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CUT&RUN profiling of EZH2, H3K27me3, and H3K4me3 enrichment in FACS-sorted CD70⁻ and CD70⁺ tumor cells from untreated ex vivo ccRCC and HGSOC patient-derived xenografts.

GSE311098 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 82 samples Submitted 2026/02/26 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 82 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
Ovarian cancerThis series is part of our curated briefing on it.
Samples
82 samples: 31 conditions, mostly in duplicateGroups 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
Sensitive CAR T cells redefine targetable CD70 expression in solid tumorsScience (New York, N.Y.) · 2026
Summary (written by the submitters)
CD70 expression in solid tumors is heterogeneous. We demonstrate that cells appearing CD70-negative retain ultra-low levels of CD70 expression. These cells that appear negative by conventional detection methods. Bulk ATAC-seq analysis of FACS-sorted CD70⁻ and CD70⁺ tumor populations revealed differential chromatin accessibility, indicating epigenetic regulation of CD70 expression in both ccRCC and HGSOC models.
Read the full summary ↓
CUT&RUN profiling of EZH2, H3K27me3, and H3K4me3 in FACS-sorted CD70⁻ and CD70⁺ tumor cells derived from ccRCC and HGSOC PDXs revealed enrichment of differential repressive and activating histone modifications.
Published in
Sensitive CAR T cells redefine targetable CD70 expression in solid tumors
Hanina SA, Park T, Lopez M et al. · Science (New York, N.Y.) 2026 · PMID 41747043 · doi:10.1126/science.adv7378
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 GSE311098_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1368670 and SRA study SRP648345. Searching any of these in the dataset finder brings you back here.

Study design
31 conditions, mostly in duplicate
C&R, OV4, OVARIAN, CD70lo, EZH2, ×4 C&R, OV4, OVARIAN, CD70lo, H3K4me3, ×4 C&R, OV4, OVARIAN, CD70Pos, H3K27me3, ×4 C&R, OV4, OVARIAN, CD70Pos, H3K4me3, ×4 C&R, OV4, OVARIAN, CD70lo, H3K27me3, ×3 C&R, OV4, OVARIAN, CD70Pos, EZH2, ×3 C&R, OV4, OVARIAN, EZH2, ×3 C&R, OV4, OVARIAN, H3K27me3, ×3 +29 more

Supports a between-group comparison across 76 samples.

How we read this: 31 replicated groups read from 82 sample titles; they account for 76 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

+ 42 more — browse all 82 samples with per-sample file links →

More Ovarian cancer datasets

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

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