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Soluble Mesothelin-Related Peptide as a Prognosticator in Pleural Mesothelioma Patients Receiving Checkpoint Immunotherapy

GSE274983 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/08/19 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
Topic
MesotheliomaThis series is part of our curated briefing on it.
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.
Paper
Soluble mesothelin-related peptide as a prognosticator in pleural mesothelioma patients receiving checkpoint immunotherapyThe Journal of thoracic and cardiovascular surgery · 2025
Summary (written by the submitters)
Objective: Immune checkpoint therapy (ICT) has significantly impacted malignant pleural mesothelioma (MPM) treatment. Despite some promising results from combination therapies, nearly half of MPM patients do not benefit, underscoring the urgent need for reliable predictive biomarkers. This study assesses the prognostic value of serum soluble mesothelin-related peptide (SMRP) and PD-L1 levels in MPM patients receiving ICT.
Read the full summary ↓
Results: Seventy-seven patients (62%) were treated with either anti-PD-(L)1 monotherapy, while the remaining 38% were given combination ICT. Higher pre-ICT SMRP levels were notably observed in epithelioid versus non-epithelioid MPM. Serum PD-L1 levels did not show significant differences between the groups. Univariable analysis identified durable clinical benefits, development of immune-related adverse events, and SMRP levels as significantly associated with OS. Multivariable analysis confirmed SMRP as an independent prognostic factor, with lower levels (≤1.35 nmol/L) correlating with improved OS (median survival: 23 months vs. 13 months). This finding was further validated in the prospective ICT clinical trial cohort. Conclusions: SMRP emerges as a promising serum biomarker for predicting survival in MPM patients treated with ICT, warranting further prospective investigation.
Published in
Soluble mesothelin-related peptide as a prognosticator in pleural mesothelioma patients receiving checkpoint immunotherapy
Mitra S, Jang HJ, Kuncheria A et al. · The Journal of thoracic and cardiovascular surgery 2025 · PMID 39395787 · doi:10.1016/j.jtcvs.2024.10.005
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 GSE274983_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 PRJNA1148672 and SRA study SRP526737. Searching any of these in the dataset finder brings you back here.

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
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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.