Upcoming Presentation at University of Windsor, Ontario, Canada.

Peter Rogan will present:

“Genomic analysis of metastasis and tumor chemotherapy response based on information theory and machine learning”

Department of Computer Science

University of Windsor

Date:  Friday, November 13th, 2015
Time: 11:00 am
Location: Chrysler Hall – G100

 Abstract: The integrated analyses of cancer phenotypes with complex genomic datasets has resulted in many new insights into diagnosis and prognosis. However, there is no single correct way to analyze these data, and the data themselves can vary significantly  in content and interpretation between different studies of the same tumor type.   We have used mutation, expression and copy number data to study breast cancer genes and genomes (hereditary and somatic). A major challenge in inherited breast cancer is the missing heritability; pathogenic mutations are not detected despite strong family historie. Our approach has been to prioritize functionally significant variants using information theory-based models of DNA and RNA binding protein binding sites.  These same approaches – when applied to breast tumour exome sequences – have revealed numerous missed mRNA splicing mutations, and identified mutated pathways, validated by RNA sequencing, that are overrepresented in these tumour genomes. Application of biochemically-inspired machine learning to these integrated genomic data from cell lines produces gene signatures that robustly predict therapeutic response that we have validated with patient tumor data. Machine learning is a promising general approach that can be used for other drugs and tumor types with good recall.

Posted in News.