Unraveling Hypoxia-Driven Gene and Methylation Signatures in Meningioma: Identifying Novel Biomarkers and Therapeutic Targets
DNA methylation · human · 10 samples
- What it is
- DNA methylationChemical marks on DNA that help switch genes on or off.
- Organism
- Homo sapiens (human)
- Samples
- 10 samples: 3 × IOMM-Lee norm_biol vs 3 × IOMM-Lee hyp_biol vs 2 × Normoxia EPIC V2, vs 2 × Hypoxia EPIC V2,Groups 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
- Novel insights into hypoxia-driven transcriptomic and epigenetic landscapes in grade 3 meningiomaJournal of translational medicine · 2025
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE282352_RAW.tar (it can run to tens of gigabytes).
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: Look for beta-value tables or raw IDAT files among the supplementary files.
Also filed as BioProject PRJNA1188173 and SRA study SRP546254. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 4 replicated groups read from 10 sample titles; they account for 10 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.
- GSM8641722 IOMM-Lee norm_biol rep1 IOMM-Lee norm_biol
- GSM8641723 IOMM-Lee norm_biol rep2 IOMM-Lee norm_biol
- GSM8641724 IOMM-Lee norm_biol rep3 IOMM-Lee norm_biol
- GSM8641725 IOMM-Lee hyp_biol rep1 IOMM-Lee hyp_biol
- GSM8641726 IOMM-Lee hyp_biol rep2 IOMM-Lee hyp_biol
- GSM8641727 IOMM-Lee hyp_biol rep3 IOMM-Lee hyp_biol
- GSM8641730 Normoxia EPIC V2, Replicate 1 Normoxia EPIC V2,
- GSM8641731 Normoxia EPIC V2, Replicate 2 Normoxia EPIC V2,
- GSM8641732 Hypoxia EPIC V2, Replicate 1 Hypoxia EPIC V2,
- GSM8641733 Hypoxia EPIC V2, Replicate 2 Hypoxia EPIC V2,
- GSE304097 DNA methylation profiling identifies long-range epigenetic silencing of clustered protocadherins as a key determinant of meningioma progression 293 samples shares methylation, meningioma
- GSE298243 Single-Cell Profiling of DNA Methylation in Autism Spectrum Disorder Prefrontal Cortex Reveals Distinct Regulatory and Aging Signatures 49 samples shares methylation, signatures
- GSE290805 Meningioma microenvironment harbors a rich immune landscape with therapeutic implications (Bulk RNA-seq part) 47 samples shares therapeutic, meningioma
- GSE308390 Identifying Potential Biomarkers Associated with Sebum Production, Pore Enlargement, and Comedones Using Transcriptomic Approaches 24 samples shares identifying, biomarkers
- GSE320212 Identifying Senescence and Immune Biomarkers Predictive of Benefit to Combined CDK4/6 and PD-1 Blockade in Dedifferentiated Liposarcoma: Single-Cell RNA-seq of Serial Tumor Biopsies 23 samples shares identifying, biomarkers
- GSE253957 Methylation of the epigenetic regulator KMT2D by SMYD2 contributes to therapeutic response in hormone-dependent breast cancer [SMYD2_KD_RNA] 12 samples shares methylation, therapeutic
- GSE300385 Discovery and Evaluation of Biomarkers for Triple-Negative Breast Cancer Subtypes Uncovers Patient Stratification and Targeted Therapeutic Strategies 12 samples shares therapeutic, biomarkers
- GSE309430 Blood-Based Gene Signatures Associated with Therapeutic Response to Anti-TNF Therapy in Rheumatoid Arthritis: A Combined Meta-Analytical and Machine Learning Approach 8 samples shares therapeutic, signatures
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.