Clinical and Translational Science (Apr 2022)
A case study of a patient‐centered reverse translational systems‐based approach to understand adverse event profiles in drug development
Abstract
Abstract Adverse drug reactions (ADRs) of targeted therapy drugs (TTDs) are frequently unexpected and long‐term toxicities detract from exceptional efficacy of new TTDs. In this proof‐of‐concept study, we explored how molecular causation involved in trastuzumab‐induced cardiotoxicity changes when trastuzumab was given in combination with doxorubicin, tamoxifen, paroxetine, or lapatinib. The data analytical platform Molecular Health Effect was utilized to map population ADR data from the US Food and Drug Administration (FDA) Adverse Event Reporting System to chemical and biological databases (such as UniProt and Reactome), for hypothesis generation regarding the underlying molecular mechanisms causing cardiotoxicity. Disproportionality analysis was used to assess the statistical relevance between adverse events of interest and molecular causation. Literature search was performed to compare the established hypotheses to published experimental findings. We found that the combination therapy of trastuzumab and doxorubicin may affect mitochondrial dysfunction in cardiomyocytes through different molecular pathways such as BCL‐X and PGC‐1α proteins, leading to a synergistic effect of cardiotoxicity. We found, on the other hand, that trastuzumab‐induced cardiotoxicity would be diminished by concomitant use of tamoxifen, paroxetine, and/or lapatinib. Tamoxifen and paroxetine may cause less cardiotoxicity through an increase in antioxidant activities, such as glutathione conjugation. Lapatinib may decrease the apoptotic effects in cardiomyocytes by altering the effects of trastuzumab on BCL‐X proteins. This patient‐centered systems‐based approach provides, based on the trastuzumab‐induced ADR cardiotoxicity, an example of how to apply reverse translation to investigate ADRs at the molecular pathway and target level to understand the causality and prevalence during drug development of novel therapeutics.