Back

Transcriptomic landscape identifies two unrecognized ependymoma subtypes and novel pathways in medulloblastoma

Arora, S.; Holland, E.; Vardharajan, S.; Taylor, M.; Sahm, F.; Mack, S. C.; Sievers, P.; Korshunov, A.; Nuechterlein, N.; Jensen, M.; Glatzer, G.

2024-10-22 bioinformatics
10.1101/2024.10.21.619495 bioRxiv
Show abstract

Medulloblastoma and ependymoma are common pediatric central nervous system tumors with significant molecular and clinical heterogeneity. We collected bulk RNA sequencing data from 888 medulloblastoma and 370 ependymoma tumors to establish a comprehensive reference landscape. Following rigorous batch effect correction, normalization, and dimensionality reduction, we constructed a unified landscape to explore gene expression, signaling pathways, RNA fusions, and copy number variations. Our analysis revealed distinct clustering patterns, including two primary ependymoma compartments, EPN-E1 and EPN-E2, each with specific RNA fusions and molecular signatures. In medulloblastoma, we observed precise stratification of Group 3/4 tumors by subtype and in SHH tumors by patient age. This landscape serves as a vital resource for identifying biomarkers, refining diagnoses, and enables the mapping of new patients bulk RNA-seq data onto the reference framework to predict biology and outcome from nearest neighbor analysis facilitate accurate disease subtype identification. The landscape is accessible via Oncoscape, an interactive platform, empowering global exploration and application. One Sentence SummaryA landscape built using only Transcriptomic analysis for medulloblastoma and ependymoma reveals novel insights about subtype-specific biology.

Published in Neuro-Oncology (predicted rank #1) · training set

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.