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Age-stratified transcriptomic profiling reveals biologically distinct molecular phenotypes across pediatric, adolescent, and adult osteosarcoma

GSE317512 Homo sapiens (human) RNA-seq (gene expression) 70 samples Submitted 2026/02/11 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 70 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
OsteosarcomaThis series is part of our curated briefing on it.
Samples
70 samples: 68 × OSGroups 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
Age-Stratified Transcriptomic Profiling Reveals Biologically Distinct Molecular Phenotypes Across Pediatric, Adolescent, and Adult OsteosarcomaBiomedicines · 2026
Summary (written by the submitters)
Osteosarcoma exhibits a bimodal age distribution with distinct clinical behaviors between pediatric and adult patients. In this study, bulk RNA sequencing was performed on tumor specimens from 70 osteosarcoma patients stratified into pediatric (14 years and younger), adolescent (15 to 18 years), and adult (19 years and older) groups. Differential expression, functional enrichment, and immune infiltration analyses were conducted to characterize age-associated transcriptional differences.
Read the full summary ↓
Pediatric tumors exhibited a hyperproliferative phenotype, adolescent tumors showed enhanced immune-related signatures, and adult tumors displayed activation of osteogenic differentiation programs. A characteristic pediatric-specific gene signature was further identified, providing insights into age-related molecular heterogeneity in osteosarcoma.
Published in
Age-Stratified Transcriptomic Profiling Reveals Biologically Distinct Molecular Phenotypes Across Pediatric, Adolescent, and Adult Osteosarcoma
Hu L, Qi F, Liu H et al. · Biomedicines 2026 · PMID 41751262 · doi:10.3390/biomedicines14020363
This dataset
Open GSE317512 in finder → Find more human RNA-seq datasets → Osteosarcoma 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 GSE317512_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 PRJNA1414398. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41751262) ↗
Study design
68 × OS

Supports a between-group comparison across 68 samples.

How we read this: 1 replicated groups read from 70 sample titles; they account for 68 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

+ 30 more — browse all 70 samples with per-sample file links →

More Osteosarcoma datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.