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Gene expression data from a Brazilian cohort of pediatric adrenocortical tumors

GSE182022 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2025/05/02 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 14 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)
Samples
14 samples: 14 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
Identifying prognostic hub genes and key pathways in pediatric adrenocortical tumors through RNA sequencing and Co-expression analysisMolecular and cellular endocrinology · 2024
Summary (written by the submitters)
Adrenocortical tumors in children are rare, but 10-15 times more incident in Southern Brazil than in the rest of the world. However, reliable biomarkers capable of establishing a well-defined prognostic correlation or predicting relapse risk of the disease are still challenging. Herein, we aimed to compare the expression profiles of pediatric adrenocortical tumors of patients with favorable and unfavorable clinical outcomes.
Published in
Identifying prognostic hub genes and key pathways in pediatric adrenocortical tumors through RNA sequencing and Co-expression analysis
Veronez LC, Xavier AET, Nagano LF et al. · Molecular and cellular endocrinology 2024 · PMID 39413985 · doi:10.1016/j.mce.2024.112383
This dataset
Open GSE182022 in finder → Find more human RNA-seq datasets →
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 GSE182022_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 PRJNA754189 and SRA study SRP332355. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39413985) ↗
Study design
14 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 14 sample titles: 14 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
Datasets on a similar topic

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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.