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A blood-brain barrier-like vascular gate limits immunotherapy efficacy in neuroendocrine cancers

GSE287964 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/03/23 Platform GPL24247Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 12 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
Mus musculus (mouse)
Samples
12 samples: 3 × Endothelial cells isolated from mouse NSCLC tumor vs 2 × Endothelial cells isolated from mouse SCLC tumor vs 2 × small cell lung cancer tissue, sgIgfbp5,Groups 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)
Small cell lung cancer (SCLC), a highly aggressive neuroendocrine malignancy, is among the most immune-desert tumor types and exhibits poor response to immunotherapy. However, the mechanisms underlying this immune resistance remain unclear. Here, we identify a unique immune-excluding vascular (IEV) barrier in SCLC, distinct from non-small cell lung cancer (NSCLC) and other cancers, composed of tightly connected endothelial cells, a thickened basement membrane, and dense pericyte coverage.
Read the full summary ↓
Functionally, this barrier restricts immune cell infiltration, contributing to SCLC’s immunotherapy resistance. Mechanistically, we show that ASCL1, the master transcription factor of SCLC, is essential for IEV barrier formation. ASCL1 drives expression of insulin-like growth factor-binding protein 5 (IGFBP5), and depletion of IGFBP5 in tumor cells reduces IGF1 signaling in endothelial cells. Endothelial-specific disruption of IGF1R impairs barrier integrity. Importantly, targeting this axis either through IGFBP5 knockout or treatment with the IGF1R inhibitor OSI-906 enhances CD8+ T cell infiltration and synergizes with anti-PD1 therapy in SCLC. Furthermore, we demonstrate that this ASCL1-IGFBP5-IGF1R axis and the IEV barrier are conserved across multiple neuroendocrine cancers (NECs). Our findings reveal a previously unrecognized vascular barrier in NECs and propose novel therapeutic strategies to overcome immune exclusion and enhance immunotherapy efficacy in these recalcitrant cancers.
This dataset
Open GSE287964 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 GSE287964_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 PRJNA1215371 and SRA study SRP559700. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × Endothelial cells isolated from mouse NSCLC tumor vs 2 × Endothelial cells isolated from mouse SCLC tumor vs 2 × small cell lung cancer tissue, sgIgfbp5,

Supports a between-group comparison across 7 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 7 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
Datasets on a similar topic

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