Transcriptome analysis of pancreatic progenitor organoids (POs) carrying PDAC related mutations, treated with ERK inhibitors and depleted of AP-1 factors
RNA-seq (gene expression) · human · 40 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
- 40 samples: 14 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.
- Paper
- Human pancreatic progenitor organoids define genetic and epigenetic barriers to early PDAC transformationDevelopmental cell · 2026
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE272460_RAW.tar (it can run to tens of gigabytes).
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.
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 PRJNA1136910 and SRA study SRP520532. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 40 samples.
How we read this: 14 replicated groups read from 40 sample titles; they account for 40 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.
- GSM8403072 GFP_RNA-seq_1 GFP_RNA-seq
- GSM8403073 GFP_RNA-seq_2 GFP_RNA-seq
- GSM8403074 GFP_RNA-seq_3 GFP_RNA-seq
- GSM8403075 K_RNA-seq_1 K_RNA-seq
- GSM8403076 K_RNA-seq_2 K_RNA-seq
- GSM8403077 K_RNA-seq_3 K_RNA-seq
- GSM8403078 KC_RNA-seq_1 KC_RNA-seq
- GSM8403079 KC_RNA-seq_2 KC_RNA-seq
- GSM8403080 KC_RNA-seq_3 KC_RNA-seq
- GSM8403081 KP_RNA-seq_1 KP_RNA-seq
- GSM8403082 KP_RNA-seq_2 KP_RNA-seq
- GSM8403083 KP_RNA-seq_3 KP_RNA-seq
- GSM8403084 KCP_RNA-seq_1 KCP_RNA-seq
- GSM8403085 KCP_RNA-seq_2 KCP_RNA-seq
- GSM8403086 KCP_RNA-seq_3 KCP_RNA-seq
- GSM8403087 KCPS_RNA-seq_1 KCPS_RNA-seq
- GSM8403088 KCPS_RNA-seq_2 KCPS_RNA-seq
- GSM8403089 KCPS_RNA-seq_3 KCPS_RNA-seq
- GSM8403090 KCP_DMSO_RNA-seq_1 KCP_DMSO_RNA-seq
- GSM8403091 KCP_DMSO_RNA-seq_2 KCP_DMSO_RNA-seq
- GSM8403092 KCP_LY_RNA-seq_1 KCP_LY_RNA-seq
- GSM8403093 KCP_LY_RNA-seq_2 KCP_LY_RNA-seq
- GSM8403094 KCP_NT_RNA-seq_1 KCP_NT_RNA-seq
- GSM8403095 KCP_NT_RNA-seq_2 KCP_NT_RNA-seq
- GSM8403096 KCP_NT_RNA-seq_3 KCP_NT_RNA-seq
- GSM8403097 KCP_FOS_KO_RNA-seq_1 KCP_FOS_KO_RNA-seq
- GSM8403098 KCP_FOS_KO_RNA-seq_2 KCP_FOS_KO_RNA-seq
- GSM8403099 KCP_FOS_KO_RNA-seq_3 KCP_FOS_KO_RNA-seq
- GSM8403100 KCP_FOSL1_KO_RNA-seq_1 KCP_FOSL1_KO_RNA-seq
- GSM8403101 KCP_FOSL1_KO_RNA-seq_2 KCP_FOSL1_KO_RNA-seq
- GSM8403102 KCP_FOSL1_KO_RNA-seq_3 KCP_FOSL1_KO_RNA-seq
- GSM8403103 KCP_FOSL2_KO_RNA-seq_1 KCP_FOSL2_KO_RNA-seq
- GSM8403104 KCP_FOSL2_KO_RNA-seq_2 KCP_FOSL2_KO_RNA-seq
- GSM8403105 KCP_FOSL2_KO_RNA-seq_3 KCP_FOSL2_KO_RNA-seq
- GSM8403106 KCP_JUNB_KO_RNA-seq_1 KCP_JUNB_KO_RNA-seq
- GSM8403107 KCP_JUNB_KO_RNA-seq_2 KCP_JUNB_KO_RNA-seq
- GSM8403108 KCP_JUNB_KO_RNA-seq_3 KCP_JUNB_KO_RNA-seq
- GSM8403109 KCP_JUND_KO_RNA-seq_1 KCP_JUND_KO_RNA-seq
- GSM8403110 KCP_JUND_KO_RNA-seq_2 KCP_JUND_KO_RNA-seq
- GSM8403111 KCP_JUND_KO_RNA-seq_3 KCP_JUND_KO_RNA-seq
- GSE263364 Characterization of human pancreatic tissue and organoids reveals subpopulation of intercalated duct cells with progenitor traits 23 samples shares pancreatic, progenitor, organoids
- GSE205154 Bulk RNA-Seq gene expression data for 289 primary and metastatic pancreatic ductal adenocarcinoma (PDAC) tumor samples from FFPE blocks. 289 samples shares pdac, pancreatic
- GSE275078 In vitro drug screening of RAF/MEK/ERK Inhibitors in combination with Autophagy inhibition in the context of two PDA Cell Lines 136 samples shares erk, inhibitors
- GSE319951 Effect of pancreatic tumor interstitial fluid media on transcriptional responses in PDAC cells 54 samples shares pdac, pancreatic
- GSE235244 Senescent cancer-associated fibroblasts in pancreatic adenocarcinoma suppress CD8+ T cell activation and inhibit response to immune checkpoint therapy [hPDAC] 8 samples shares pdac, pancreatic
- GSE273073 A hPSC-Derived Progressive Pancreatic Ductal Adenocarcinoma Model Reveals Dual Pathways in ERK-Driven Cellular Plasticity 93 samples shares erk, pancreatic
- GSE300200 The Lysine Demethylase Kdm4C is an Oncogenic Driver and Regulates ERK Activity in KRAS Mutant Pancreatic Ductal Adenocarcinoma 26 samples shares erk, pancreatic
- GSE300595 Multiomic sequencing identifies myeloid cell associations with neoadjuvant chemotherapy treatment response in pancreatic adenocarcinoma (PDAC) 24 samples shares pdac, pancreatic
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.