Related Experiment Video
Updated: May 25, 2026
Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor
Published on: August 25, 2023
Single-cell multi-omic integration analysis prioritizes druggable genes and reveals cell-type-specific causal effects
Yu-Feng Huang1, Kun-Long Wang2
1The First Clinical Medical School, Shanxi Medical University, Taiyuan, China. huangyufeng@sxmu.edu.cn.
Background:
Gliomas constitute 80% of malignant brain tumors, with glioblastoma (GBM) being the most aggressive subtype. The single-cell-level mechanisms underlying gliomagenesis are poorly understood, hindering therapeutic development. We combine genome-wide association studies (GWAS) with bulk tissue and single-cell multi-omics to prioritize genetically supported candidate genes and to explore potential cell-type-specific mechanisms relevant to gliomagenesis.
Methods:
We integrated the largest glioma GWAS with brain-specific multi-omics to prioritize genetically supported candidate genes using two broad categories of prioritized methods. Biological enrichment, differential gene expression, and CRISPR/miRNA were used to assess target enrichment and druggability. By integrating single-cell multi-omics data (genomics, transcriptomics, epigenomics), we investigated GBM-relevant cells, tumor microenvironment (TME) interactions, and cell-type-specific mechanisms in glioblastomagenesis. Additionally, phenome-wide association studies (PheWAS) and drug repurposing analyses were conducted to annotate genetic pleiotropy and enhance drug repositioning.
Results:
We prioritized 11 high-confidence and 47 putatively causal genes, most of which are druggable. Astrocytes and oligodendrocyte precursor cells (OPCs) were implicated as GBM-relevant cell populations, with significantly increased TME cell communication between these populations and neurons. We further identified 14 putative cell-type-specific effects related to glioblastomagenesis, including three high-confidence genes (EGFR in astrocytes, CDKN2A in OPCs, and JAK1 in excitatory neurons). Most effects (85.7%, 12/14) were associated with non-GBM-relevant cell cells, encompassing both glial and neural cells.
Conclusions:
This study systematically identifies genetically supported candidate genes in gliomagenesis and their cell-type-specific effects. These findings provide a resource for future mechanistic investigation and may help inform the development of more precise therapeutic hypotheses.
