Case Study: Beijing Normal University achieves new glioma classification insights with Qlucore Omics Explorer

Statistical analysis could improve understanding and treatment of different brain tumors

Beijing Normal University, working with Professor Xiaolong Fan and colleagues in Beijing and Sweden, set out to improve glioma classification by moving beyond morphology-based diagnosis. They needed a way to analyze gene expression, genomic, and clinical datasets to better understand brain tumor pathogenesis and support more accurate diagnosis and treatment decisions. Qlucore’s Omics Explorer was used to help biologists apply bioinformatics methods without advanced mathematical training.

Using Qlucore Omics Explorer, the team analyzed publicly available multi-region datasets and identified two key gene co-expression modules, EGFR and PDGFRA, that enabled a new glioma classification framework. Qlucore helped the researchers propose three major glioma subtypes—EM, PM, and EMlowPMlow—distinct in prognosis, genetic abnormalities, and lineage-related signatures, and the findings were published in PNAS. The project also delivered a practical impact by enabling cross-source data integration and supporting a biologist-friendly analysis workflow.

Beijing Normal University