Common Fund Gene Utility Compendium: A Systems Biology Resource to Explore Tissue-Specific Functional Genes and Druggable Genomes

PROJECT SUMMARY Tissue-specific genes are underutilized as disease targets. Tissue-specific genes show narrow expression, play key roles in maintaining tissue homeostasis and are thought to be good drug candidates. Thus, targeting of dysfunctional tissue-specific genes can provide a safer therapeutic approach due to the reduced risk of side

effects. However, identifying which tissue-specific genes are critical in disease is a bottleneck in drug discovery. We hypothesize that key tissue-specific genes have the ability to spread perturbations in a protein-protein interactome and can be identified by their context specific functionality. This approach offers a paradigm shift

from conventional analyses that uniquely focus on one-gene expression levels. We recently proposed Gene Utility Model (GUM) which hypothesizes that it is how a gene is utilized in protein-protein interaction (PPI) network dictates its importance in disease development. We will use information flow of a gene within a PPI

network to represent the gene utility in a given biological state. Under this scenario, genes with high information flows (i.e., high gene utilities) in a disease state, instead of gene expression level, are deemed to play more important roles in disease development. Thus, this application seeks to increase the clinical utility of NIH

Common Funds datasets by employing state-of-the-art systems biology approaches to precisely and reliably identifying tissue-specific druggable functional genes (TS-DFGs). We will construct a prototype for Common Fund Gene Utility Compendium by leveraging four NIH Common Fund datasets: Genotype Tissue Expression

(GTEx), Library of Integrated Network-based Cellular Signatures (LINCS), Illuminating the Druggable Genome (IDG), and 4D Nucleome (4DN). We will focus on three disease types, liver cancer, nonalcoholic fatty liver disease (NAFLD), and Alzheimer's disease (AD) as proof-of-concept studies. In Aim 1, we will uncover highly

utilized tissue-specific genes across multiple normal tissue types and three selected disease types. We will then construct utility karyotype to indicate chromosomal regions enriched with highly utilized genes. In Aim 2, we will employ selectivity, controllability, and suitability as criteria to score druggability for TS-DFG candidates with

respect to liver cancer, NAFLD, and AD. Druggable utility networks (DUNs) with respect to each disease type will be constructed to assess the distribution of highly score TS-DFGs in a PPI network and signaling pathways. The constructed prototype of the Common Fund Gene Utility Compendium will promote innovative research to

enhance the usage and provide added clinical value for the NIH Common Fund datasets by offering a new paradigm shift for target and drug discovery. Our long-term goal is to enlarge this compendium by including more diseases across different tissue types to facilitate integrative pan-tissue analyses and drive drug

discovery.