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Selective NSD2 Inhibition Reveals an Epigenetic Vulnerability of KRAS-Driven Cancers [CUT&Run]

GSE273490 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 120 samples Submitted 2025/04/12 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 120 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Topic
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
120 samples: 59 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.
Summary (written by the submitters)
NSD2, through generation of the epigenetic modification histone H3 di-methylated at lysine 36 (H3K36me2), is a candidate convergent downstream effector of oncogenic KRAS-signaling. However, whether NSD2 targeting represents a therapeutic vulnerability of KRAS-driven cancers is unknown. Here, we characterize a first-in-class, clinical grade small molecule catalyticNSD2inhibitor (NSD2i) series and find pharmacological targeting of NSD2 constitutes an epigenetic dependency with broad therapeutic efficacy in KRAS-driven pre-clinical cancer models.
Read the full summary ↓
NSD2i inhibits NSD2 potently, with single digit nM IC50values, and shows high selectively for NSD2 versus NSD1, NSD3, and other similar enzymes. Structural analyses reveal the molecular basis of NSD2i specificity for NSD2, which includesS-adenosylmethionine (SAM)-competitive binding and catalytic disruption via a dual-channel obstruction mechanism. Proteo-epigenomic and single cell strategies in pancreatic ductal adenocarcinoma (PDAC) and lung adenocarcinoma (LUAD) samples support a model in which durable NSD2i exposure reverses H3K36me2-driven pathologic chromatin plasticity, re-establishing silencing at H3K27me3-legacy loci to curtail KRAS-regulated and oncogenic-associated gene expression programs. Accordingly, NSD2i treatment inhibits PDAC and LUAD cell viability and patient-derived xenograft tumor growth. Further, NSD2 inhibition, which is well toleratedin vivo, is equally effective as KRAS inhibition (sotorasib) treatment in prolonging survival in advanced stage autochthonous KRASG12C-driven PDAC and LUAD mouse tumor models. Moreover, in these models, NSD2 inhibition and sotorasib co-treatment synergize to confer sustained survival with extensive tumor nodule regression and elimination.Together, our work uncovers targeting of the NSD2-H3K36me2 axis as an actionable vulnerability in KRAS-driven cancers and provides a mechanistic rationale for testing NSD2i-KRAS inhibition combination therapies in the clinic.
This dataset
Open GSE273490 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Pancreatic 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 GSE273490_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1142010 and SRA study SRP523166. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
59 conditions, mostly in duplicate
MIA PaCa-2 cells, DMSO, day1, H3K4me3, biol ×2 MIA PaCa-2 cells, DMSO, day5, H3K4me3, biol ×2 MIA PaCa-2 cells, DMSO, day9, H3K4me3, biol ×2 MIA PaCa-2 cells, NSD2i, day1, H3K4me3, biol ×2 MIA PaCa-2 cells, NSD2i, day5, H3K4me3, biol ×2 MIA PaCa-2 cells, NSD2i, day9, H3K4me3, biol ×2 MIA PaCa-2 cells, DMSO, day1, H3K27me3, biol ×2 MIA PaCa-2 cells, DMSO, day5, H3K27me3, biol ×2 +53 more

Supports a between-group comparison across 118 samples.

How we read this: 59 replicated groups read from 120 sample titles; they account for 118 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

+ 80 more — browse all 120 samples with per-sample file links →

More Pancreatic cancer datasets

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

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