GEO series

Inhibition of METTL3 by STC-15 induces RNA misprocessing that results in dsRNA formation and activates innate immunity [RNA-Seq dose_response]

GSE313114 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2026/05/13 Platform GPL34284

At a glance

RNA-seq (gene expression) · human · 21 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: 21 samples: 7 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.

Summary (written by the submitters)

The RNA methyltransferase METTL3 is responsible for the generation of m6A, the most abundant modification mark on mRNA and long non-coding RNA. Accumulating evidence suggests numerous roles of METTL3 in cancer initiation and progression and highlights the potential for targeting this enzyme in oncology. STC-15 is a potent and selective METTL3 inhibitor and the first RNA modifying enzyme inhibitor to enter human clinical development.

Read the full summary ↓

It is structurally related to the previously published tool inhibitors STM2457 and STM3675. We previously identified the induction of a cancer cell-intrinsic interferon response following pharmacological inhibition of METTL3, leading to activation of T-cell-mediated anti-tumour response. Here, we profiled m6A levels at nucleotide resolution using GLORI and characterised RNA changes following METTL3 inhibition with STC-15 or STM3675. Following loss of m6A, we uncovered aberrant mRNA transcripts arising from intron retention (IR) and transcriptional run-on (RO) events downstream of m6A-enriched exons in human cancer cells and in tumour samples in vivo. We found that these IR and RO events produce double-stranded RNA and are bound by the cytoplasmic dsRNA sensor MDA5.Using preclinical in vitro and in vivo models, we characterised in detail the anti-tumour immune responses induced by STC-15. Our study reveals how METTL3 inhibition leads to dsRNA accumulation, which triggers a type I interferon response and induces anti-tumour immunity. Together, these findings provide a mechanistic rationale for STC-15 as a novel anti-cancer drug both as monotherapy and in combination with anti-PD1 checkpoint inhibitors.

This dataset

Open GSE313114 in finder → Find more human 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 GSE313114_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 PRJNA1378551 and SRA study SRP653938. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

7 conditions, mostly in triplicate

CAOV3, DMSO, 24 h, ×3 CAOV3, 3 nM, 24 h, ×3 CAOV3, 10 nM, 24 h, ×3 CAOV3, 30 nM, 24 h, ×3 CAOV3, 100 nM, 24 h, ×3 CAOV3, 300 nM, 24 h, ×3 CAOV3, 1000 nM, 24 h, ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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

GSM9361309 CAOV3, DMSO, 24 h, rep1 CAOV3, DMSO, 24 h,
GSM9361310 CAOV3, 3 nM, 24 h, rep1 CAOV3, 3 nM, 24 h,
GSM9361311 CAOV3, 10 nM, 24 h, rep1 CAOV3, 10 nM, 24 h,
GSM9361312 CAOV3, 30 nM, 24 h, rep1 CAOV3, 30 nM, 24 h,
GSM9361313 CAOV3, 100 nM, 24 h, rep1 CAOV3, 100 nM, 24 h,
GSM9361314 CAOV3, 300 nM, 24 h, rep1 CAOV3, 300 nM, 24 h,
GSM9361315 CAOV3, 1000 nM, 24 h, rep1 CAOV3, 1000 nM, 24 h,
GSM9361316 CAOV3, DMSO, 24 h, rep2 CAOV3, DMSO, 24 h,
GSM9361317 CAOV3, 3 nM, 24 h, rep2 CAOV3, 3 nM, 24 h,
GSM9361318 CAOV3, 10 nM, 24 h, rep2 CAOV3, 10 nM, 24 h,
GSM9361319 CAOV3, 30 nM, 24 h, rep2 CAOV3, 30 nM, 24 h,
GSM9361320 CAOV3, 100 nM, 24 h, rep2 CAOV3, 100 nM, 24 h,
GSM9361321 CAOV3, 300 nM, 24 h, rep2 CAOV3, 300 nM, 24 h,
GSM9361322 CAOV3, 1000 nM, 24 h, rep2 CAOV3, 1000 nM, 24 h,
GSM9361323 CAOV3, DMSO, 24 h, rep3 CAOV3, DMSO, 24 h,
GSM9361324 CAOV3, 3 nM, 24 h, rep3 CAOV3, 3 nM, 24 h,
GSM9361325 CAOV3, 10 nM, 24 h, rep3 CAOV3, 10 nM, 24 h,
GSM9361326 CAOV3, 30 nM, 24 h, rep3 CAOV3, 30 nM, 24 h,
GSM9361327 CAOV3, 100 nM, 24 h, rep3 CAOV3, 100 nM, 24 h,
GSM9361328 CAOV3, 300 nM, 24 h, rep3 CAOV3, 300 nM, 24 h,
GSM9361329 CAOV3, 1000 nM, 24 h, rep3 CAOV3, 1000 nM, 24 h,

Datasets on a similar topic

GSE312942 Inhibition of METTL3 by STC-15 induces RNA misprocessing that results in dsRNA formation and activates innate immunity [RNA-seq] 36 samples shares mettl3, stc-15, misprocessing, inhibition, formation, activates, immunity, induces
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GSE303446 Beyond CD30 Targeting: Brentuximab Vedotin Triggers Immunogenic Cell Death and Antitumor Immunity in Mycosis Fungoides, Overcoming Resistance via BCL2 Inhibition 13 samples shares inhibition, immunity
GSE312197 MEK inhibition induces AXIN1 loss in colorectal cancer by mTOR associated suppression of protein synthesis 66 samples shares inhibition, induces
GSE295261 CDK4/6 inhibition induces a senescence-associated secretory phenotype via delayed NF-κB activation [CUT&Tag] 24 samples shares inhibition, induces
GSE303106 Prolonged KRAS-MAPK Inhibition Induces Interferon-mediated Epithelial-to-Mesenchymal Transition and Reveals Therapeutic Opportunities [cut and run-ChipSeq] 9 samples shares inhibition, induces

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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.