Unveiling insights: Leveraging single-cell transcriptomics and epigenomics for biomarker discovery
Single-cell genomics has facilitated the understanding of mechanisms involved in various biological processes such as tumorigenesis, cell development, and differentiation. This webinar will show how different single-cell transcriptomics or epigenomics methodologies can be leveraged to identify important biomarkers such as gene fusions, splicing isoforms, and cell type-specific histone modification patterns.
This webinar features presentations by Dr. Ilaria Iacobucci from St. Jude Children’s Hospital and Dr. Derek Janssens from Fred Hutch Cancer Center.
Topics covered
Dr. Ilaria Iacobucci, PhD, is a Principal Scientist in the Department of Pathology at St. Jude Children’s Research Hospital, Memphis. Her research focuses on the understanding of mechanisms underlying the pathogenesis of high-risk myeloid and lymphoid leukemia subtypes in both children and adults through the identification of novel genetic alterations with a diagnostic, prognostic and therapeutic relevance and the development of preclinical in-vitro and in-vivo models which faithfully recapitulate human leukemia. She has published ~150 peer-reviewed articles and contributed to the identification of multiple new genomic subtypes of acute lymphoblastic, erythroid and myeloid leukemia.
Dr. Derek Janssens PhD is a postdoctoral researcher in the lab of Dr. Steven Henikoff in the Basic Sciences Division of the Fred Hutchinson Cancer Center in Seattle. After completing his graduate thesis at the University of Michigan, Derek joined the Henikoff lab in 2017 and has been developing novel chromatin profiling tools to understand the epigenetic heterogeneity of cancer. The automated CUT&RUN and CUT&Tag platforms Derek developed are currently available as core services through the Fred Hutchinson Cancer Center. More recently, Derek has been optimizing CUT&Tag for single cell applications and finding creative ways to use the ICELL8 to increase the number of single cells profiled in each experiment, while minimizing the cost.
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