GEO series

PIKfyve-regulated lipid metabolism as a therapeutic vulnerability in neuroendocrine prostate cancer

GSE295392 Homo sapiens (human) RNA-seq (gene expression) 82 samples Submitted 2026/08/05 Platform GPL16791Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 82 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: 82 samples: 74 distinct titles, 8 of them repeatedGroups 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: A Stress-Adaptive Lipid Kinase Axis Defines Metabolic Vulnerabilities in Neuroendocrine Prostate CancerbioRxiv : the preprint server for biology · 2026

Summary (written by the submitters)

Neuroendocrine prostate cancer (NEPC) is a lethal, androgen receptor (AR)-independent subtype of prostate cancer that often arises after AR pathway inhibition and has limited treatment options. We hypothesized that NEPC might be susceptible to metabolic interventions targeting PIKfyve. Here, we identify the lipid kinase PIKfyve as overexpressed in advanced prostate cancers and find that NEPC cells are especially dependent on PIKfyve-driven lipid metabolism.

Read the full summary ↓

Pharmacological PIKfyve inhibition triggered rapid apoptosis in NEPC cells. Mechanistically, AR pathway loss in NEPC reprogrammed tumor cells to tolerate sustained stress through autophagy. PIKfyve blockade forced NEPC cells to rely on de novo lipid synthesis for survival, and accordingly, dual inhibition of PIKfyve and de novo lipid synthesis synergistically suppressed NEPC tumor growth. These findings reveal a unique metabolic vulnerability in NEPC and suggest that targeting PIKfyve-dependent lipid metabolism could be a promising therapeutic strategy for this aggressive prostate cancer subtype.

Published in

A Stress-Adaptive Lipid Kinase Axis Defines Metabolic Vulnerabilities in Neuroendocrine Prostate Cancer

Zheng Y, Cheng C, Cao Y et al. · bioRxiv : the preprint server for biology 2026 · PMID 42528528 · doi:10.64898/2026.06.15.732391

This dataset

Open GSE295392 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 GSE295392_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 PRJNA1254508 and SRA study SRP580726. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42528528) ↗

Study design

74 distinct titles, 8 of them repeated

LTL331R-CL 5%FBS DMSO 6h biol ×2 LTL331R-CL 5%FBS ESK981 1µM 6h biol ×2 LTL331R-CL 5%FBS Apilimod 1µM 6h biol ×2 LTL331R-CL 5%FBS PIK5-33d 0.3µM 6h biol ×2 LTL331R-CL 0.1%FBS DMSO 6h biol ×2 LTL331R-CL 0.1%FBS ESK981 1µM 6h biol ×2 LTL331R-CL 0.1%FBS Apilimod 1µM 6h biol ×2 LTL331R-CL 0.1%FBS PIK5-33d 0.3µM 6h biol ×2

How we read this: Read from 82 sample titles: 74 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.

Samples in this study

GSM8947079 LTL331R-CL 5%FBS DMSO 6h biol rep 1
GSM8947080 LTL331R-CL 5%FBS DMSO 6h biol rep 2
GSM8947081 LTL331R-CL 5%FBS ESK981 1µM 6h biol rep 1
GSM8947082 LTL331R-CL 5%FBS ESK981 1µM 6h biol rep 2
GSM8947083 LTL331R-CL 5%FBS Apilimod 1µM 6h biol rep 1
GSM8947084 LTL331R-CL 5%FBS Apilimod 1µM 6h biol rep 2
GSM8947085 LTL331R-CL 5%FBS PIK5-33d 0.3µM 6h biol rep 1
GSM8947086 LTL331R-CL 5%FBS PIK5-33d 0.3µM 6h biol rep 2
GSM8947087 LTL331R-CL 0.1%FBS DMSO 6h biol rep 1
GSM8947088 LTL331R-CL 0.1%FBS DMSO 6h biol rep 2
GSM8947089 LTL331R-CL 0.1%FBS ESK981 1µM 6h biol rep 1
GSM8947090 LTL331R-CL 0.1%FBS ESK981 1µM 6h biol rep 2
GSM8947091 LTL331R-CL 0.1%FBS Apilimod 1µM 6h biol rep 1
GSM8947092 LTL331R-CL 0.1%FBS Apilimod 1µM 6h biol rep 2
GSM8947093 LTL331R-CL 0.1%FBS PIK5-33d 0.3µM 6h biol rep 1
GSM8947094 LTL331R-CL 0.1%FBS PIK5-33d 0.3µM 6h biol rep 2
GSM8947095 MDA-PCa-146-12 8R
GSM8947096 MDA-PCa-146-12 8L
GSM8947097 VCaP 20R
GSM8947098 VCaP 2101L
GSM8947099 VCaP 2101R
GSM8947100 VCaP 2104L
GSM8947101 VCaP 2104R
GSM8947102 CRPC VCaP 79R
GSM8947103 CRPC VCaP 79L
GSM8947104 CRPC VCaP 81R
GSM8947105 CRPC VCaP 81L
GSM8947106 LNCaP 512R
GSM8947107 LNCaP 512L
GSM8947108 LNCaP 537L
GSM8947109 LTL610 1307R
GSM8947110 LTL610 1307L
GSM8947111 LTL610 1320R
GSM8947112 LTL610 1320L
GSM8947113 LTL610 1740R
GSM8947114 LTL610 1740L
GSM8947115 LTL610 1745R
GSM8947116 LTL610 1745L
GSM8947117 LTL331R 1572R
GSM8947118 LTL331R 1572L

+ 42 more — browse all 82 samples with per-sample file links →

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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.