GEO series

Single-cell RNA and TCR sequencing reveals distinct systematic immune response induced by SABR with or without prior anti-PD-1 therapy

GSE190905 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2025/02/05 Platform GPL20795

At a glance

Single-cell RNA-seq · human · 16 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 16 samples: 16 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: Pre-immunotherapy alters stereotactic ablative radiotherapy-induced systemic T cell responses in early-stage NSCLCCancer immunology, immunotherapy : CII · 2025

Summary (written by the submitters)

Previous studies have demonstrated that stereotactic body radiation therapy (SBRT) could activate systemic immune response, however, these researches showed limitations in comprehensively characterizing changes of T cell profile and T cell receptor (TCR).

Read the full summary ↓

In the present study, we applied scRNA-seq and scTCR-seq to observe the dynamics of T cell and TCR repertoire from peripheral blood mononuclear cells (PBMCs) in early stage non-small-cell lung cancer (NSCLC) patients receiving SBRT with or without prior anti-PD-1 therapy, demonstrating the distinct systemic immune response between SBRT and ISBRT group. An enrichment of CD8-TE, CD8-EM, and CD4-TE clusters with increased cytotoxic and exhausted score were observed after treatment in SBRT group, while a decrease of those were presented in ISBRT group. Moreover, gene expression analysis revealed T cell mediated cytotoxicity signaling and T cell proliferation signaling were enriched in SBRT group while decreased in SBRT group. Analysis of TCR repertoire indicated a substantial alteration of TCR repertoire after treatment. The proportions of the large clone of TCR were increased after treatment in SBRT group while an opposite alteration existed in ISBRT group. After treatment, both SBRT and ISBRT group generated numerous new TCR clones which were mainly enriched in CD8 TE. Single clones and large clones were the mainly types of new TCRs in SBRT group, whereas in ISBRT group single clones accounted for the majority of new TCRs. These findings suggested that systemic immunity was activated in distinct pattern between the SBRT and ISBRT group, and provide evidence for future development of new treatment regimen.

Published in

Pre-immunotherapy alters stereotactic ablative radiotherapy-induced systemic T cell responses in early-stage NSCLC

Liu C, Chen Y, Li X et al. · Cancer immunology, immunotherapy : CII 2025 · PMID 39891774 · doi:10.1007/s00262-024-03935-8

This dataset

Open GSE190905 in finder → Find more human 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 GSE190905_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 PRJNA788905 and SRA study SRP350787. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39891774) ↗

Study design

16 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 16 sample titles: 16 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

GSM5733753 P001_pre_RNA [Batch1]
GSM5733754 P001_pre_TCR [Batch1]
GSM5733755 P005_pre/P006_pre_RNA [Batch2]
GSM5733756 P005_pre/P006_pre_TCR [Batch2]
GSM5733757 P004_pre/P002_pre_RNA [Batch3]
GSM5733758 P004_pre/P002_pre_TCR [Batch3]
GSM5733759 P001_post_RNA [Batch4]
GSM5733760 P001_post_TCR [Batch4]
GSM5733761 P003_pre_RNA [Batch5]
GSM5733762 P003_pre_TCR [Batch5]
GSM5733763 P006_post_RNA [Batch6]
GSM5733764 P006_post_TCR [Batch6]
GSM5733765 P004_post/P002_post_RNA [Batch7]
GSM5733766 P004_post/P002_post_TCR [Batch7]
GSM5733767 P005_post/P003_post_RNA [Batch8]
GSM5733768 P005_post/P003_post_TCR [Batch8]

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