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In situ multi-modal characterization of pancreatic cancer reveals tumor cell identity as a defining factor of the surrounding microenvironment. [RNA-Seq]

GSE310388 Homo sapiens (human) Single-cell RNA-seq 171 samples Submitted 2025/12/03 Platform GPL30173
At a glance

Single-cell RNA-seq · human · 171 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
171 samples: 55 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
In situ multi-modal characterization of pancreatic cancer reveals tumor cell identity as a defining factor of the surrounding microenvironmentCell reports · 2026
Summary (written by the submitters)
Pancreatic ductal adenocarcinoma is heterogeneous, with low tumor purity, a prominent microenvironment, and complex architecture, which preclude the identification of shared tumor-intrinsic and stromal biology within and across patients. We overcame these challenges by achieving necessary resolution and context through the application of complimentary genomics, pathology and machine learning approaches to characterize primary untreated tumors from 39 patients.
Read the full summary ↓
We capture 340K spatial low-bulk and 530K spatial single-cell transcriptomes and observe a spectrum of classical-to-basal tumor subtypes present within all patients. We find each subtype has distinct regulators, stromal neighborhoods, microenvironment, extracellular matrix and histology corresponding to multiple immunosuppressive and therapy resistance mechanisms. We define key tumor heterogeneity features including the presence of mixed KRAS mutations and tertiary lymphoid structures; identifying biomarkers that distinguish the latter from lymph nodes. Lastly, leveraging patient, cell and mouse data, we determine which aspects of tumor biology are recapitulated in bulk datasets and reductionist models.
Published in
In situ multi-modal characterization of pancreatic cancer reveals tumor cell identity as a defining factor of the surrounding microenvironment
Lyubetskaya A, Rabe B, Kavran A et al. · Cell reports 2026 · PMID 41533516 · doi:10.1016/j.celrep.2025.116827
This dataset
Open GSE310388 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 GSE310388_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 PRJNA1365869 and SRA study SRP646360. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41533516) ↗
Study design
55 conditions, mostly in triplicate
Hypoxia_AsPC1_Day1 ×3 Hypoxia_AsPC1_Day14 ×3 Hypoxia_AsPC1_Day3 ×3 Hypoxia_AsPC1_Day7 ×3 Hypoxia_AsPC1_Day9 ×3 Hypoxia_PACADD188_Day1 ×3 Hypoxia_PACADD188_Day14 ×3 Hypoxia_PACADD188_Day3 ×3 +53 more

Supports a between-group comparison across 165 samples.

How we read this: 55 replicated groups read from 171 sample titles; they account for 165 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

+ 131 more — browse all 171 samples with per-sample file links →

More Pancreatic cancer datasets

Search all human RNA-seq datasets in GEO →

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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.