A0556
Title: Integrating transcriptomic and pathomic features to reconstruct 3D tissue maps with super-resolution
Authors: Mingyao Li - University of Pennsylvania (United States) [presenting]
Abstract: Solid tissues form complex 3D structures, and examining the tissue microenvironment in a 3D context allows researchers to gain a comprehensive understanding of how cells interact within the original tissue context. This 3D information also reveals spatial relationships between different cell types and signaling pathways that are not observable in 2D tissue sections. The purpose is to present the recently developed tool that is aimed at generating single-cell resolution 3D ST tissue maps while significantly reducing experimental costs. By integrating information from spatial transcriptomics and pathology imaging data, our method gradually increases gene expression resolution down to the single-cell level. Additionally, an algorithm is developed to register tissue sections obtained from serial tissue cuts and impute missing gene expression data between tissue gaps, enabling the construction of accurate 3D tissue volumes. The resulting analysis will not only generate a single-cell resolution spatial transcriptomics tissue map but also facilitate detailed characterization and quantification of tissue structures of interest in 3D.
