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PICB Seminar: Epigenetic Stochasticity in Normal Development and Cancer by Prof. Andrew P. Feinberg (March 29, 2017)

Speaker: Andrew P. Feinberg, MD, MPH
John Hopkins University
Bloomberg Distinguished Professor
Director, Center for Epigenetics
King Fahd Professor of Medicine, Biomedical Engineering, Mental Health, Oncology, Biostatistics, Molecular Biology & Genetics, and Psychiatry & Behavioral Sciences

Time: 10:00am, 29th March (Wednesday)

Place: Lecture Hall, SIBS Main Building, 320 Yueyang Road (岳阳路320号生理楼报告厅)

Host:Prof. Andrew E.Teschendorff, CAS-MPG Partner Institute for Computational Biology (PICB) 

Title:Epigenetic Stochasticity in Normal Development and Cancer


I have been pursuing an idea that natural selection will favor the emergence of genetic loci for epigenetic variation that can occur randomly or in response to environmental signals and affect phenotypes in which the environment changes unpredictably but often enough, and these epigenetically variable loci are critical to normal embryonic development and injury response. The idea is also relevant to cancer, in that mutations cause increased epigenetic stochasticity, which would allow rapid selection for tumor cell survival at the expense of the host. Several recent discoveries point to a genome-scale disruption of the epigenome that involves large blocks of DNA hypomethylation, mutations of epigenetic modifier genes and alterations of heterochromatin in cancer (including large organized chromatin lysine modifications (LOCKs) and lamin-associated domains (LADs)), all of which increase epigenetic and gene expression plasticity. We also find large-scale reprogramming of chromatin and DNA modifications during the natural evolution of distant metastasis, with dependence on the oxidative branch of the pentose phosphate pathway. Finally, we are developing a novel stochastic mathematical approach to understanding the nature of epigenetic information and its relationship to environmental exposure and biological function. This has led to several new measures, including normalized methylation entropy, which turns out to be surprisingly relevant to understanding some fundamental principles of physical biology. I will discuss these models in the context of stem cell differentiation, aging, and cancer.


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