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Detection and monitoring of translocation renal cell carcinoma via plasma cell-free epigenomic profiling

GSE280708 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 161 samples Submitted 2025/10/31 Platform GPL24676Platform GPL34281
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 161 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Topic
Kidney cancerThis series is part of our curated briefing on it.
Samples
161 samples: 21 conditions, mostly with about 6 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
Cell-free DNA epigenomic profiling enables noninvasive detection and monitoring of translocation renal cell carcinomaThe Journal of clinical investigation · 2026
Summary (written by the submitters)
Translocation renal cell carcinoma (tRCC) is an aggressive fusion-driven subtype of kidney cancer that is frequently misdiagnosed due to morphologic overlap with other kidney cancer subtypes. Conventional liquid biopsy assays targeting DNA alterations are suboptimal for use in tRCC due to its paucity of genomic changes. We demonstrate the utility of cell-free chromatin profiling to noninvasively detect and monitor tRCC with high accuracy, a method that could have applicability to other genomically quiet cancers.
Published in
Cell-free DNA epigenomic profiling enables noninvasive detection and monitoring of translocation renal cell carcinoma
Garinet S, Semaan K, Li J et al. · The Journal of clinical investigation 2026 · PMID 41623182 · doi:10.1172/JCI195725
This dataset
Open GSE280708 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE280708_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1180073 and SRA study SRP542200. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41623182) ↗
Study design
21 conditions, mostly with about 6 replicates each
mTRCC_12 ×13 wTRCC_12 ×13 K27ac_TRCC_12 ×11 K4me3_CCRCC ×10 K4me3_TRCC_12 ×10 K27ac_CCRCC ×9 mTRCC ×7 K27ac_TRCC ×7 +27 more

Supports a between-group comparison across 147 samples.

How we read this: 21 replicated groups read from 161 sample titles; they account for 147 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

+ 121 more — browse all 161 samples with per-sample file links →

More Kidney cancer datasets

Search all human ChIP / ATAC / CUT&Tag 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.