Our lab seeks to understand the molecular causes of cancer in order to develop better therapies and improve patient outcome. Through a combination of computational and experimental methods, we study how genes are regulated in cancer, and how changes in gene regulation and cell signaling networks drive tumor progression.
G-protein coupled receptors as cancer drug targets
GPCRs transduce extracellular signals from a variety of ligands through the plasma membrane, resulting in the modulation of intracellular signaling pathways. This is accomplished in large measure by the activation of heterotrimeric G-proteins and downstream second messengers. Composed of over 900 members in humans, GPCRs are seven-transmembrane proteins that regulate many physiological processes including vision, olfaction, taste, behavior and autonomic nervous system transmission. This wide array of functions has resulted in the extensive utilization of GPCR targeted therapeutics, accounting for 30-50% of all currently used drugs. The wide use of GPCR drugs can also be attributed to GPCR localization on the cell surface, abrogating the requirement for a drug to be cell permeable, as well as the ability of GPCRs to bind a variety of ligands, including antibodies, peptides and small molecules. Furthermore, GPCR signaling can be tightly regulated through the utilization of agonists, antagonists and inverse agonists. However, drugs targeting GPCRs are rarely utilized in cancer treatment, despite evidence that GPCRs mediate many aspects of tumorigenesis, including cell proliferation, invasion, immune cell recruitment and secondary niche generation. Genomic analyses have uncovered GPCR mutations, copy number alterations and gene expression and methylation changes in a wide variety of cancers. We hypothesize that determining the biological implication of these genomic alterations will allow utilization of GPCR targeted therapeutics in those patients with GPCR-driven tumors. Our lab uses computational methods to select high priority GPCR targets, followed by experimental validation and therapeutic evaluation in three-dimensional cell culture and mouse models.
Noncoding mutations as cancer drivers
Large-scale exome sequencing efforts have revealed genes and pathways important for cancer progression. However, the exome comprises less than 2% of the human genome and whole-genome sequencing (WGS) analyses have revealed tumors often carry thousands of somatic mutations per genome, the vast majority of which are located in noncoding regions and are completely uncharacterized. To detect somatic noncoding mutations (NCMs) in pancreatic cancer (PDA), I co-developed a computational pipeline to analyze WGS data of 308 PDA tumors. To discriminate amongst the thousands of identified NCMs, we developed GECCO (Genomic Enrichment Computational Clustering Operation) to identify candidate NCMs that drive differential gene expression. Using GECCO, we identified novel recurrent mutations and interrogated expression data from matched tumors to find several variants associated with changes in mRNA levels. We found significant differential expression of 16 genes associated with NCMs, and reveal two (PTPRN2, SLC12A8) with previously unidentified clinical relevance in PDA. Pathway analysis of the genes associated with recurrent NCMs identified known and novel PDA pathways. Furthermore, we found enrichment for mutations in specific regulatory regions, suggesting that NCMs may be acted upon by selection during tumor formation. Our analysis provides a model for tumor evolution via the formation and selection for alterations in noncoding regulatory elements of specific genes as a means of control over specific biological pathways. Our lab is extending these efforts to focus on a broad array of regulatory elements and cancer types through a combination of computational and experimental methods.