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A Multivariate Cell-Based Liquid Biopsy for Lung Nodule Risk Stratification: Analytical Validation and Early Clinical Evaluation

GSE275699 Homo sapiens (human) RNA-seq (gene expression) 249 samples Submitted 2025/08/07 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 249 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
Homo sapiens (human)
Topic
Lung cancerThis series is part of our curated briefing on it.
Samples
249 samples: 218 distinct titles, 3 of them repeatedGroups 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
A multivariate cell-based liquid biopsy for lung nodule risk stratification: Analytical validation and early clinical evaluationThe journal of liquid biopsy · 2025
Summary (written by the submitters)
The iCAP is a tool for blood-based diagnostics that addresses the low signal-to-noise ratio of blood biomarkers by using cells as biosensors. The assay exposes patient serum to standardized cells in culture and classifies disease by AI analysis of gene expression readouts from the cells. This method simplifies the complexity of blood into a concise readout in a scalable cell-based assay.
Read the full summary ↓
We developed the LC-iCAP as a rule-out test for nodule management in CT-based lung cancer screening. The assay achieved an AUC of 0.63 (95% CI 0.50-0.75) in blind temporal validation with retrospective samples. When integrated with CT data after validation, it demonstrated 90% sensitivity, 67% specificity and 95% NPV using an estimated 25% prevalence, significantly outperforming the Mayo Clinic model and potentially reducing unnecessary follow-up procedures. Analytical validation demonstrated LC-iCAP reproducibility, identified unwanted variation from long-term sample storage and indicated enrichment of hypoxia signaling in the differential assay readout.
Published in
A multivariate cell-based liquid biopsy for lung nodule risk stratification: Analytical validation and early clinical evaluation
Berndt JD, Duffy FJ, D'Ascenzo MD et al. · The journal of liquid biopsy 2025 · PMID 40831733 · doi:10.1016/j.jlb.2025.100313
This dataset
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.

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 GSE275699_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1152596 and SRA study SRP528726. Searching any of these in the dataset finder brings you back here.

Study design
218 distinct titles, 3 of them repeated
16HBE cells, 5% serum reference control, 24h, ×14 16HBE cells, 5% case serum pool 20200917, 24h, ×10 16HBE cells, 5% control serum pool 20200917, … ×10

Supports a case/control comparison: 215 samples read as cases, 24 as controls.

How we read this: Read from 249 sample titles: 218 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

+ 209 more — browse all 249 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.