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Neuronal-Activity Dependent Mechanisms of Small Cell Lung Cancer Pathogenesis

GSE303152 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2025/09/10 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 36 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
Small cell lung cancerThis series is part of our curated briefing on it.
Samples
36 samples: 36 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
Neuronal activity-dependent mechanisms of small cell lung cancer pathogenesisNature · 2025
Summary (written by the submitters)
Neural activity is increasingly recognized as a crucial regulator of cancer growth. In the brain, neuronal activity robustly influences glioma growth both through paracrine mechanisms and through electrochemical integration of malignant cells into neural circuitry via neuron-to-glioma synapses. Outside of the CNS, innervation of tumors such as prostate, breast, pancreatic and gastrointestinal cancers by peripheral nerves similarly regulates cancer progression.
Read the full summary ↓
However, the extent to which the nervous system regulates small cell lung cancer progression, either in the lung or when growing within the brain, is less well understood. Small cell lung cancer (SCLC) is a lethal high-grade neuroendocrine tumor that exhibits a strong propensity to metastasize to the brain. Here we demonstrate that SCLC cells in the brain co-opt neuronal activity-regulated mechanisms to stimulate growth and progression. In the lung, vagus nerve transection markedly inhibits primary lung tumor formation and development, highlighting a critical role for innervation in SCLC growth. In the brain, glutamatergic and GABAergic cortical neuronal activity each drive proliferation of SCLC in the brain through both paracrine and synaptic neuron-cancer interactions. SCLC cells form bona fide neuron-to-SCLC synapses and exhibit depolarizing currents with consequent calcium transients in response to neuronal activity. SCLC cell membrane depolarization is sufficient to promote the growth of intracranial tumors. Taken together, these studies illustrate that neuronal activity plays a crucial role in dictating SCLC pathogenesis in both the lung and the brain.
Published in
Neuronal activity-dependent mechanisms of small cell lung cancer pathogenesis
Savchuk S, Gentry KM, Wang W et al. · Nature 2025 · PMID 40931074 · doi:10.1038/s41586-025-09492-z
This dataset
Open GSE303152 in finder → Find more human RNA-seq datasets → Small cell lung 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 GSE303152_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 PRJNA1294240. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40931074) ↗
Study design
36 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 36 sample titles: 36 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
More Small cell lung cancer datasets

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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.