GEO series

Oncogenic and tumor-suppressive forces converge on a progenitor-orchestrated niche to shape early tumorigenesis [KPLOH scRNA-seq]

GSE313305 Mus musculus (mouse) Single-cell RNA-seq 17 samples Submitted 2026/03/18 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 17 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 17 samples: 6 × Pre-tumor p53 proficient vs 4 × Pre-tumor p53 deficient vs 4 × Tumor p53 proficient vs 3 × Tumor p53 deficientGroups 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)

The transition from benign to malignant growth is a pivotal yet poorly understood step in cancer progression that marks the shift from a pathologically inert condition to a clinically lethal disease. Here, we integrate lineage tracing, single-cell and spatial transcriptomics to visualize the molecular, cellular and tissue-level events that promote or restrain malignancy during the tumor initiation in mouse models of pancreatic ductal adenocarcinoma (PDAC).

Read the full summary ↓

We identify a discrete progenitor-like population of KRAS-mutant cells that co-activates oncogenic and tumor-suppressive programs—including p53, CDKN2A, and SMAD4—engaging senescence-like responses and remodeling their microenvironment, ultimately assembling a niche that mirrors invasive PDAC. Even brief KRAS inhibition in the epithelial compartment depletes progenitor-like cells and dismantles their niche, substantially delaying cancer initiation. Conversely, p53 suppression enables progenitor cell expansion, epithelial–mesenchymal reprogramming, and immune-privileged niche formation. These findings position the progenitor-like state as the convergence point of cancer-driving mutations, plasticity, and tissue remodeling—revealing a critical window for intercepting malignancy at its origin.

This dataset

Open GSE313305 in finder → Find more mouse 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 GSE313305_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 PRJNA1378908 and SRA study SRP654144. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 × Pre-tumor p53 proficient vs 4 × Pre-tumor p53 deficient vs 4 × Tumor p53 proficient vs 3 × Tumor p53 deficient

Supports a between-group comparison across 17 samples.

How we read this: 4 replicated groups read from 17 sample titles; they account for 17 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

GSM9365527 Pre-tumor p53 proficient 0 Pre-tumor p53 proficient
GSM9365528 Pre-tumor p53 proficient 1 Pre-tumor p53 proficient
GSM9365529 Pre-tumor p53 proficient 2 Pre-tumor p53 proficient
GSM9365530 Pre-tumor p53 proficient 3 Pre-tumor p53 proficient
GSM9365531 Pre-tumor p53 proficient 4 Pre-tumor p53 proficient
GSM9365532 Pre-tumor p53 proficient 5 Pre-tumor p53 proficient
GSM9365533 Pre-tumor p53 deficient 1 Pre-tumor p53 deficient
GSM9365534 Pre-tumor p53 deficient 2 Pre-tumor p53 deficient
GSM9365535 Pre-tumor p53 deficient 4 Pre-tumor p53 deficient
GSM9365536 Pre-tumor p53 deficient 5 Pre-tumor p53 deficient
GSM9365537 Tumor p53 proficient 6 Tumor p53 proficient
GSM9365538 Tumor p53 proficient 7 Tumor p53 proficient
GSM9365539 Tumor p53 proficient 8 Tumor p53 proficient
GSM9365540 Tumor p53 proficient 12 Tumor p53 proficient
GSM9365541 Tumor p53 deficient 6 Tumor p53 deficient
GSM9365542 Tumor p53 deficient 7 Tumor p53 deficient
GSM9365543 Tumor p53 deficient 8 Tumor p53 deficient

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GSE317073 Oncogenic and tumor-suppressive forces converge on a progenitor-orchestrated niche to shape early tumorigenesis [kras_inhibitor_scRNA-seq] 4 samples shares progenitor-orchestrated, tumor-suppressive, tumorigenesis, oncogenic, scrna-seq, converge, forces
GSE315243 Oncogenic and tumor-suppressive forces converge on a progenitor-orchestrated niche to shape early tumorigenesis 69 samples shares progenitor-orchestrated, tumor-suppressive, tumorigenesis, oncogenic, converge, forces
GSE216741 Oncogenic fatty acid oxidation senses sleep deficiency-induced circadian disruption to promote tumorigenesis 48 samples shares tumorigenesis, oncogenic
GSE216729 Oncogenic fatty acid oxidation senses sleep deficiency-induced circadian disruption to promote tumorigenesis [circadian] 42 samples shares tumorigenesis, oncogenic
GSE297023 Aging represses oncogenic KRAS-driven lung tumorigenesis and alters tumor suppression 16 samples shares tumorigenesis, oncogenic
GSE277228 Changing dynamics of the fibroblast differentiation hierarchy during mammary gland morphogenesis and tumorigenesis [scRNA-Seq I] 13 samples shares tumorigenesis, scrna-seq
GSE224830 Active repression of cell fate plasticity by PROX1 safeguards hepatocyte identity and prevents liver tumorigenesis [Prox1 OE iHep Timecourse scRNA-seq] 13 samples shares tumorigenesis, scrna-seq
GSE299487 LY6D Identifies Persistent Tumor-Initiating Cells Driving Pancreatic Tumorigenesis [scRNA-seq] 12 samples shares tumorigenesis, scrna-seq

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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.