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Discovery and Validation of a 15-Gene Prognostic Signature for Clear Cell Renal Cell Carcinoma

GSE254566 Homo sapiens (human) RNA-seq (gene expression) 91 samples Submitted 2024/04/01 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 91 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
Kidney cancerThis series is part of our curated briefing on it.
Samples
91 samples: 89 × Myriad vs 2 × MyriadR_2234Groups 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
Discovery and Validation of a 15-Gene Prognostic Signature for Clear Cell Renal Cell CarcinomaJCO precision oncology · 2024
Summary (written by the submitters)
We report a kidney cancer tissue-based prognostic biomarker encompassing 15 genes (15G score) to classify patients into low versus high risk for recurrence after curative nephrectomy. The 15G score was independently associated with disease free survival adjusting for clinicopathologic variables as well as existing clinical risk calculators or nomograms.
Read the full summary ↓
By improving risk stratification of patients with ccRCC, the 15G score has the capacity to facilitate selection of biopsy confirmed small renal cancers (T1a) for treatment versus surveillance; inform intensity and duration of surveillance after curative nephrectomy; and to potentially facilitate patient selection for adjuvant systemic therapy. We retrospectively identified 110 patients who underwent radical nephrectomy for ccRCC (discovery cohort). Patients who recurred were matched based on grade/stage to patients without recurrence. Capture whole transcriptome sequencing was performed on RNA isolated from archival tissue using the Illumina platform. We developed a gene-expression signature to predict recurrence/disease-free survival (DFS) using a 15-fold lasso and elastic-net regularized linear Cox model. We derived the 31-gene cell cycle progression (mxCCP) score using RNAseq data for each patient. Kaplan-Meier (KM) curves and multivariable Cox proportional hazard testing were used to validate the independent prognostic impact of the gene-expression signature on DFS, disease specific survival (DSS) and overall survival (OS) in two validation datasets (combined n=761).
Published in
Discovery and Validation of a 15-Gene Prognostic Signature for Clear Cell Renal Cell Carcinoma
Mehra R, Nallandhighal S, Cotta B et al. · JCO precision oncology 2024 · PMID 38810179 · doi:10.1200/PO.23.00565
This dataset
Open GSE254566 in finder → Find more human RNA-seq datasets → Kidney cancer 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 GSE254566_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 PRJNA1071056 and SRA study SRP486873. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38810179) ↗
Study design
89 × Myriad vs 2 × MyriadR_2234

Supports a between-group comparison across 91 samples.

How we read this: 2 replicated groups read from 91 sample titles; they account for 91 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

+ 51 more — browse all 91 samples with per-sample file links →

More Kidney 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.