I work in The Laboratory of Translational RNA Biology, where I combine next-generation sequencing, machine learning, and gene editing technology to study the genetic nature of neuroendocrine tumors.
After completing my undergraduate degree in biochemistry, I began my Master's Degree at Queen's University in the Department of Pathology and Molecular Medicine, where I pursued my interests to combine computing and cell biology, and to study their applications in clinical science. I have since upgraded to the Doctoral Program, where I study under the supervision of Dr. Neil Renwick.
During my post-secondary education, I have had the opportunity to gain experience in a variety of clinical and laboratory settings, including SickKids hospital, the University of Toronto, the Banting and Best Diabetes Centre and the Rockefeller University, in addition to my primary research projects at Queen's.
My PhD project investigates the genetic nature of neuroendocrine tumors (NETs). Specifically, can microRNA (miRNA) profiling be used to classify and diagnose NETs? Furthermore, can these miRNA profiles explain the unique behaviour and morphology of NETs? I use next-generation (next-gen) sequencing, machine learning, and gene editing to discover novel biomarkers and oncogenes.
miRNA are extracted from blood, FFPE tissue blocks, and cell lines, and sequenced with an Illumina Hi-Seq next-gen sequencer. The miRNA are then annotated and compiled into profiles for each individual patient.
The miRNA profiles are analyzed with data mining and pattern recognition algorithms. These algorithms show the genetic relationships between subgroups of NETs. They also identify important features / genetic biomarkers to classify the NET subgroups and differentiate between cancerous and non-cancerous cells.
Gene editing techniques such as CRISPR-Cas9 and lentiviral transfection are used to overexpress and knock down important miRNA biomarkers in NETs to determine their biological role.