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Differential mRNA expression analysis of multiple human and mouse pancreatic cancer cells and tumors after DMSO, tazemetostat, RMC-6236, or the combination treatment.

GSE315130 Homo sapiens (human) RNA-seq (gene expression) 67 samples Submitted 2026/01/31 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · human · 67 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)
Topic
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
67 samples: 21 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)
Our study demonstrated that combined treatment with the EZH2 inhibitor tazemetostat and the KRAS inhibitor RMC-6236 significantly suppressed the growth of subcutaneous and orthotopic tumors. To investigates the transcriptional effects of combined EZH2 and KRAS inhibition in pancreatic cancer models, transcriptome profiling was performed in PSN1, SW1990, and KPC cells treated with DMSO, tazemetostat, RMC-6236, or the combination of both inhibitors.
Read the full summary ↓
In parallel, orthotopic KPC tumors subjected to the same treatments were harvested for RNA sequencing. In addition, an acquired resistance model to RMC-6236 was established in mice, and tumors treated with RMC-6236 alone or in combination with tazemetostat were collected at different stages for RNA-seq analysis to characterize dynamic changes in gene expression profiles.
This dataset
Open GSE315130 in finder → Find more 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 GSE315130_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 PRJNA1395035 and SRA study SRP658603. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
21 conditions, mostly in triplicate
KPC_orthotopic_tumor_Con ×4 KPC_orthotopic_tumor_Taze ×4 KPC_orthotopic_tumor_RMC6236 ×4 KPC_orthotopic_tumor_Combo ×4 PSN1_cell_Con ×3 PSN1_cell_Taze ×3 PSN1_cell_RMC6236 ×3 PSN1_cell_Combo ×3 +13 more

Supports a between-group comparison across 67 samples.

How we read this: 21 replicated groups read from 67 sample titles; they account for 67 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

+ 27 more — browse all 67 samples with per-sample file links →

More Pancreatic cancer datasets

Search all 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.