Integrated Meta-Analysis of Prostate Cancer Genomes
Abstract
Hypothesis. We hypothesize that an integrated database of prostate cancer genomic profiles will improve our understanding of the molecular and evolutionary determinants of lethal disease. Study Design: Aim #1. There are several dozen prostate cancer genome sequencing studies, comprising almost 10,000 patient specimens. These vary in the DNA sequencing technology and in the portion of the genome analyzed. Most have targeted sequencing but by volume most data is from whole-genome sequencing. We will systematically re-analyze all data through consistent state-of-the-art computational pipelines and aggregate the results into a single community available database for easy retrieval and analysis for downstream studies. Study Design: Aim #2. We have DNA whole-genome sequencing data from patients across all prostate cancer disease states. We will apply cutting-edge subclonal reconstruction techniques to identify the specific evolutionary features of each state and use evolutionary timing analysis to pinpoint when specific mutations and mutational processes occur during tumor evolution. Study Design: Aim #3. Using our aggregated meta-database, we will rigorously identify somatic mutational driver events that occur more frequently than expected by chance. We will search for these at the level of copy number variants, coding and non-coding point variants, genomic rearrangements, and mitochondrial variants. We will then create multivariate models that relate these drivers to clinical features to characterize their timing, and to transcriptional data to understand their phenotypic consequences.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 2023
- Accession Number
- AD1206971
Entities
People
- Paul C. Boutros
Organizations
- University of California, Los Angeles