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HDAC5 Deficiency Induces Intrinsic Resistance to KRASG12D Inhibition by Disrupting c-Myc Acetylation-Ubiquitination Homeostasis [RNA-seq]

GSE309499 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/10/04 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × A.shNC+Vehicle vs 3 × B.shNC+MRTX1133 vs 3 × C.shHDAC5+Vehicle vs 3 × D.shHDAC5+MRTX1133Groups 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
HDAC5 deficiency induces intrinsic resistance to KRAS inhibition by disrupting c-Myc acetylation-ubiquitination homeostasisThe Journal of clinical investigation · 2026
Summary (written by the submitters)
We found that HDAC5 deletion significantly enhances intrinsic resistance to MRTX1133 in KRASG12D mutant pancreatic cancer. Mechanistic studies show that HDAC5 deletion promotes resistance to KRASG12D inhibitors by sustaining the activation of the MAPK signaling pathway.
Published in
HDAC5 deficiency induces intrinsic resistance to KRAS inhibition by disrupting c-Myc acetylation-ubiquitination homeostasis
Chen T, Yu H, Wang K et al. · The Journal of clinical investigation 2026 · PMID 41379561 · doi:10.1172/JCI195814
This dataset
Open GSE309499 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 GSE309499_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 PRJNA1336178 and SRA study SRP629596. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41379561) ↗
Study design
3 × A.shNC+Vehicle vs 3 × B.shNC+MRTX1133 vs 3 × C.shHDAC5+Vehicle vs 3 × D.shHDAC5+MRTX1133

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
Datasets on a similar topic

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