Deep spatial-omics to aid personalization of precision medicine in metastatic recurrent Head & Neck Cancers

Abstract

Immune checkpoint inhibitor (ICI) modality has had a limited success (<20%) in treating metastatic recurrent Head & Neck Oropharyngeal Squamous cell carcinomas (OPSCCs). To improve response rates to ICIs, tailored approaches capable to capture the tumor complexity and dynamics of each patients disease are needed. Here, we performed advanced analyses of spatial proteogenomic technologies to demonstrate that: (i) compared to standard histopathology, spatial transcriptomics better-identified tumor cells and could specifically classify them into two different metabolic states with therapeutic implications; (ii) our new method (Spatial Proteomics-informed cell deconvolution method or SPiD) improved profiling of local immune cell types relevant to disease progression, (iii) identified clinically relevant alternative treatments and a rational explanation for checkpoint inhibitor therapy failure through comparative analysis of pre- and post-failure tumor data and, (iv) discovered ligand-receptor interactions as potential lead targets for personalized drug treatments. Our work establishes a clear path for incorporating spatial-omics in clinical settings to facilitate treatment personalization.