Showing papers by "Brian R. Wamhoff published in 2019"
TL;DR: This work provides a general framework for the use of high-content molecular profiling to identify NAFLD patient sub groups and shows that patient subgroups can be distinguished by the relative distribution of gene-level scores in specific gene sets.
Abstract: The heterogeneity of biological processes driving the severity of nonalcoholic fatty liver disease (NAFLD) as reflected in the transcriptome and the relationship between the pathways involved are not well established. Well-defined associations between gene expression profiles and disease progression would benefit efforts to develop novel therapies and to understand disease heterogeneity. We analyzed hepatic gene expression in controls and a cohort with the full histological spectrum of NAFLD. Protein-protein interaction and gene set variation analysis revealed distinct sets of coordinately regulated genes and pathways whose expression progressively change over the course of the disease. The progressive nature of these changes enabled us to develop a framework for calculating a disease progression score for individual genes. We show that, in aggregate, these scores correlate strongly with histological measures of disease progression and can thus themselves serve as a proxy for severity. Furthermore, we demonstrate that the expression levels of a small number of genes (~20) can be used to infer disease severity. Finally, we show that patient subgroups can be distinguished by the relative distribution of gene-level scores in specific gene sets. While future work is required to identify the specific disease characteristics that correspond to patient clusters identified on this basis, this work provides a general framework for the use of high-content molecular profiling to identify NAFLD patient subgroups.
89 citations
TL;DR: It is demonstrated that significant tumor cell transcriptomic changes occur in the TMES that correlate with the in vivo xenograft and patient transcriptome, and provides a unique platform to rigorously evaluate novel therapies and is amenable to using patient tumor material directly, with applicability for patient avatars.
Abstract: The development of drugs to treat cancer is hampered by the inefficiency of translating pre-clinical in vitro monoculture and mouse studies into clinical benefit. There is a critical need to improve the accuracy of evaluating pre-clinical drug efficacy through the development of more physiologically relevant models. In this study, a human triculture 3D in vitro tumor microenvironment system (TMES) was engineered to accurately mimic the tumor microenvironment. The TMES recapitulates tumor hemodynamics and biological transport with co-cultured human microvascular endothelial cells, pancreatic ductal adenocarcinoma, and pancreatic stellate cells. We demonstrate that significant tumor cell transcriptomic changes occur in the TMES that correlate with the in vivo xenograft and patient transcriptome. Treatment with therapeutically relevant doses of chemotherapeutics yields responses paralleling the patients' clinical responses. Thus, this model provides a unique platform to rigorously evaluate novel therapies and is amenable to using patient tumor material directly, with applicability for patient avatars.
22 citations