Discovery of Tissue Biomarkers using Formal Methods

(CSE Distinguished Lecture Series)

Debashis Sahoo

Speaker: Debashis Sahoo, Professor, UC San Diego Pediatrics and CSE
Date: Monday, December 11, 2017
Time: 11am
Location: Room 1202, CSE Building

Abstract: All normal cancer and other diseased tissues contain a diversity of different cell types with distinct morphological features. The identification and characterization of these different cell types within normal and diseased tissue are not only critical for the understanding of underlying biology but also in developing more effective therapeutic strategies. Previous attempts to identify markers for cells at hierarchical stages of tissue differentiation involved either 1) large screening studies using antibody libraries or gene expression arrays, or 2) focused trials of established markers identified in other normal and diseased tissues.  Unfortunately, these approaches are insufficient to trace complex cellular differentiation stages, and thus most often fails. Therefore a systematic approach to identify cells within tissue differentiation hierarchies is required.

We developed systematic computational approaches based on formal methods to identify markers of stem and progenitor cells by analyzing publicly available, high-throughput gene expression datasets consisting of more than 2 billion measurement points. We developed a set of tools - StepMiner, BooleanNet (a network of Boolean implications), MiDReG (Mining Developmentally Regulated Genes) that uses Boolean implications to predict genes in developmental pathways, and HEGEMON (Hierarchical Exploration of Gene Expression Microarray Online) to identify genes expressed in the stem and progenitor cells in both normal and malignant tissue development. We demonstrated that coordinated use of these tools could predict genes involved in developmental stages in human normal and cancer tissues. We will use an example from human colon tissue to show the power of this computational approach. This approach identifies biomarkers with diagnostic and prognostic value for immediate translation into clinical applications.

Bio:  Debashis Sahoo, PhD is an assistant professor at the Department of Pediatrics and Department of Computer Science and Engineering at University of California San Diego. Dr. Sahoo received his MS and PhD in Electrical Engineering at Stanford University, and BTech in Computer Science and Engineering at IIT-Kharagpur. Dr. Sahoo has worked in the area of formal verification of hardware design early in his career. Later he has successfully applied the concepts from formal verification to discover prognostic and predictive biomarkers in human bladder and colon cancer. His active research areas include computational biology, systems biology, bioinformatics, cancer biology, immunology, genetics and stem cell biology. He is currently directing a research group that develops and validates formal models of complex biological systems.