Dr. Laura Elnitski received her Ph.D. from The Pennsylvania State University in the area of Biochemistry and Molecular Biology. She later carried out her post-doctoral research at The Pennsylvania State University in the area of Computational Biology, where she received a Ruth L. Kirschstein National Research Service Award from the NIH.
Currently she serves as a Tenured Principal Investigator at the National Human Genome Research Institute at the National Institutes of Health, Bethesda, MD, USA. The recipient of the Genome Technology International Young Investigator Award in 2009, and the NHGRI Annual Mentoring Award in 2013 and the National Institutes of Health, Ruth L. Kirschstein Mentoring Award in 2014. Dr. Elnitski is funded through the National Human Genome Research Institute, Division of Intramural Research program. She serves on the Genomics Computational Biology and Technology (GCAT) Scientific Grant Review Panel, as well as NCI and NHGRI special subject review panels, and is a co-PI on a grant to study the Mapping Genetic Variation to Functional Changes in Mental Disorders. Her research involves the study of epigenomes, with a focus on computational methods to identify tumor subclasses by their DNA methylation landscapes. Her research accomplishments include the identification of the first candidate pan-cancer biomarker for use in cancer diagnostics, such as blood-based, liquid biopsies.
Title: Assessing ZNF154 hypermethylation from circulating tumor DNA in pan-cancer diagnostics
Aberrant DNA methylation in cancer represents a potential biomarker for screening and diagnostics. We identified hypermethylation at the ZNF154 CpG island in 15 solid epithelial tumor types from 13 different organs. We further assessed the magnitude and pattern of differential methylation across colon, lung, breast, stomach, and endometrial tumors using next generation bisulfite amplicon sequencing. Our findings strongly support this epigenetic signature as a relevant biomarker for circulating tumor DNA. Analysis of patient plasma samples, sensitivity of the assay, and comparison to other methods will be addressed.