Waiting Time Models for Mutual Exclusivity and Order Constraints in Cancer Progression

In recent years, high-throughput sequencing technologies have generated an unprecedented amount of genomic cancer data, opening the way to a more profound understanding of tumorigenesis. In this regard, two fundamental questions have emerged: 1) which alterations drive tumor progression? and 2) what are the evolutionary constraints on the order in which these alterations occur? Answering these questions is crucial for targeted therapeutic decisions, which are often based on the identification of early genetic events. During this talk, I will present two models, TiMEx: a waiting time model for mutually exclusive cancer alterations, and pathTiMEx: a waiting time model for the joint inference of mutually exclusive cancer pathways and their dependencies in tumor progression. We regard tumorigenesis as a dynamic process, and base our model on the temporal interplay between the waiting times to alterations, characteristic for every gene and alteration type, and the observation time. We assume that, in tumor development, alterations can either occur independently, or depend on eachother by being part of the same pathway or by following particular progression paths. By inferring these two types of potential dependencies simultaneously, we jointly addresses the two fundamental questions of identifying important cancer genes and progression, on the basis of the same cancer dataset. On biological cancer datasets, TiMEx identifies gene groups with stronger functional biological relevance than previous methods, while also proposing many new candidates for biological validation. Additionally, the results of pathTiMEx on tumor progression are highly consistent with the literature in the case of colorectal cancer and glioblastoma.

Bio

Simona Constantinescu is a graduate student at ETH Zurich, in Switzerland, in Niko Beerenwinkel's group. Her main research interest is the design of models and algorithms with application to cancer genomics data. Particularly, she is working on projects related to inferring the temporal progression and mutual exclusivity in cancer, evolutionary dynamics of cancer, and toxicogenomics. Simona obtained a Master's Degree in Computational Biology and Bioinformatics (Department of Computer Science) from ETH Zurich, and degrees in Mathematics and Economic Informatics from the University of Bucharest. During her Master studies, she was awarded an ETH Excellence Scholarship.