Northwestern University

Apr
17
Tue 10:00 AM

Joint Seminar - Zhaoming Wang, PhD

When: Tuesday, April 17, 2018
10:00 AM - 12:00 PM  

Where: 680 N. Lake Shore Drive, Suite 1400, Stamler Conference Room, Chicago, IL 60611 map it

Audience: Faculty/Staff - Student - Post Docs/Docs - Graduate Students

Contact: Andrius Aukstuolis  

Group: Department of Preventive Medicine

Category: Lectures & Meetings

Description:

The Department of Preventive Medicine Presents: A Joint Seminar of Biostatistics, Cancer Epidemiology, and the Center for Data Science and Informatics

Investigation of Germline Cancer Susceptibility using SNP Arrays and Next Generation Sequencing

Cancer Genome-Wide Association Studies (GWAS) has been tremendously successful for the past decade in discovering hundreds of genetic loci conferring risks to the different cancer sites including prostate, breast, lung, ovary, colon, pancreas et al. Although the clinical utility of applying GWAS findings in population risk screening is still questionable, novel biological mechanisms in cancer etiology started to be revealed. Cancer GWAS as an efficient approach has also evolved in the following aspects: 1) array improvement including SNP density and SNP content; 2) even larger sample size; and 3) more advanced statistics methods. I will review these with concrete examples from my own research experience. With the rapidly dropping cost of next-generation sequencing technologies, sequencing-based association studies will inevitably replace the genotyping array-based GWAS. Whole-genome sequencing (WGS) allows for exploitation of the full spectrum of genetic variations, including both common and rare variants; both genic and inter-genic. WGS studies may therefore increase the power of genetic association studies and directly interrogate functional variants. In the end, I will present some latest results in identifying rare pathogenic or likely pathogenic mutations in cancer predisposition genes and show their contributions independent of treatment exposures to the risk of developing subsequent neoplasms among survivors of childhood cancer using WGS data.

Presenter Bio:

Zhaoming Wang, Ph.D., is a bioinformatics expert in analyzing high throughput genomics data, especially in the field of cancer genome-association association studies (GWAS). He currently works as a bioinformatics scientist in the Department of Computational Biology at St. Jude Children’s Research Hospital where he manages both operational and scientific aspects of the genomics component of St. Jude Lifetime Cohort (SJLIFE) study by performing comprehensive and systematic analyses of whole-genome sequencing (WGS) and whole-exome sequencing (WES) data with the primary goal of identifying genetic modifiers of risk for the development of subsequent neoplasms or other sequelae among survivors of childhood cancer. Before joining St. Jude, he led cancer GWAS analyses in the Division of Cancer Genetics and Epidemiology (DCEG) at the National Cancer Institute (NCI) from 2005 to 2015 where he participated in many high profile projects including Cancer Genetic Markers of Susceptibility (CGEMS), an NCI cancer GWAS initiative in searching for genetic loci conferring risks to prostate and/or breast cancers; contributed to the development of a software package called genotype library utility (GLU), and implemented an efficient pipeline to process SNP data with more than 120,000 individuals scanned on different arrays at DCEG/NCI. As a bioinformatics expert, he joined the world leaders in the field of cancer epidemiology and genetics and played a major role in the OncoArray design for the GAME-ON international consortium to study the etiology for breast, prostate, lung, colon and ovary cancers in 2013. Since 2007, he has been an author on nearly 150 publications including prestigious journals like Nature and Nature Genetics, with ~30 first/co-first authors, multiple corresponding authors, invited Commentary and Research highlights.

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