A Multiscale Topological Framework for Phenotypic Profiling of the Oropharyngeal Carcinoma Microenvironment
Abstract
Purpose
Standardizing the assessment of the Tumor Microenvironment (TME) is critical for personalizing therapy in Head and Neck Squamous Cell Carcinoma (HNSCC). As part of a larger multiomics effort to discover multiscale biomarkers, we developed a mathematical framework to quantify the topological grammar of three distinctive TME habitats (immune, tumor, and stroma) and identify the architectural constraints that define the HNSCC phenotypic profile.
Methods
We integrated CD45+ and PanCK+ spatial distributions to construct global cellular graphs across a cohort of HNSCC patients. The Hausdorff distance (dH) was employed to measure topological similarity between habitats, identifying which architectural rules are conserved or decoupled. The sensitivity and directionality of these shifts were further validated using Mann-Whitney U tests and Cliff’s Delta effect size analysis, providing a non-parametric and multi-scale description of tissue organization.
Results
Analysis of the oropharyngeal carcinoma (OPC) microenvironment demonstrated significant architectural divergence. Clustering deviation and correlation variance (dH > 0.93) were the primary axes of structural decoupling, particularly at the immune-stroma interface. Conversely, central node dominance (dH < 0.2) was globally conserved across habitats, reflecting tissue characteristics that remain invariant despite metabolic or phenotypic heterogeneity. Cliff’s Delta values characterized the tumor parenchyma as exhibiting a state of topological dominance, with significant increases in high betweenness (delta = 0.79) and node dominance (delta = 0.46) relative to the stroma.
Conclusion
These findings suggest the Hausdorff metric can operate as a robust, observer-independent metric for characterizing the architectural landscape of the HNSCC tumor microenvironment. By identifying structural divergence or invariance in tissue organization, this framework can provide a quantitative bridge between mesoscale pathomics and macro-scale radiomics - offering a rigorous methodology for the discovery of structural biomarkers that may identify patients at risk of treatment failure. Ultimately, this topological approach supports the transition toward more precise, spatially-informed therapeutic strategies in HNSCC.