GEO series

Combinatorial delivery of low-dose irradiation and immunotherapy to patients with immune-excluded tumors effectively enhances CD8+ T cell functionality in tumors with homologous recombination repair deficiency [scRNA-seq]

GSE295600 Homo sapiens (human) Single-cell RNA-seq 18 samples Submitted 2026/04/07 Platform GPL20301

At a glance

Single-cell RNA-seq · human · 18 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: 18 samples: 18 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.

Summary (written by the submitters)

Immune-checkpoint blockade (ICB) has shown significant efficacy across various tumor types. However, tumors with low intraepithelial T-cell infiltration, often referred to as "cold" tumors, are expected to yield poor responsiveness to ICB. We investigated the potential of LDRT to enhance immune-checkpoint blockade (ICB) responses in 25 patients with multimetastatic immune-excluded solid tumors through a multi-cohort phase I clinical trial (RACIN).

Read the full summary ↓

Primary endpoint was to determine the safety and tolerability of the combination of a backbone treatment, comprising nivolumab, ipilimumab, aspirin/celecoxib, and low-dose cyclophosphamide in association with escalated LDRT. Secondary endpoints included among others disease control rate (DCR) and overall survival (OS). Exploratory endpoints included biomarkers and molecular correlates of response. The combination treatment showed a manageable safety profile, with Grade 3 or higher adverse events in 12% to 21% of patients across cohorts. The overall disease control rate (CR + PR + SD) was 41.6%. Progression free survival across all cohorts was 2.1 months (95% C.I.: 1.8 – 4.2 months), with the highest PFS observed in cohort 1 which received 0.5 Gy (5.7 months, (95% C.I.: 1.9 - 11.3 months). Median overall survival was 14.0 months (95% CI: 8.5–24.6 months), with one patient with ovarian cancer still maintaining a complete response at three years follow-up. Site-paired tumour biopsies collected for each patient at baseline and after LDRT +/- Cy enabled the comprehensive characterization of the dynamics of their excluded/desert tumour microenvironments (TME) at the single cell level. Response to LDRT and ICB was associated with DNA damage and repair responsiveness and the presence of detectable intratumoral PD1+CD8+ tumour infiltrating lymphocytes (TILs) at baseline. Our data revealed that LDRT amplified CD8+ TIL functionality in responding patients offering mechanistic insights on how LDRT improves ICB effectiveness. In contrast, we observed a radiosensitivity of TILs in tumours of non-responders. Detailed single cell immune profiling before LDRT also highlighted a lack of key immune stimulatory myeloid cells that can therefore limit ICB efficacy in excluded tumors. Collectively, this study represents the most comprehensive profiling of longitudinal samples of cancer patients treated with LDRT. Our findings highlight several genetic, transcriptomic and TME parameters associated with response to combinatorial LDRT and ICB in advanced immune-excluded solid cancers, generating rationale for their validation in larger cohorts.

This dataset

Open GSE295600 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 GSE295600_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 PRJNA1255246 and SRA study SRP581127. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

18 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 18 sample titles: 18 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

GSM8953605 patient_1_baseline
GSM8953606 patient_1_day10
GSM8953607 patient_3_baseline
GSM8953608 patient_6_baseline
GSM8953609 patient_6_day10
GSM8953610 patient_8_baseline
GSM8953611 patient_10_baseline
GSM8953612 patient_11_baseline
GSM8953613 patient_11_day10
GSM8953614 patient_17_day10
GSM8953615 patient_18_baseline
GSM8953616 patient_18_day10
GSM8953617 patient_19_baseline
GSM8953618 patient_19_day10
GSM8953619 patient_20_baseline
GSM8953620 patient_20_day10
GSM8953621 patient_22_baseline
GSM8953622 patient_22_day10

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