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An RNA seq-based reference landscape of human normal and neoplastic brain
Sonali Arora1, Frank Szulzewsky1, Matt Jensen1
1Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA 98109.
Biorxiv : the Preprint Server for Biology
|January 30, 2023
Summary
This study integrates multiple brain tumor datasets to create a comprehensive reference map. This resource enables comparisons of gene expression and pathways across normal brain, adult gliomas, and pediatric brain tumors.
Area of Science:
- Neuroscience
- Genomics
- Bioinformatics
Background:
- Understanding the molecular differences between normal brain tissue and neoplastic conditions is crucial for developing targeted therapies.
- Existing large-scale datasets are often fragmented, hindering comprehensive comparative analysis.
Approach:
- Combined five large-scale public RNA-sequencing datasets, correcting for batch effects.
- Applied Uniform Manifold Approximation and Projection (UMAP) to generate a unified reference landscape (Brain-UMAP).
- Integrated clinical metadata, gene expression, mutations, copy number variations, and gene fusions.
Key Points:
- The Brain-UMAP reference includes 702 adult gliomas, 802 pediatric tumors, and 1409 normal brain samples.
- Normal brain regions and tumor types form distinct clusters within the landscape.
- Comparative gene expression and Gene Ontology (GO) patterns are readily visualized.
Conclusions:
- This meta-analysis provides a novel resource for comparing gene expression and pathways across adult gliomas, pediatric brain tumors, and normal brain.
- The interactive online tool Oncoscape offers open-source access for visualization and analysis by the scientific community.
