Timing Chromosomal Abnormalities Using Mutation Data

• Activity Number: 574
• Type: Invited
• Date/Time: Wednesday, August 7, 2013 : 2:00 PM to 3:50 PM
• Sponsor: WNAR
• Author(s): Elizabeth Purdom*+
• Companies: UC, Berkeley
• Keywords: Sequencing ; Cancer ; Genomics

Abstract

Tumors accumulate large numbers of mutations and other chromosomal abnormalities due to the breakdown in genomic repair mechanisms that is a hallmark of tumors. However, not all of these abnormalities are believed to be crucial for tumor growth and progression. One important indicator of the importance of the abnormality is the order in which it occurred, relative to other abnormalities. Early events may be critical and possibly targets for drug treatment or early diagnosis. Outside of animal models, we generally will not have tumors from multiple time points in the progression of the tumor, and cannot directly observe the temporal ordering of genomic abnormalities.

However, the distribution of allele frequencies within regions with copy number aberrations provides information about when the chromosomal abnormality occurred. Using sequencing data, we develop a probabilistic model for the observed allele frequency of a mutation that allows us to order abnormalities within a tumor. Our method gives a novel insight into the biology of tumor progression and a quantitative measure to compare across samples for highlighting driver mutations and events.