a common pediatric cancer. Here, we show that METTL3 knockdown or pharmacologic inhibition with the small molecule STM2457 leads to reduced neuroblastoma cell proliferation and increased differentiation. These changes in neuroblastoma phenotype were associated with decreased m6A deposition on transcripts involved in nervous system development and neuronal differentiation and increased stability and expression of target mRNAs. In preclinical studies, STM2457 treatment suppressed the growth of neuroblastoma tumors in vivo. Together, these results support the potential of METTL3/METTL14 complex inhibition as therapeutic strategy against neuroblastoma.
Published in
Small-molecule inhibition of the METTL3/METTL14 complex suppresses neuroblastoma tumor growth and promotes differentiation
Pomaville M, Chennakesavalu M, Wang P et al. · Cell reports 2024 · PMID 38691450 · doi:10.1016/j.celrep.2024.114165
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 GSE240581_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 PRJNA1004269 and SRA study SRP454495. Searching any of these in the dataset finder brings you back here.

Study design
20 conditions, mostly in duplicate
Kelly cells, DMSO, 3D, 0h, ×2 Kelly cells, DMSO, 3D, 3h, ×2 Kelly cells, STM, 3D, 0h, ×2 Kelly cells, STM, 3D, 3h, ×2 Kelly cells, DMSO, 3D, 6h, ×2 Kelly cells, STM, 3D, 6h, ×2 Kelly cells, DMSO, 6D, 0h, ×2 Kelly cells, STM, 6D, 0h, ×2 +20 more

Supports a between-group comparison across 40 samples.

How we read this: 20 replicated groups read from 48 sample titles; they account for 40 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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