Investigate FOXA2, NKX2-1 and P300 regulated transcription program by RNA-seq in prostate cancer cells.
RNA-seq (gene expression) · human · 52 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
- 52 samples: 52 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
- NKX2-1 drives neuroendocrine transdifferentiation of prostate cancer via epigenetic and 3D chromatin remodelingNature genetics · 2025
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE239275_RAW.tar (it can run to tens of gigabytes).
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: 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 PRJNA998732 and SRA study SRP451656. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 52 sample titles: 52 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.
- GSM7662426 LNCaP, FOXA2-D0 1#
- GSM7662427 LNCaP, FOXA2-D0 2#
- GSM7662428 LNCaP, FOXA2-D0 3#
- GSM7662429 LNCaP, FOXA2-D2 1#
- GSM7662430 LNCaP, FOXA2-D2 2#
- GSM7662431 LNCaP, FOXA2-D2 3#
- GSM7662432 LNCaP, FOXA2-D7 1#
- GSM7662433 LNCaP, FOXA2-D7 2#
- GSM7662434 LNCaP, FOXA2-D7 3#
- GSM7662435 LNCaP, FOXA2-D14 1#
- GSM7662436 LNCaP, FOXA2-D14 2#
- GSM7662437 LNCaP, FOXA2-D14 3#
- GSM7662438 LNCaP, FOXA2-D21 1#
- GSM7662439 LNCaP, FOXA2-D21 2#
- GSM7662440 LNCaP, FOXA2-D21 3#
- GSM7662441 LNCaP, FOXA2-D28 1#
- GSM7662442 LNCaP, FOXA2-D28 2#
- GSM7662443 LNCaP, FOXA2-D28 3#
- GSM7662444 22Rv1, plv-Week4 1#
- GSM7662445 22Rv1, plv-Week4 2#
- GSM7662446 22Rv1, FOXA2-Week4 1#
- GSM7662447 22Rv1, FOXA2-Week4 2#
- GSM7662448 LuNE, DMSO 1#
- GSM7662449 LuNE, DMSO 2#
- GSM7662450 LuNE, DMSO 3#
- GSM7662451 LuNE, CCS1477 1#
- GSM7662452 LuNE, CCS1477 2#
- GSM7662453 LuNE, CCS1477 3#
- GSM7662454 LuNE, sgNC 1#
- GSM7662455 LuNE, sgNC 2#
- GSM7662456 LuNE, sgNC 3#
- GSM7662457 LuNE, sgNKX2-1 1#
- GSM7662458 LuNE, sgNKX2-1 2#
- GSM7662459 LuNE, sgNKX2-1 3#
- GSM7662460 LuNE, sgFOXA2 1#
- GSM7662461 LuNE, sgFOXA2 2#
- GSM7662462 LuNE, sgFOXA2 3#
- GSM7662463 LuNE, sgFOXA2+NKX2-1 1#
- GSM7662464 LuNE, sgFOXA2+NKX2-1 2#
- GSM7662465 LuNE, sgFOXA2+NKX2-1 3#
+ 12 more — browse all 52 samples with per-sample file links →
- GSE245969 EP300/CREBBP acetyltransferase inhibition limits steroid receptor and FOXA1 signaling in prostate cancer cells 122 samples shares p300, prostate
- GSE269826 Conserved patterns of transcriptional dysregulation, heterogeneity and cell states in clear cell kidney cancer [scRNA-seq] 79 samples shares transcription, rna-seq
- GSE335040 Evolutionary guided transcription factor design programs novel T cell states [RNAseq_Paired] 33 samples shares transcription, program
- GSE310664 Analysis of experimental colorectal liver metastases identifies distinct proliferation independent transcriptional programs in micro- versus macrometastases 22 samples shares transcription, program
- GSE189357 Spatiotemporal transcriptional atlas of lung adenocarcinoma from adenocarcinoma in situ to invasive carcinoma [scRNA-seq] 9 samples shares transcription, rna-seq
- GSE335058 Evolutionary guided transcription factor design programs novel T cell states [ChIP-Seq] 66 samples shares transcription, program
- GSE270503 Epigenetic heterogeneity and state-specific transcriptional programs determine differential drug response in osteosarcoma [Cut&Run] 56 samples shares transcription, program
- GSE318861 Quantitative analysis of Tat-dependent and host-driven HIV transcription by ChIP-seq and RNA-seq 52 samples shares transcription, rna-seq
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.