Baker, G. | bioRxiv Science

bioRxiv2025

Drug and single-cell gene expression integration identifies sensitive and resistant glioblastoma cell populations

Glioblastoma (GBM) remains the most common and lethal adult malignant primary brain cancer with few treatment options. A significant issue hindering GBM therapeutic development is intratumor heterogeneity. GBM tumors contain neoplastic cells within a spectrum of different transcriptional states. Identifying effective therapeutics requires a platform that predicts the differential sensitivity and resistance of these states to various treatments. Here, we developed a novel framework, ISOSCELES (Inferred cell Sensitivity Operating on the integration of Single-Cell Expression and L1000 Expression Signatures), to quantify the cellular drug sensitivity and resistance landscape. Using single-cell RNA sequencing of newly diagnosed and recurrent GBM tumors, we identified compounds from the LINCS L1000 database with transcriptional response signatures selectively discordant with distinct GBM cell states. We validated the significance of these findings in vitro, ex vivo, and in vivo, and identified a novel combination of an OLIG2 inhibitor and Depatux-M for GBM. Our studies suggest that ISOSCELES identifies cell states sensitive and resistant to targeted therapies in GBM and that it can be applied to identify new synergistic combinations. HighlightsO_LIIntegration of GBM single-cell RNA sequencing data with L1000-derived drug response signatures facilitates clustering of tumor cells and small molecules on cell-drug connectivity. C_LIO_LICell-drug connectivity predicts the identities of drug-sensitive and resistant cell states. C_LIO_LIIn silico perturbation analysis using cell-drug connectivity predicts drug-induced changes in the cell-drug connectivity landscape in vivo. C_LIO_LIIn silico perturbation analysis to predict drug-induced changes in the tumor cell-drug connectivity landscape predicts drug combinations that synergize in vivo to extend survival. C_LI

cancer biology↗

bioRxiv2019

Dopaminergic control of postnatal mammalian spinal network function is predominantly inhibitory.

Dopamine is well known to regulate movement through the differential control of direct and indirect pathways in the striatum that express D1 and D2 receptors respectively. The spinal cord also expresses all dopamine receptors however; how the specific receptors regulate spinal network output in mammals is poorly understood. We explore the receptor-specific mechanisms that underlie dopaminergic control of spinal network output of neonatal mice during changes in spinal network excitability. During spontaneous activity, which is a characteristic of developing spinal networks operating in a low excitability state, we found that dopamine is primarily inhibitory. We uncover an excitatory D1-mediated effect of dopamine on motoneurons and network output that also involves co-activation with D2 receptors. Critically, these excitatory actions require higher concentrations of dopamine; however, analysis of dopamine concentrations of neonates indicates that endogenous levels of spinal dopamine are low. Because endogenous levels of spinal dopamine are low, this excitatory dopaminergic pathway is likely physiologically-silent at this stage in development. In contrast, the inhibitory effect of dopamine, at low physiological concentrations is mediated by parallel activation of D2, D3, D4 and 2 receptors which is reproduced when endogenous dopamine levels are increased by blocking dopamine reuptake and metabolism. We provide evidence in support of dedicated spinal network components that are controlled by excitatory D1 and inhibitory D2 receptors that is reminiscent of the classic dopaminergic indirect and direct pathway within the striatum. These results indicate that network state is an important factor that dictates receptor-specific and therefore dose-dependent control of neuromodulators on spinal network output and advances our understanding of how neuromodulators regulate neural networks under dynamically changing excitability.\n\nSignificance statementMonoaminergic neuromodulation of neural networks is dependent not only on target receptors but also on network state. We studied the concentration-dependent control of spinal networks of the neonatal mouse, in vitro, during a low excitability state characterized by spontaneous network activity. Spontaneous activity is an essential element for the development of networks. Under these conditions, we defined converging receptor and cellular mechanisms that contribute to the diverse, concentration-dependent control of spinal motor networks by dopamine, in vitro. These experiments advance understanding of how monoamines modulate neuronal networks under dynamically changing excitability conditions and provide evidence of dedicated D1 and D2 regulated network components in the spinal cord that are consistent with those reported in the striatum.

neuroscience↗