Ovarian cancer remains a disease with high mortality due to late-stage diagnoses and tumor recurrence. Understanding how ovarian tumors begin and come back (recur) would provide new ways to develop early detection methods and targets of recurrent disease. One hypothesis as to how ovarian tumors are initiated and recur is through a rare population of cells called Ovarian Cancer Stem-like Cells (OCSCs). OCSCs have similar characteristics as normal stem cells that can give rise to many kinds of cells in a tissue, but instead possess the ability to produce the cells that comprise ovarian tumors. Further, these cells have been shown to be capable of tumor initiation and possess characteristics that allow them a measure of innate therapy resistance, providing a possible mechanism for tumor re-initiation/recurrence. In this project, we propose to profile individual OCSCs using new technologies we have developed in our group to provide a rich picture of these cells at each step in the process of differentiating into the various types of cells in a tumor in a process known as lineage tracing. The first innovative way we are tackling this problem is by giving each individual OCSC a unique cell barcode. When an OCSC divides into two cells, we will be able to keep track of both the new cell and which cell it came from by sequencing the DNA and RNA. We have developed new sequencing approaches that profile patterns of marks on the DNA (methylation) and how they can regulate which genes are turned on and off (RNA) in the cell. How and why these patterns change during OCSC differentiation will provide new information that we can use to target the tumor initiating cells and potentially lowering disease recurrence, hopefully leading to better patient outcomes.
This grant was made possible in part by a generous donation by The Mike & Patti Hennessy Foundation
Dr. Benjamin Johnson is currently a bioinformatics postdoctoral fellow in laboratory of Dr. Hui Shen in the Department of Epigenetics at the Van Andel Institute (VAI) in Grand Rapids, Michigan. Dr. Johnson received his undergraduate degree in Biology from Calvin University. During his undergraduate studies, he worked as a research and teaching assistant as part of the HHMI SEA-PHAGES program, characterizing mycobacteriophage diversity and evolution. A primary thrust of this program was to begin training undergraduates in both experimental and computational techniques, which ultimately led to Dr. Johnson receiving an NSF scientific computing scholarship. He obtained his Ph.D. from Michigan State University, under the supervision of Dr. Robert Abramovitch, investigating Mycobacterium tuberculosis (Mtb) pH-dependent adaptations. This work resulted in several publications and a U.S. Patent for identification of a small molecule that disrupts Mtb adaptation to acidic pH in vivo, reducing pathogen virulence. Following his doctoral degree, Dr. Johnson continued to hone his computational skills by joining the Bioinformatics and Biostatistics Core group at VAI. It was during this time that he discovered he wanted to focus his postdoctoral work on the interplay of epigenetics and transcription driving ovarian cancer, leading to him joining the laboratory of Dr. Hui Shen at VAI. His current research focuses on the discovery and characterization of the molecular underpinnings that define the landscape of cellular states and fates in ovarian cancer.