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Patient-Derived Meningioma Organoids: A Reliable Model for Studying Human Tumor Pathophysiology

GSE287174 Homo sapiens (human) RNA-seq (gene expression) 65 samples Submitted 2025/02/11 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 65 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
65 samples: 22 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)
Introduction: Meningiomas are the most common primary central nervous system tumors, constituting 39.7% of intracranial tumors. Although generally benign, some exhibit aggressive be-havior and risk of recurrence, necessitating adjuvant therapy and repeat surgical in-terventions. Molecular studies have identified tumor-driving mutations, leading to tar-geted therapies and clinical trials.
Read the full summary ↓
However, translating preclinical findings into clinical success is often hindered by limitations in current meningioma tumor models. This study aims to develop and validate a standardized protocol for establishing patient-derived meningioma organoids (MEN-O) that faithfully replicate human disease. Methods: We obtained meningioma samples from neurosurgical resections and MEN-O were developed using an optimized culture protocol. Histological and immunohistochemical analyses were used to assess the resemblance of MEN-O to original tumor tissues. RNA sequencing compared transcriptional signatures between MEN-O and corresponding patient-resected tissues. Results: MEN-O were successfully established from patient-resected samples and maintained in culture for up to four weeks, showing stable growth and structural integrity. Histopathological analysis revealed that MEN-O preserved key architectural features, including cellular organization, nuclear mor-phology, and proliferation rates. Immunohistochemical staining for meningioma-specific markers, such as progesterone receptor, confirmed similar expression patterns to parental tumors. Transcriptomic profiling demonstrated that MEN-O retained the transcriptional signatures of original tissues, including genes associated with meningioma pathology (NF2, CDKN2A, TP53). Differential expression and deconvolution analyses showed that MEN-O contained diverse cell populations, including tumor and stromal cells, while preserving the immune microenvironment, as validated by histopathological and tran-scriptomic profiling. Conclusion: We established a robust, reproducible protocol for generating MEN-O, which faithfully replicates the histopathological, molecular, and cellular characteristics of original tumors. MEN-O provide a valuable model for studying meningioma biology and evaluating therapeutic strategies.
This dataset
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.

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 GSE287174_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1211555 and SRA study SRP557872. Searching any of these in the dataset finder brings you back here.

Study design
22 conditions, mostly in triplicate
Patient resected tumor P2 ×3 Patient resected tumor P3 ×3 Patient resected tumor P4 ×3 Patient resected tumor P5A ×3 Patient resected tumor P5B ×3 Patient resected tumor P6 ×3 Patient resected tumor P7 ×3 Patient resected tumor P8 ×3 +14 more

Supports a between-group comparison across 65 samples.

How we read this: 22 replicated groups read from 65 sample titles; they account for 65 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

+ 25 more — browse all 65 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.