Abstract A04: Tumor development trajectories for exploring differences between cancer subtypes

Abstract

Abstract We have employed PhylogicNDT, our computational method for timing somatic events and subclonal architecture reconstruction, to explore the association of tumor development trajectory (from normal cell to malignant state) with cancer subtype and genetic landscape. Previous attempts to understand the order of somatic events that lead to the formation of cancers are mostly based on studies of premalignant samples, which are often hard or impossible to obtain due to small size or inaccessible location. Our approach allows us to use information from whole-exome and whole-genome data to computationally reconstruct the order of events preceding malignant transformation of the tissue. We show that this approach yields accurate reconstruction of premalignant events in lung, colorectal, and head and neck cancers based on previous exploration of premalignant lesions. We explored the association between the developmental trajectories, treatment outcome, and survival in several cancer types. PhylogicNDT can be used to infer the order of clonal driver events (including in precancerous stages), subclonal populations of cells and their phylogenetic relationships, and dynamics of cell populations. This methodology will enable a systematic study of tumor initiation and progression across cancer types and therapies. Citation Format: Ignaty Leshchiner, Daniel Rosebrock, Oliver Spiro, Edmund Mroz, Dimitri Livitz, James W. Rocco, Gad Getz. Tumor development trajectories for exploring differences between cancer subtypes [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Optimizing Survival and Quality of Life through Basic, Clinical, and Translational Research; 2019 Apr 29-30; Austin, TX. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_2):Abstract nr A04.