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Synergistic Inhibition of PI3K and HSP90 Enhanced Antitumorigenic Efficacy in Adrenocortical Carcinoma

GSE330925 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/07/23 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
Adrenocortical cancer (ACC) is a rare and aggressive malignancy with poor survival due to a lack of effective treatments; therefore, it is important to identify therapies that can be readily studied in clinical trials. Quantitative high-throughput drug combination screening identified potent synergy between phosphatidylinositol-3-kinase (PI3K) inhibition and heat shock protein 90 (HSP90) inhibition.
Read the full summary ↓
This GEO submission contains the 18 bulk RNA-seq samples from NCI-H295R ACC cells that were used in the publication to evaluate transcriptional responses to PI3K and HSP90 inhibitors alone and in combination. The submitted samples include untreated controls and cells treated with STA9090, PIK75, BGT226, STA9090+PIK75, or STA9090+BGT226, with three biological replicates per condition. These RNA-seq data supported the comparison of molecular responses induced by PI3K/HSP90 inhibitor combinations in ACC cells, including distinct responses associated with PIK75+STA9090 and BGT226+STA9090 treatment.
This dataset
Open GSE330925 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 GSE330925_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 PRJNA1466199 and SRA study SRP700490. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
Untreated ACC cells HC ×3 STA9090 treated ACC cells HS ×3 PIK75 treated ACC cells HP ×3 BGT226 treated ACC cells HB ×3 STA9090+PIK75 treated ACC cells HSP ×3 STA9090+BGT226 treated ACC cells HSB ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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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.