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Characterization of 3′UTRCES-mediated alternative polyadenylation (APA) engineering in prostate cancer and 293FT cells

GSE210746 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2026/05/22 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 15 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
Prostate cancerThis series is part of our curated briefing on it.
Samples
15 samples: 6 conditions, mostly in triplicateGroups 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
Programmable mRNA 3'UTR engineering restores MHC-I and overcomes immune evasion in prostate cancerNature biomedical engineering · 2026
Summary (written by the submitters)
To determine SPSB1 3′UTR alternative polyadenylation (APA) usage following 3′UTRCES-mediated editing in prostate cancer cells, and to evaluate global gene expression changes and potential off-target effects of the 3′UTRCES system in 293FT cells.
Published in
Programmable mRNA 3'UTR engineering restores MHC-I and overcomes immune evasion in prostate cancer
Huang F, Yuan F, Li K et al. · Nature biomedical engineering 2026 · PMID 42303814 · doi:10.1038/s41551-026-01720-9
This dataset
Open GSE210746 in finder → Find more human RNA-seq datasets → Prostate 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 GSE210746_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 PRJNA867357 and SRA study SRP390450. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42303814) ↗
Study design
6 conditions, mostly in triplicate
293FT_Dummy ×3 293FT_SPSB1-g5 ×3 293FT_SPSB1-g6 ×3 LNCaP-abl_gCtrl ×2 LNCaP-abl_SPSB1-g5 ×2 LNCaP-abl_SPSB1-g6 ×2

Supports a between-group comparison across 15 samples.

How we read this: 6 replicated groups read from 15 sample titles; they account for 15 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
More Prostate 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.