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Selective NSD2 Inhibition Reveals an Epigenetic Vulnerability of KRAS-Driven Cancers [RNA-Seq]

GSE273492 Homo sapiens (human) Single-cell RNA-seq 36 samples Submitted 2025/04/12 Platform GPL29480
At a glance

Single-cell RNA-seq · human · 36 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Topic
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
36 samples: 10 conditions, mostly with about 4 replicates eachGroups 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 signaling. However, whether selective inhibition of NSD2 enzymatic activity at chromatin can serve as an effective cancer therapy is unknown. Here, we characterize a first-in-class, clinical grade small molecule catalytic NSD2 inhibitor (NSD2i) series and find that pharmacological targeting of NSD2 constitutes an epigenetic dependency with broad therapeutic efficacy in KRAS-driven pre-clinical cancer models.
Read the full summary ↓
NSD2i potently inhibits NSD2 with single digit nM IC50 values and high selectivity over NSD1, NSD3, and other methyltransferases. Structural analyses reveal the molecular basis of NSD2i specificity for NSD2 includes S-adenosylmethionine (SAM)-competitive binding and catalytic disruption via a binary-channel obstruction mechanism. Proteo-epigenomic and single-cell strategies in pancreatic ductal adenocarcinoma (PDAC) and lung adenocarcinoma (LUAD) samples support a model in which sustained 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 inhibits PDAC and LUAD cell viability and patient-derived xenograft tumor growth. Further, NSD2i, which is well-tolerated in vivo, prolongs survival in advanced-stage autochthonous KRASG12C-driven PDAC and LUAD mouse tumor models nearly as effectively as KRAS inhibition with sotorasib. Moreover, in these models, NSD2i synergizes with sotorasib 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 inhibitor combination therapies in the clinic.
This dataset
Open GSE273492 in finder → Find more human RNA-seq 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 GSE273492_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1142008 and SRA study SRP523143. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly with about 4 replicates each
MIA PaCa-2 cells, DMSO, day1 biol ×4 MIA PaCa-2 cells, NSD2i, day1 biol ×4 MIA PaCa-2 cells, DMSO, day5 biol ×4 MIA PaCa-2 cells, NSD2i, day5 biol ×4 MIA PaCa-2 cells, DMSO, day9 biol ×4 MIA PaCa-2 cells, NSD2i, day9 biol ×4 KP2 cells, DMSO, biol ×3 KP2 cells, NSD2i, biol ×3 +2 more

Supports a between-group comparison across 36 samples.

How we read this: 10 replicated groups read from 36 sample titles; they account for 36 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
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