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

GSE288591 Homo sapiens (human) RNA-seq (gene expression) 34 samples Submitted 2025/08/21 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 34 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
34 samples: 17 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
Open GSE288591 in finder → Find more human RNA-seq datasets →
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 GSE288591_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 PRJNA1218647 and SRA study SRP561234. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40956611) ↗
Study design
17 conditions, mostly in duplicate
LNCaP_FGC_p29 ×2 LNCaP_95_p25 ×2 LNCaP_abl_p13 ×2 LNCaP_C42B_p6 ×2 LNCaP_shAR_pATK_p43 ×2 LNCaP_APIPC_p28 ×2 LNCaP_16D_p30 ×2 LNCaP_42D_ENZR_p14 ×2 +9 more

Supports a between-group comparison across 34 samples.

How we read this: 17 replicated groups read from 34 sample titles; they account for 34 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
Datasets on a similar topic

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