Statistical analysis of genetic and epigenetic features in cancer cells

Cancer is one of the leading causes of death in almost every country and, in 2020, 19.3 million new cases and 10 million cancer deaths in the world have been estimated by WHO. The onset of a tumor is often accompanied with a set of genetic and epigenetic alterations, whose understanding can have both diagnostic role and prognostic power for targeted treatments. The spread of NGS platforms, which allow to sequence an entire human genome in a short time and relatively low cost, and the use of statistical methods that help in dealing with such huge amount of data and in finding hidden relationships, have a crucial role in the development of the precision medicine. The present thesis work consists in two projects. The first one is a study of point mutations and methylation of a cohort of patients diagnosed with Glioblastoma (GBM), involving both Illumina sequencing-by-synthesis platform and Oxford Nanopore Technologies. The second one is an application of Dirichlet Process, a statistical learning method, to a set of Multiple Myeloma (MM) patients characterized by Copy Number Variant (CNV) measures. The study of GBM patients resulted in a characterization of mutated targeted genes and methylated regions of MGMT, which is involved in the cancer evolution. Moreover, this project confirmed that results from ILM data and ONT do agree, giving the opportunity to use ONT for long read sequencing. This approach will reduce misalignment issues when repeats and pseudogenes are present and allows for the identification of point variants far from each other in the same chromosome. In the second project, the use of two Hierarchical Dirichlet Clustering approaches allowed to identify groups of MM patients with similar CNV evolution between the diagnosis and the post-treatment relapse. The results confirmed the high CNV variability of MM and show that its progression cannot be simply explained by means of clinical parameters about the therapy carried out and patient's response.