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A Comprehensive Adenoid Cystic Carcinomas-Derived Organoid Platform for Disease Modeling and Drug Screening Captures Interpatient Heterogeneity

GSE319175 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/03/04 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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 Comprehensive Adenoid Cystic Carcinoma-Derived Organoid Platform for Disease Modeling and Drug Screening Captures Interpatient HeterogeneityCells · 2026
Summary (written by the submitters)
Salivary adenoid cystic carcinoma (ACC) is a highly aggressive salivary gland malig-nancy characterized by infiltrative growth patterns that hinder complete resection. Lacking effective chemotherapy, recurrent or metastatic ACC remains clinically incur-able. This research aimed to develop an efficient culture system for ACC organoids, which can preserve tumor heterogeneity and establish a reliable drug screening plat-form.
Read the full summary ↓
Under our optimized culture conditions, ACC organoids grew rapidly and suc-cessfully recapitulated three characteristic histopathological patterns. Whole-genome sequencing (WGS) further confirmed they mirrored the genomic features of their pa-rental tumors, including significantly mutated genes, non-coding regulatory region mutations, copy number variation, and minor allele frequency. RNA sequencing con-firmed ACC organoids recapitulated the MYB-NFIB fusion gene. At the protein level, these organoids contained multiple cellular components, including epithelial cells, mesenchymal cells, K7+ duct cells, a-SMA+ myoepithelial cells, K5+ basement mem-brane cells, and CD44+ tumor stem cells, with proper spatial distribution patterns. With an 88% success rate, the first ACC organoids platform, incorporating normal sal-ivary gland (SG) organoids as toxicity controls, enabled high-throughput drug testing within two weeks. In conclusion, we develop an efficient culture system for ACC or-ganoids that can preserve tumor heterogeneity and establish a reliable drug screening platform for mechanistic studies and personalized precision therapy research.
Published in
A Comprehensive Adenoid Cystic Carcinoma-Derived Organoid Platform for Disease Modeling and Drug Screening Captures Interpatient Heterogeneity
Chai Y, Sui Y, Zhang X et al. · Cells 2026 · PMID 41744826 · doi:10.3390/cells15040383
This dataset
Open GSE319175 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 GSE319175_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 PRJNA1422508 and SRA study SRP676417. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41744826) ↗
Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 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
Datasets on a similar topic

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