GEO series

Basal cell of origin resolves neuroendocrine-tuft lineage plasticity in cancer [Single cell RNA-seq]

GSE279200 Mus musculus (mouse) Single-cell RNA-seq 14 samples Submitted 2025/07/01 Platform GPL34290Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 14 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: 14 samples: 14 samples, each with a distinct title — no replicated groupsGroups 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: Basal cell of origin resolves neuroendocrine-tuft lineage plasticity in cancerNature · 2025

Summary (written by the submitters)

Neuroendocrine and tuft cells are rare, chemosensory epithelial lineages defined by expression of ASCL1 and POU2F3 transcription factors, respectively. Neuroendocrine cancers, including small cell lung cancer (SCLC), frequently display tuft-like subsets, a feature linked to poor patient outcomes. The mechanisms driving neuroendocrine–tuft tumour heterogeneity, and the origins of tuft-like cancers are unknown.

Read the full summary ↓

Using multiple genetically-engineered animal models of SCLC, we demonstrate that a basal cell of origin (but not the accepted neuroendocrine origin) generates neuroendocrine–tuft-like tumours that highly recapitulate human SCLC. Single-cell clonal analyses of basal-derived SCLC further uncovers unexpected transcriptional states and lineage trajectories underlying neuroendocrine–tuft plasticity. Uniquely in basal cells, introduction of genetic alterations enriched in human tuft-like SCLC, including high MYC, PTEN loss, and ASCL1 suppression, cooperate to promote tuft-like tumours. Transcriptomics of 944 human SCLCs reveal a basal-like subset and a tuft-ionocyte-like state that altogether demonstrate remarkable conservation between cancer states and normal basal cell injury response mechanisms. Together, these data suggest that the basal cell is a plausible origin for SCLC and other neuroendocrine-tuft cancers that can explain neuroendocrine–tuft heterogeneity—offering new insights for targeting lineage plasticity.

Published in

Basal cell of origin resolves neuroendocrine-tuft lineage plasticity in cancer

Ireland AS, Xie DA, Hawgood SB et al. · Nature 2025 · PMID 40963028 · doi:10.1038/s41586-025-09503-z

This dataset

Open GSE279200 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 GSE279200_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 PRJNA1171367 and SRA study SRP537724. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40963028) ↗

Study design

14 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 5 samples read as cases, 1 as controls.

How we read this: Read from 14 sample titles: 14 distinct titles with little repetition. 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

GSM9019561 Wildtype_Basal_Organoids_GEX
GSM9019562 RPM_RPMA_RPR2_Basal_Organoids_CMV_CellTagged_PreCre_GEX
GSM9019563 RPM_RPMA_RPR2_Basal_Organoids_CMV_CellTagged_PreCre_CMO
GSM9019564 RPM_Basal_Organoids_CMV_CellTagged_PostCre_GEX
GSM9019565 RPM_Basal_Allograft_CellTagged_PreCre_rep1_GEX
GSM9019566 RPMA_Basal_Allograft_CellTagged_PreCre_rep1_GEX
GSM9019567 RPR2_Basal_Allograft_GEX
GSM9019568 RPM_Basal_Allograft_CellTagged_PostCre_Allo3_GEX
GSM9019569 RPM_Basal_Allograft_CellTagged_PostCre_Allo4_GEX
GSM9019570 RPM_K5_Primary_Tumor_AI651_rep1_GEX
GSM9019571 RPM_K5_Primary_Tumor_AI652_rep2,3_GEX
GSM9019572 RPM_K5_Primary_Tumor_AI652_rep2-3_CMO
GSM9019573 RPM_CGRP_Primary_Tumors_AI731_AI732_GEX
GSM9019574 RPM_CGRP_Primary_Tumors_AI731_AI732_CMO

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