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Multiomic assessments of LNCaP and derived cell strains reveal determinants of prostate cancer pathobiology (ATAC-Seq)

GSE288843 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 30 samples Submitted 2025/08/21 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 30 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)
Samples
30 samples: 12 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
Multiomic assessments of LNCaP and derived cell strains reveal determinants of prostate cancer pathobiologyThe Journal of clinical investigation · 2025
Summary (written by the submitters)
Overall, the LNCaP line has served as a remarkably versatile PC model, though the molecular characteristics of several important substrains have not been established nor compared in a systematic manner. In this study, we used genome-scale approaches to characterize the genomic and transcriptomic features of the parental LNCaP_FGC line, and a spectrum of 12 derivative models that have been deployed for studies of PC.
Read the full summary ↓
These studies provide insights into the biochemical features that endow PC with the potential to resist AR-directed therapy and identify features that may underlie the metastatic and treatment resistant phenotypes observed in patients. An important but under-appreciated feature of LNCaP concerns the remarkable heterogeneity of the original LNCaP isolate and the current LNCaP_FGC line which was never subjected to clonal selection. This feature, coupled with the inherent DNA mismatch repair deficiency and genomic instability, has produced a remarkable spectrum of sublines that have provided important insights into PC pathobiology, but also challenge reproducibility and the accurate interpretation of experimental findings.
Published in
Multiomic assessments of LNCaP and derived cell strains reveal determinants of prostate cancer pathobiology
Bose A, Bankhead A 3rd, Coleman I et al. · The Journal of clinical investigation 2025 · PMID 40956611 · doi:10.1172/JCI194727
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 GSE288843_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 PRJNA1219600 and SRA study SRP561789. Searching any of these in the dataset finder brings you back here.

Study design
12 conditions, mostly in duplicate
42F ×4 16D ×3 Abl ×3 42D ×2 95 ×2 APIPC ×2 AR_907 ×2 AR_909 ×2 +6 more

Supports a between-group comparison across 28 samples.

How we read this: 12 replicated groups read from 30 sample titles; they account for 28 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
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