Multiplexed imaging generates rich datasets where extracting meaningful insights requires more than predefined gates. 

In this webinar, we present a real-world use case analyzing tertiary lymphoid structures (TLS) in non-small cell lung cancer (NSCLC) using whole-slide multiplex immunofluorescence images acquired on the Orion™ platform (RareCyte). We demonstrate how standard HALO® workflows, including AI-driven tissue classification and cell segmentation, can be seamlessly combined with unbiased high-dimensional analysis, all within the same software. 

Using K-means, Phenograph, and UMAP, we explore phenotypic diversity within TLS from dense tumor regions and highly infiltrated zones. HALO® High Dimensional Analysis reveals biologically relevant differences between these zones beyond supervised phenotypes. Importantly, the dynamic link between UMAP plots and the original tissue image provides biological meaning to clustering results and enables clear spatial validation.