Single Cell Molecular Characterization and Computational Drug Discovery for Fertility-Sparing Treatment of Uterine Fibroids

ABSTRACT Uterine leiomyomas, better known as fibroid tumors, are clinically apparent in nearly 25% of women by age 45, and they cause major morbidity among American women. More than 200,000 surgeries are performed each year to either remove the leiomyomatous tumors or the entire uterus. There are limited medical treatments, largely unchanged over decades. The development and availability of large-scale genomic, transcriptomic, and other molecular profiling technologies, in combination with the deployment of the network concept of drug targets and the power of phenotypic screening, provide an unprecedented opportunity to advance rational drug repurposing and data-driven development of drug combinations. The goal of the proposed project is to leverage and generate leiomyomas transcriptomics data combined with publicly available drug screening data and apply a computational drug-repurposing pipeline to identify single agent and combination therapies from existing drugs based on expression reversal perturbing molecular networks away from disease-associated cellular dysfunction, and validate select drugs in human cells in vitro and an animal model of leiomyomas. In Aim 1, we will perform single nuclei RNA sequencing on 50 cases and 50 controls to determine the transcriptomic signatures of cell types in fibroids and determine their associated pathways and biological processes with a focus on MED12 positive cases. In Aim 2 we will use transcriptomic-based computational drug-repurposing to identify potential new single agent and combination therapeutics based on expression reversal leveraging public transcriptomics data. Our hypothesis is that the inverse expression profiles between the drug repositioning candidates and the disease signatures will result in therapeutic predictions. In Aim 3, we will determine the capacity of compounds of interest (COIs) to inhibit inflammatory signaling responses in primary human immune and fibroid cells and test in a preclinical fibroids model. We hypothesize that the most promising COIs identified in silico (Aim 2) will have effects on phospho‑signaling, proliferation/apoptosis and we furthermore hypothesize that the COIs identified for the treatment of fibroids will reduce tumor volume, uterine/fibroid weight, histology (Masson’s trichrome). We anticipate this study will serve as the basis for studies on newly discovered novel targets and drug-repurposing as well as functional validation in tissue as well as testing in preclinical models, and if successful, clinical trials for leiomyomas. We hope that this novel approach will change the paradigm of “one size fits all” treatment for leiomyomas and expand therapeutic options to new therapies and established therapies repurposed to improve the lives of millions of affected women and expand the research pipeline in this space.