Background: The clinical care of neglected diseases such as pulmonary hypertension (PH) has not yet benefited from large scale ?omics data analysis. Evidence suggests parallels in the pathogenesis of cancer, where ?omics data are available, and PH, thus making a repurposing of chemotherapeutics for PH possible. This proposal leverages a network-based analysis of cancer ?omics data to predict in silico and define experimentally which chemotherapies may offer the most robust actions in PH. Specifically, high density RNA sequencing data were combined with a compilation of gene clusters important in PH and a novel computational algorithm, EDDY, to define the re-wiring of PH dependency networks in response to specific chemotherapies. Two drugs were ranked particularly high in terms of most substantial re-wiring across PH clusters and overlap with activity in one particular ?hot-spot? PH gene cluster. These drugs were the BET protein inhibitors I-BET151/I- BET762 and the JAK/STAT inhibitor momelotinib -- drugs that have never been screened for efficacy in PH and where there is sparse but emerging evidence of BET protein and JAK activity in this disease. Importantly, I- BET762 is being studied in a Phase I clinical trial for cancer, and momelotinib is undergoing Phase 3 trials for myelofibrosis, with completed Phase 1/2 trials. Hypothesis: As guided computationally by EDDY, I-BET762/momelotinib work synergistically to modulate BET- and JAK/STAT-specific vascular cell reprogramming to reverse PH pathogenesis.
Specific Aim : Determine the combinatorial efficacy of I-BET762 and momelotinib in controlling the PH gene network state and PH in vivo. We will interrogate the molecular actions of these drugs on predicted ?hot- spot? PH gene clusters in human pulmonary vascular cells and in rodents with PH (UH2 phase). If successful, molecular connections will be described among chemotherapies and disease gene networks, establishing proof for this unique drug repurposing platform. We then would plan a Phase 1/2 randomized-controlled double-blind study of patients with Group 1 PH (PAH) and Group 2 PH taking I-BET762 and momelotinib, singly or in combination, versus matched placebo (on top of existing therapy) (UH3 phase). Importantly, with our Center?s volume of PH patients and expertise in PH clinical trials, we are uniquely positioned for successful and expedited completion of both preclinical and clinical phases of this work. Significance: A combined computational and experimental approach has rarely been attempted to screen chemotherapies for their precise, systems-level effects in diverse diseases, including PH. As such, current PH drugs neither prevent nor reverse disease progression. This proposal aims to define the therapeutic actions of I-BET762 and momelotinib in PH and mitigate the delay of developing new drugs de novo. Moreover, this work would establish the validity of a computational pipeline designed to repurpose drugs for a variety of diseases not possible to date.

Public Health Relevance

In this proposal, we plan to test a new mathematical algorithm designed to determine if specific combinations of chemotherapies ? drugs that have been tested for treatment of cancer ? are effective in the treatment of pulmonary hypertension (PH), an enigmatic disease of the blood vessels of the lungs where there is a lack of effective medications. If successful, this work will accelerate the testing of two specific chemotherapies, I- BET762 and momelotinib, in human PH and mitigate a delay of decades to develop new molecular inhibitors de novo. Moreover, this work would establish the further use of this algorithm in defining how to use chemotherapies in diseases even beyond PH in a way that has not yet been possible.

Agency
National Institute of Health (NIH)
Institute
National Center for Advancing Translational Sciences (NCATS)
Type
Exploratory/Developmental Cooperative Agreement Phase I (UH2)
Project #
5UH2TR002073-02
Application #
9535513
Study Section
Special Emphasis Panel (ZTR1)
Program Officer
Mount, Bobbie Ann
Project Start
2017-08-01
Project End
2019-07-31
Budget Start
2018-08-01
Budget End
2019-07-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
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