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Pulsed Electric Field Ablation Reprograms Tumor Immunity and Stimulates Germinal Center Formation in Tertiary Lymphoid Structures in Patients with Non-Small Cell Lung Cancer

GSE325414 Homo sapiens (human) Single-cell RNA-seq 67 samples Submitted 2026/06/10 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 67 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Topic
Lung cancerThis series is part of our curated briefing on it.
Samples
67 samples: 67 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)
Purpose: This treat-and-resect clinical study evaluated a specialized form of pulsed electric field (PEF) ablation’s potential to modulate antitumor immunity in early-stage non-small cell lung cancer (NSCLC). Tertiary lymphoid structures (TLS) are lymphoid aggregates that recruit immune cells into the tumor microenvironment (TME) and serve as immunity-generating neighborhoods.
Read the full summary ↓
TLS with germinal centers (GC) have strong prognostic value in most cancers and promote tumor control and responsiveness to immune-based therapies, but no commercially available therapeutics induce their formation. The Aliya System is a proprietary electrosurgical technology that delivers microsecond electrical pulses to tissue, achieving tumor clearance while maintaining stromal architecture. Patients and Methods: Treatment group patients received ablation immediately after diagnostic biopsy versus a biopsy-only control group. Herein we report on exploratory endpoints examining immune modulation in blood and tumor samples collected from patients in both groups. Results: Histopathological assessments revealed the presence of TLS with GC in resected tumors. Tissue cytokine assessments and single-cell RNA sequencing demonstrated upregulation of cytokines capable of recruiting and organizing TLS-associated lymphocytes, including CXCL13, and significant increases in GC-related immune populations, including class-switched memory B cells and plasma cells in ablated tumors versus pre-ablation biopsies. Ablation group patients had more tumors containing TLS with GC (47%) vs. control (24%). Ablation group patients exhibited enhanced systemic immunity, with increased serum HMGB1 and circulating cytotoxic T cells. Conclusions: This specialized PEF may orchestrate multiple simultaneous changes that promote a more immunologically active TME and represent a new approach for improving immunotherapeutic regimen responses in NSCLC patients.
This dataset
Open GSE325414 in finder → Find more human RNA-seq datasets → 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 GSE325414_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 PRJNA1435204 and SRA study SRP682666. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
67 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 67 sample titles: 67 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

+ 27 more — browse all 67 samples with per-sample file links →

More Lung cancer datasets

Search all human RNA-seq datasets in GEO →

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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.