← BioTransfer GEO Dataset Finder
GEO series

p300 catalytic inhibition selectively targets IRF4 oncogenic activity in multiple myeloma (DF_pt)

GSE274596 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2025/10/20 Platform GPL24676
Summary
The oncogenic transcription factor (TF) IRF4 is a universal multiple myeloma (MM) dependency that remains undrugged owing to its disordered structure. Using transcriptional regulatory network (TRN) mapping, an unbiased multi-omic approach to nominate druggable TF cofactors, we identified the chromatin coactivator lysine acetyltransferase (KAT) p300 as a key IRF4 partner. We developed KB528, a highly selective p300 KAT inhibitor to explore the regulatory relationship between IRF4 and p300. Instead of broadly inhibiting transcription, partial p300 KAT inhibition selectively downregulates IRF4 and its downstream gene expression program leading to apoptosis selectively in MM cells. IRF4 dependency is a hallmark of MM that exists downstream of existing MM therapies. Consequently, p300 KAT inhibition exhibits strong antiproliferative activity ex vivo and in vivo as a single agent as well as in combination regimens in treatment refractory models. p300 KAT inhibition is well-tolerated in vivo motivating further clinical development in MM.
Published in
Catalytic Inhibition of p300 Preferentially Targets IRF4 Oncogenic Activity and Tumor Growth in Multiple Myeloma
Lenoir WF, McKeown MR, Giorgetti G et al. · Cancer research 2026 · PMID 41248492 · doi:10.1158/0008-5472.CAN-25-3440
This dataset
Download

Direct links to NCBI, no account and no request form: the whole study as GSE274596_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1147264 and SRA study SRP525927. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Sort into groups and it will be fetched from NCBI.

+ 6 more — browse all 6 samples with per-sample file links →

Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.