yang4414

Prostate cancer (PCa) is the second leading cause of cancer-related death in American men. It is a clinically heterogeneous disease and develops in the background of diverse genetic and epigenetic changes. Understanding the coding and non-coding sequence variations of PCa cells at various stages of the disease development will be critical for the discovery of novel diagnostic biomarkers, prognostic biomarkers, and therapeutic targets. Next generation sequencing (NGS) has led to significant advances in our understanding of the mutational landscape for both primary and metastatic PCa as well as coming with major computational and analytic bottlenecks. In addition, the analysis of somatic mutations in PCa has focused almost entirely on the protein-coding regions but rarely in non-coding regulatory regions. However, projects such as ENCODE and Epigenome Roadmap are elucidating the functional elements encoded by the roughly 80% of the genome that is non-coding, including promoter and enhancer regions, and are providing an important opportunity to study somatic mutations outside of the well-studied protein-coding regions.

This project seeks to develop novel computational tools for detecting functional and clinically relevant insertion and deletion (indel) mutations in the heterogeneous PCa genome to fully harness the power of NGS and to facilitate advances toward personalized medicine. The specific aims are to develop novel computational tools for sensitive somatic indel detection, and apply those tools to large-scale experimental data in PCa and distribute the tools through an open source. The long-term goal is to develop algorithms and prototypes that are usable in clinical settings for personalized diagnosis and treatment.