Novel method for spatial, multi-omicvisualization of single-cell heterogeneity

Project SummaryThe ability to understand and measure heterogeneity is necessary in order to make advances in fighting diseases like Alzheimerandapos sdiabetesand cancerThe ability to elucidate the differences between cell types and their locations within a tissue would provide insight into how cells interact with each other and the mechanisms that give rise to various disease statesand would help identify therapeutic pathways for new treatmentsSpecifically in cancerintratumor heterogeneity is a phenomenon that actively leads to treatment failure and relapse in cancer patientsThe limitations of current tools for understanding and measuring heterogeneity inhibit personalized medicine and the discovery of advanced therapeuticsCurrent methods are eitherincapable of providing spatial data alongside `omics data orhave workflows too cumbersome to facilitate broad adoptionbioSyntagma has developed a method for resolving heterogeneity by correlating the spatial information in cellular imagery with multi omic analysisThis workflow is easily automated and scalable through its microfluidic platform which images tissueidentifies cells of interestand then isolates imaged cells for molecular analysisWe propose to utilize this technology to enable single cell applicationsSAEstablish RNA quality after laser extraction of single cells for enrichment workflowWe will optimize tissue preparation protocols to maximize the quality of genetic material produced from the microfluidic deviceThis includes parameters of tissue preservationstaining for fluorescent targetsand laser manipulation of cellsSAEstablish single cell specificity during laser enrichment workflowIsolating single cells on a microfluidic device after imaging requires precise manipulation with laser beamsWe will demonstrate the ability to achieve single cell specificity and optimize parameters for single cell analysisSADemonstrate ability to detect transcriptomic heterogeneity within tumor samplesWe will demonstrate the clinical utility of this technology by identifying heterogeneity within immune cells of a tumor based on their relative locationsThis type of novel analysis would enable drug discovery and patient screening for personalized medicinesA successful outcome this proposal will be a method for spatially resolving single cell molecular analysis with demonstrated utility in immuno oncology biomarker discoveryApplications of the technology will extend beyond cancer into brain studies and other diseasesFurther automation to increase throughput will be the subject of a future phase II submission in order to enable translation into a clinical environment Defining heterogeneity in tumors is a barrier to precision medicine that typically results in cancer drug resistance and relapseComprehensive in situ single cell analysis is critical to evaluate heterogeneity so that patients can be screenedbetter drugs can be developedand fundamental mechanisms of different diseases can be discoveredbioSyntagma will apply its spatially resolvedmulti omics technology to the problem of single cell heterogeneity