2014 Poster Sessions : Genome Evolution during Progression to Breast Cancer

Student Name : Dorna Kashef-Haghighi
Advisor : Serafim Batzoglou
Research Areas: Artificial Intelligence
Cancer is a disease of the genome and is due to cycles of cell damage, resulting in an uncontrollable rate of cell growth. Invasive ductal carcinoma is the most common form of breast cancer and is the focus of many current cancer genome sequencing projects. In this project, we utilize archival material to study the earliest stages of cancer progression and elucidate their role in cancer evolution. We performed comparative whole genome analysis of early neoplasias, carcinomas, and matched normal tissue from six patients. We show that somatic SNVs can be used as cell lineage markers to build evolutionary trees that relate the tissue samples within each patient. These lineage trees can be used to infer the order, timing and rates of genomic events. In four out of six cases, an early neoplasia and the carcinoma share a mutated common ancestor with recurring aneuploidies, and in all six cases evolution accelerated in the carcinoma lineage. Transition spectra of somatic mutations suggests that accumulation of somatic mutations is a result of increased ancestral cell division rather than specific mutational mechanisms. Aneuploidies that occur in common ancestors of neoplastic and tumor cells are the earliest events that affect a large number of genes and may predispose breast tissue to eventual development of invasive carcinoma.

Dorna Kashef is a PhD student in the Computer Science Department at Stanford University and is advised by Professor Serafim Batzoglou. She received her B.Sc. with honors in Computer Science from McGill University. Dorna is the recipient of STMicroelectronics fellowship. Her research focuses on developing new computational tools to study the breast cancer genome.