Cancer progression can be understood as the disruption of tissue homeostasis by tumor cells that co-opt their microenvironment\cite{BasantaAnderson2017}. In multiple myeloma (MM), this disruption unfolds within the bone marrow, where stromal cells, osteoclasts, osteoblasts, and immune populations form spatially heterogeneous niches. We have previously shown that integrated computational models...
The Gleason score (GS) is a key predictor of prostate cancer (PCa) aggressiveness and survival, yet treatment decisions rely on biopsies that incompletely sample highly heterogeneous tumors. As a result, clinically relevant spatial variations in tumor aggressiveness may remain undetected. To address this clinically unresolved issue, I present a personalized modelling framework for pointwise...
Drug resistance is an ongoing problem for maintaining a treatment response in advanced cancers, which are often more heterogeneous and evolvable. Evolvability may be beneficial if lesions can easily respond to large shifts in the microenvironment by modifying their traits to survive, like how metastases can survive a new environment and even thrive despite treatment applications. However,...
Spatial transcriptomics has revolutionised our ability to measure gene expression while preserving tissue architecture. Yet extracting meaningful patterns from the complex interaction of spatial organisation and molecular profiles remains challenging, particularly in the heterogeneous tumour microenvironment (TME). Here we apply Multi-Parameter Persistent Homology (MPH), a topological data...
Tumour cell plasticity and intratumour heterogeneity are key determinants of cancer progression and treatment failure \cite{cordani_2024,seferbekova_2023}. In particular, spatial heterogeneity in the tumor microenvironment (hypoxia, acidity, nutrient limitation, immune/stromal organisation, and mechanical constraints) shapes phenotypic states and their transitions \cite{perez-gonzalez_2023}....
