A clinically annotated transcriptomic atlas of nervous system tumors.

ABSTRACT:

Background

While DNA methylation signatures are distinct across nervous system neoplasms, it has not been comprehensively demonstrated whether transcriptomic signatures exhibit similar uniqueness. Additionally, no large-scale dataset for comparative gene expression analyses exists. This study addresses these knowledge and resource gaps.

Methods

We compiled and harmonized raw transcriptomic and clinical data for neoplastic (n = 5,402) and nonneoplastic (n = 1,973) nervous system samples from publicly available sources, all profiled on the same microarray platform. After adjusting for surrogate variable effects ("batch effects"), machine learning methods were used to visualize, cluster, and reclassify samples with uncertain diagnoses (n = 2,225).

Results

We generated th

SUBMITTER: Le CH 

PROVIDER: S-EPMC12833534 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature