MIG Special Seminar - Nicholas Banovich - Using functional genomics to uncover novel biology in complex disease
Using functional genomics to uncover novel biology in complex disease
This talk will cover ongoing work on two major disease areas of interest in the Banovich Lab, idiopathic pulmonary fibrosis and multiple myeloma.
Idiopathic pulmonary fibrosis: Idiopathic pulmonary fibrosis (IPF) is the most common and severe form of interstitial lung disease. IPF occurs in middle-aged and older adults and affects over 50,000 Americans each year. Most IPF patients die from respiratory failure within five years of diagnosis. The current therapies target downstream disease mechanisms, and while they modestly slow the decline in lung function, they have not been shown to improve survival or quality of life for IPF patients. There is considerable heterogeneity of clinical outcomes among IPF patients, and we believe this heterogeneity is due to distinct mechanisms and programs involved in disease initiation that culminate in a common a pathology of end-stage lung fibrosis. As such, the development of transformative treatments hinges on our ability to better understand and target “upstream” disease mechanisms. However, progress to this end has been held back by the limited study of the cell types and molecular changes initiating IPF pathogenesis. Here we perform single cell RNA-sequencing (scRNA-seq) on explant lungs from patients with IPF and healthy controls. This work has uncovered a number of cell-type-specific signals associated with disease initiation and progression as well as a pathogenic epithelial cell state only associated with diseased lungs.
Multiple Myeloma: Multiple myeloma (MM) is the second most common hematological cancer, accounting for 2% of all cancer deaths. MM is associated with a poor prognosis, with a 5-year overall survival of 50.7%. While the introduction of new therapies in the last decade has nearly doubled the survival rate, most patients still experience a relapse. Genome-wide association studies have identified germline variants associated with MM risk, indicating inherited genetic susceptibility. Furthermore, MM exhibits a disparity in occurrence and mortality between the sexes and ethnicities, men and African Americans being in at a higher risk than women or those of European ancestry. To better understand the genetic and biological basis of MM predisposition, we utilize a systems genomics approach to examine non-coding inherited and somatic genetic effects on gene expression (eQTLs) and MM outcome. Using over 600 patients from the Multiple Myeloma Research Foundation CoMMpass study, we identified thousands of genes with at least one cis-acting eQTL. Furthermore, we discovered a number of regulatory variants with differential effects on tumor gene expression between the sexes and ethnicities, as well as eQTLs overlapping MM GWAS risk loci, providing regulatory mechanisms for these loci. Finally, we discovered eQTLs that modulate overall survival in patients with MM.
Dr Nicholas Banovich, Assistant Professor
Dr Nicholas Banovich
Translational Genomics Research Institute
Dr. Nicholas Banovich is an Assistant Professor in the Integrated Cancer Genomics Division at the Translational Genomics Research Institute (TGen). He received his B.S. in Anthropology from Arizona State University and his PhD in Human Genetics from the University of Chicago. Dr. Banovich joined TGen as a senior postdoctoral researcher before transitioning into a professorial position. The Banovich lab is focused on understanding how genetic variation (somatic or germline) within the noncoding portion of the genome alters gene expression levels and contributes to complex disease. While many noncoding variants have been associated with complex disease, understanding how these variants modulate risk remains elusive. This is particularly true in cancer, where the functional implication of noncoding variation remains vastly understudied. Our lab employs functional genomics, computational biology, population genetics, and molecular biology to understand how regulatory changes affect patient outcomes.