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Prognostic Models and Signatures in Retroperitoneal Sarcoma

GSE296413 Homo sapiens (human) RNA-seq (gene expression) 119 samples Submitted 2025/05/21 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 119 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
Soft tissue sarcomaThis series is part of our curated briefing on it.
Samples
119 samples: 11 conditions, mostly with about 8 replicates eachGroups 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
CINSARC and Sarculator in Patients with Primary Retroperitoneal Sarcoma: A Combined Analysis of Single-Institution Data and the EORTC-STBSG-62092 Trial (STRASS)Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
Summary (written by the submitters)
CINSARC (the Complexity Index in SARComas) is a transcriptomic profile that independently forecasts the risk of metastasis in soft tissue sarcoma patients. This study aimed to (1) deliver the first standalone validation of CINSARC in a group of patients with retroperitoneal sarcoma (RPS) and (2) investigate if integrating CINSARC could improve the predictive accuracy of the Sarculator model.
Published in
CINSARC and Sarculator in Patients with Primary Retroperitoneal Sarcoma: A Combined Analysis of Single-Institution Data and the EORTC-STBSG-62092 Trial (STRASS)
Callegaro D, Tinè G, Oppong FB et al. · Clinical cancer research : an official journal of the American Association for Cancer Research 2025 · PMID 40423526 · doi:10.1158/1078-0432.CCR-25-0099
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 GSE296413_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 PRJNA1259244 and SRA study SRP583275. Searching any of these in the dataset finder brings you back here.

Study design
11 conditions, mostly with about 8 replicates each
LD ×20 KW ×16 KQ ×15 KJ ×14 KH ×12 KU ×9 K ×8 LG ×8 +3 more

Supports a between-group comparison across 119 samples.

How we read this: 11 replicated groups read from 119 sample titles; they account for 119 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

+ 79 more — browse all 119 samples with per-sample file links →

More Soft tissue sarcoma 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.