Integrated electrophysiological and genomic profiles of single cells reveal spiking tumor cells in human glioma

Prior studies have described the complex interplay that exists between glioma cells and neurons; however, the electrophysiological properties endogenous to glioma cells remain obscure. To address this, we employed Patch-sequencing (Patch-seq) on human glioma specimens and found that one-third of patched cells in IDH mutant (IDHmut) tumors demonstrate properties of both neurons and glia. To define these hybrid cells (HCs), which fire single, short action potentials, and discern if they are of tumoral origin, we developed the single cell rule association mining (SCRAM) computational tool to annotate each cell individually. SCRAM revealed that HCs possess select features of GABAergic neurons and oligodendrocyte precursor cells, and include both tumor and non-tumor cells. These studies characterize the combined electrophysiological and molecular properties of human glioma cells and describe a cell type in human glioma with unique electrophysiological and transcriptomic properties that may also exist in the non-tumor brain. [Display omitted] •Patch-seq identifies spiking tumor cells in human glioma•Spiking glioma cells exhibit GABAergic and glial properties in IDH mutant gliomas•SCRAM algorithm accurately annotates tumor and non-tumor cells from Patch-seq data•Spiking glioma cells confer increased survival in IDH mutant glioma Curry et al. employ simultaneous electrophysiological and genomic profiling of single cells from human glioma to identify glioma cells that fire action potentials (APs). This study introduces single cell rule association mining (SCRAM), a computational tool that provides integrated genomic and transcriptomic profiles for each single cell.