OCT 16, 2013 01:00 PM PDT

Investigating tissue specificity of cancer-causing germline mutations

  • Assistant Professor, Department of Systems & Computational Biology, Assistant Professor, Department of Epidemiology & Population Health, Albert Einstein College of Medicine
      Jessica Mar is an Assistant Professor at Albert Einstein College of Medicine in the Department of Systems and Computational Biology in the Bronx, New York. The focus of the Mar lab is to understand how variability in gene expression contributes to the regulation of cellular phenotypes. Around the topic of variability, her work involves applications in single cell genomics, stem cells, genetics and cancer biology. Jessica Mar received her Bachelor of Science degree in Mathematics at the University of Queensland in Brisbane, Australia and First Class Honors in Statistics in 2002. She got her PhD in Biostatistics from Harvard University in 2008. Previously she was a postdoctoral research fellow at the Dana-Farber Cancer Institute in Boston, and a visiting scientist at the European Bioinformatics Institute in the UK. Since July 2016, Dr. Mar holds a joint appointment with the Australian Institute for Bioengineering and Nanotechnology at the University of Queensland, Australia as a Group Leader.


    The remarkable diversity we see between different cell types in the human body is governed by the specificity attained through transcriptional and epigenetic regulatory programs. Cancer is a disease that targets specific tissues, and in the case of cancer-causing germline mutations, it is perplexing that primary tumors arise in a restricted subset of tissues only. Understanding why a mutation can be suppressed in one tissue but not others stands to unlock insights into tissue-specific transcriptional regulation and how these programs promote fragility or resistance of cancer-causing mutations. We have been studying cancer-causing germline mutations in the context of cell type-specific gene regulatory networks. Using a comprehensive tissue expression atlas from the FANTOM5 consortium, we have access to CAGE sequencing data that captures promoter usage and gene expression in over 1000 human samples, including primary cells, tissues and cell lines. Levering information from COSMIC, the Cancer Gene Census, and FANTOM5, two classes of genes that have tissues-specific, cancer-causing mutations have been identified (1) genes that are expressed in the cell type where the cancer occurs, (2) genes that are expressed ubiquitously across many different cell types. For this second class, we have begun comparing regulatory networks associated with these genes in susceptible versus resistant cell types to identify changes in network topology that may change a cell types oncogenic potential. Learning Objectives *To understand how normal human tissues use gene networks differently. *To appreciate that some genes with cancer-causing mutations are expressed in a wide range of tissues but tumors develop in only a restricted subset of those tissues.

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