Spatial Clonal Heterogeneity in Glioblastoma Glioblastoma (GBM) is the most common malignant primary brain tumor in adults characterized by an extensive intratumor heterogeneity. Intratumor heterogeneity is driven by somatic alterations. Tumor growth is carried out by distinct cell populations called clones and subclones, which differ in their evolutionary development through genetic mutations within their microenvironment.
Somatic genetic alterations can be broadly classified into two categories: Small Somatic Mutations (SSMs) and Copy Number Alterations (CNAs), which emerge during tumor evolution and may interact with each other.
Multiregional bulk whole-exome-sequencing data of GBM tumor samples represent a mixture of cells, for which the number of distinct cell populations (clones and subclones) and their relative proportions are unknown. In this thesis, we will apply computational methods for tumor phylogenies using variant allele frequency estimates considering both somatic single-nucleotide variants and copy number variants to get more insights about the spatial tumor heterogeneity in GBM. This information can lead to valuable insights into the dynamics of tumor evolution and help guide the development of personalized treatment strategies for GBM patients.