Multiscale modeling of drug resistance in glioblastoma with gene mutations and angiogenesis

Abstract

Drug resistance is a prominent impediment to the efficacy of targeted therapies across various cancer types, including glioblastoma (GBM). However, comprehending the intricate intracellular and extracellular mechanisms underlying drug resistance remains elusive. Empirical investigations have elucidated that genetic aberrations, such as gene mutations, along with microenvironmental adaptation, notably angiogenesis, act as pivotal drivers of tumor progression and drug resistance. Nonetheless, mathematical models frequently compartmentalize these factors in isolation. In this study, we present a multiscale agent-based model of GBM, encompassing cellular dynamics, intricate signaling pathways, gene mutations, angiogenesis, and therapeutic interventions. This integrative framework facilitates an exploration of the interplay between genetic mutations and the vascular microenvironment in shaping the dynamic evolution of tumors during treatment with tyrosine kinase inhibitor. Our simulations unveil that mutations influencing the migration and proliferation of tumor cells expedite the emergence of phenotype heterogeneity, thereby exacerbating tumor invasion under both treated and untreated conditions. Moreover, angiogenesis proximate to the tumor fosters a protumoral milieu, augmenting mutation-induced drug resistance by increasing the survival rate of tumor cells. Collectively, our findings underscore the dual roles of intrinsic genetic mutations and extrinsic microenvironmental adaptations in steering tumor growth and drug resistance. Finally, we substantiate our model predictions concerning the impact of gene mutations and angiogenesis on the responsiveness of targeted therapies by integrating single-cell RNA-seq, spatial transcriptomics, bulk RNA-seq, and clinical data from GBM patients. The multidimensional approach enhances our understanding of the complexities governing drug resistance in glioma and offers insights into potential therapeutic strategies.

Keywords: Angiogenesis; Drug resistance; Genetic mutations; Multiscale modeling.