GEO series

Cryo-thermal therapy reprograms myeloid cells into CCL5+ mature phenotype to increase T cell infiltration and potentiates anti-PD-1 therapy

GSE314594 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/03/01 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 18 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: 18 samples: 5 conditions, mostly in triplicateGroups 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)

Although immune checkpoint blockade (ICB) represented by anti-PD-1 therapy has demonstrated significant clinical benefits, its efficacy remains limited by the immunosuppressive tumour microenvironment (TME). Cryo-thermal therapy (CTT) not only completely ablates local solid tumours by pre-freezing before radiofrequency heating, but also reverses immunosuppression and triggers strong systemic anti-tumour immunity to inhibit tumour recurrence and metastasis.

Read the full summary ↓

Our present study reveals that combining CTT with anti-PD-1 treatment potently enhances myeloid cell maturation and simultaneously promotes the infiltration and functional activation of T cells in distal tumours, resulting in superior suppression of distal tumour growth compared to either cryoablation or radiofrequency ablation combined with anti-PD-1. Mechanistically, CTT specifically induces TNF-α production in mature myeloid cells, triggering autocrine CCL5 secretion that recruits peripheral IFN-γ+ T cells induced by CTT in distal tumours, creating a cytokine loop where IFN-γ derived from T cells and TNF-α derived from myeloid cells collectively promote CCL5 secretion in myeloid cells to enhance effector T cell recruitment in distal tumours. Subsequently, after CTT, anti-PD-1 treatment amplifies this cascade by enhancing TNF-α production in T cells, and high levels of IFN-γ and TNF-α in distal tumours promotes higher secretion of CCL5 in myeloid cells, resulting in robust infiltration of T cells. The parallel activation of STAT1 by IFN-γ and NF-κB by TNF-α in myeloid cells converges to drive IRF7-dependent CCL5 upregulation to create a local immune enhancing environment via CCL5-mediated recruitment of T cells. Our study demonstrates that CTT establishes an immunologically favorable TME by reprogramming immunosuppressive myeloid cells into mature myeloid cells with high CCL5 production, thereby facilitating effector T cell recruitment, providing an efficient therapeutic strategy to promote the response to anti-PD-1 therapy.

This dataset

Open GSE314594 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 GSE314594_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 PRJNA1392186 and SRA study SRP657086. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 conditions, mostly in triplicate

C ×3 CP ×3 RP ×3 A ×3 AP ×3 R1 ×1 R2 ×1 R3 ×1

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 18 sample titles; they account for 15 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

GSM9405264 C1 C
GSM9405265 C2 C
GSM9405266 C3 C
GSM9405267 CP1 CP
GSM9405268 CP2 CP
GSM9405269 CP3 CP
GSM9405270 R1
GSM9405271 R2
GSM9405272 R3
GSM9405273 RP1 RP
GSM9405274 RP2 RP
GSM9405275 RP3 RP
GSM9405276 A1 A
GSM9405277 A2 A
GSM9405278 A3 A
GSM9405279 AP1 AP
GSM9405280 AP2 AP
GSM9405281 AP3 AP

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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.