Statistical & Machine Learning Approaches to Interpretation of the Tissue Microenvironment Using Spatial Immuno-profiling & Spatial Transcriptomics
Conference
65th ISI World Statistics Congress 2025
Format: IPS Abstract - WSC 2025
Keywords: functional data analysis, personalized medicine
Session: IPS 695 - Statistics Concourse of Machine Learning and Artificial Intelligence
Thursday 9 October 10:50 a.m. - 12:30 p.m. (Europe/Amsterdam)
Abstract
Spatial profiling technologies like hyper-plex immunostaining in tissue, spatial transcriptomics etc have the potential to enable a multi-factorial, multi-modal characterization of the tissue microenvironment. Scalable, quantitative methods to analyze and interpret spatial patterns of protein staining and gene expression are required to understand cell-cell relationships in the context of local variations in tissue structure. Objective scoring methods inspired by recent advances in statistics and machine learning can serve to aid the interpretation of these datasets, as well as their integration with other, companion data like genomics. In this talk, we will discuss elements of spatial profiling from multiple studies as well as paradigms from statistics and machine learning in the context of these problems. This talk will also discuss the use of AI/ML and spatial analytics of the tumor microenvironment to derive spatial biomarkers of immunotherapy.