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The Histone Methyltransferase KMT2D is a Critical Mediator of Lineage Plasticity and Therapeutic Response in Castration Resistant Prostate Cancer [LNCaP Bulk RNA-Seq]

GSE296115 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2025/12/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
16 samples: 8 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
The Histone Methyltransferase KMT2D Is a Critical Mediator of Lineage Plasticity and Therapeutic Response in Castration-Resistant Prostate CancerCancer research · 2026
Summary (written by the submitters)
Castration-resistant prostate cancer (CRPC) is largely dependent on the androgen receptor (AR) for growth and often exhibits hyperactive PI3K signaling, most frequently due to PTEN loss. Therapeutic pressure from anti-AR therapies can induce trans-differentiation toward an AR-independent phenotype. Recently, different subtypes of AR-independent CRPC have been redefined, with the stem cell-like (SCL) subtype emerging as one of the most prevalent.
Read the full summary ↓
Elucidation of the epigenetic mechanisms controlling the maintenance of these distinct CRPC cell states could pave the way for effective combinatorial therapies for CRPC. In this study, we identified a key role for the histone methyltransferase KMT2D in establishing the chromatin competence necessary for the recruitment of AR and FOXA1 transcription factors (TFs) that are essential for the AR transcriptional output in AR-dependent CRPC cell lines, patient derived organoids, and patient samples. Unexpectedly, KMT2D maintained the identity of the AR-low CRPC-SCL subtype and controlled activity of AP-1 TFs such as FOSL1, which acts as a master regulator of this subtype. Single cell transcriptomics and chromatin assays underscored the role of KMT2D in sustaining a mixed lineage cell state via AP-1 and FOXA1. The combined suppression of PI3K/AKT and KMT2D reduced cell proliferation in prostate cancer cells and patient-derived organoids in both CRPC-AR and CRPC-SCL subtypes. Altogether, these results unveil KMT2D as a major mediator of the epigenetic landscape in subtype-specific CRPC, contributing to tumor growth and therapeutic response.
Published in
The Histone Methyltransferase KMT2D Is a Critical Mediator of Lineage Plasticity and Therapeutic Response in Castration-Resistant Prostate Cancer
Kittane S, Ladewig E, Li T et al. · Cancer research 2026 · PMID 41379538 · doi:10.1158/0008-5472.CAN-25-2053
This dataset
Open GSE296115 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 GSE296115_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1257816 and SRA study SRP582595. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41379538) ↗
Study design
8 conditions, mostly in duplicate
LNCAP_control_DHT ×2 LNCAP_control_DHT+GDC0941 ×2 LNCAP_control_DMSO ×2 LNCAP_control_GDC0941 ×2 LNCAP_shKMT2D_DHT ×2 LNCAP_shKMT2D_DHT+GDC0941 ×2 LNCAP_shKMT2D_DMSO ×2 LNCAP_shKMT2D_GDC0941 ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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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