November 2018 Meeting Announcement, Delaware Valley Mass Spectrometry Discussion Group
- Topic: " Identifying sex differences in colon cancer metabolism
- Speaker:Caroline Johnson, Yale University
- Date: Monday, November 12, 2018. 6:00 PM
- Please RSVP to email@example.com by Thursday November 8.
- Time: Social Hour: 6:00 PM.
Talk: 7:00 PM.
- Place: Department of Chemistry, Villanova University (Mendel 213)
- Abstract: Colon cancer is the second most common cancer to affect women worldwide. While women have a 30-40% lower incidence of colon cancer than men, they have a higher likelihood of cancer presentation on the right-side of the colon. This is of concern because patients with right-sided colon cancer have poorer clinical outcomes than those with left-sided colon cancers. The reasons for this difference in outcome are not known, however, it has been proposed that female sex hormones influence colonic metabolism and affect tumor growth in this region of the colon. We have examined the metabolic differences between 210 colon tumor tissues from men and women with left and right-sided colon cancer using untargeted liquid chromatography mass spectrometry-based metabolomics. Using pathway analysis tools, we show region-specific and sex-specific differences in metabolites that may influence tumor growth in women with colon cancer.
- Bio: Dr. Johnson obtained her PhD in Analytical Chemistry from Imperial College London in 2009 and studied under the direction of Prof. Jeremy K. Nicholson. Since then she has held postdoctoral and staff appointments at the National Cancer Institute and The Scripps Research Institute where she developed mass spectrometry-based metabolomics methods to understand the metabolic reprogramming that takes place in cancer. Dr. Johnson began a faculty appointment at Yale School of Public Health in July 2016 and her primary research focus is to understand how sex hormones influence metabolism in healthy and diseased individuals. Her lab is also developing methods to carry out population-level metabolomics analyses and systems-level data integration.
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