An In Vitro Cynomolgus Vascular Surrogate System for Preclinical Drug Assessment and Human Translation

Abstract

Cynomolgus macaques are highly responsive to atherogenic diets, and the atherogenic response is influenced by lipoprotein diet composition. Atherogenic diet-fed cynomolgus macaques develop coronary artery lesions, raised plasma cholesterol levels, and lesions of similar composition to humans. Atherosclerosis development in cynomolgus macaques is highly influenced by genetic predisposition, confounding diseases (such as diabetes mellitus), exercise, sex (increased susceptibility in men), and behavioral and psychosocial factors. Objectives-The predictive value of animal and in vitro systems for drug development is limited, particularly for nonhuman primate studies as it is difficult to deduce the drug mechanism of action. We describe the development of an in vitro cynomolgus macaque vascular system that reflects the in vivo biology of healthy, atheroprone, or advanced inflammatory cardiovascular disease conditions. Approach and Results-We compare the responses of the in vitro human and cynomolgus vascular systems to 4 statins.Although statins exert beneficial pleiotropic effects on the human vasculature, the mechanism of action is difficult to investigate at the tissue level. Using RNA sequencing, we quantified the response to statins and report that most statins significantly increased the expression of genes that promote vascular health while suppressing inflammatory cytokine gene expression. Applying computational pathway analytics, we identified statin-regulated biological themes, independent of cholesterol lowering, that provide mechanisms for off-target effects, including thrombosis, cell cycle regulation, glycogen metabolism, and ethanol degradation. Conclusions-The cynomolgus vascular system described herein mimics the baseline and inflammatory regional biology of the human vasculature, including statin responsiveness, and provides mechanistic insight not achievable in vivo. All of these characteristics are similar to the human atherosclerosis disease, and thus, they make cynomolgus macaques a good nonhuman primate model for atherosclerosis. 7,8 In this study, a cynomolgus vascular system was developed using primary endothelial cells (ECs), smooth muscle cells (SMCs), and hemodynamics derived in vivo from cynomolgus arteries. The system was validated against inflammatory risk factor response, including a comparison between human-and cynomolgus-derived oxidized low-density lipoproteins (LDLs), and exposure to several statins. A comparative analysis between the cynomolgus and human vascular tissue systems was conducted to determine the cross-species translational capabilities of these models, which is an important component in the transition from preclinical to human clinical studies. Materials and MethodsMaterials and Methods are available in the online-only Data Supplement. Results Development of an In Vitro Cynomolgus Vascular Surrogate SystemThe human vascular surrogate system applies human-derived blood shear stress patterns to a transwell vascular coculture of ECs and SMCs ( Figure 1A). Atherosclerotic...

Pharmacotoxicology of clinically-relevant concentrations of obeticholic acid in an organotypic human hepatocyte system

“…The distribution and spread of data points reflects a greater number of genes that were differentially expressed at the supratherapeutic concentration (Total: 4954, Up-regulated: 2539, Down-regulated: 2415; p<0.01, FDR<10%) than the therapeutic concentration (Total: 2373 Up-regulated: 1110, Down-regulated: 1263; p<0.01). Analysis of the transcriptomic responses at both doses using the relative similarity index (RSI) methods described previously (Cole et al 2015; Feaver etl. 2016), revealed that a majority of the differentially expressed genes (DEGs) were regulated in the same direction (2238 genes; RSI>0.74) and only a small number (3 genes; RSI<−0.74) were regulated in opposite directions (Supplementary Figure S1).…”

“…Our data analysis algorithms have been previously published (Cole et al 2015; Feaver et al 2016). Briefly, following RNA deep sequencing, the reads were aligned to a standard hg19 human transcriptome using Bowtie 0.12.9 (Langmead and Salzberg, 2012) and the final gene counts calculated using eXpress v1.5.1 (Roberts et al 2013).…”

“…If two conditions stimulated identical responses, all the data would fall on the identity line of a gene-by-gene scatterplot. The Response Similarity Index (RSI) was calculated for each gene and determined the degree to which the two conditions altered gene expression in the same (RSI>0.2, purple dots) or opposite (RSI<-0.2, green dots) manner (Supplementary Figure S1) (Cole et al 2015; Feaver et al 2016). Summary radar plots were plotted to quantitatively depict the average FDR-corrected gene expression fold-change for the indicated pathways relative to the vehicle control.…”

Exposure of Induced Pluripotent Stem Cell-Derived Vascular Endothelial and Smooth Muscle Cells in Coculture to Hemodynamics Induces Primary Vascular Cell-Like Phenotypes

“…Herein, we assessed human iECs and iSMCs cocultured under vascular region-specific blood flow hemodynamics to determine if they display similar transcriptomic and functional responses to cocultures of primary human endothelial (pEC) and smooth muscle (pSMC) cells exposed to the same hemodynamics. We have previously demonstrated that this human vascular surrogate system utilizing cocultures of pEC:pSMC exposed to relevant hemodynamics mimics the in vivo endothelial and smooth muscle architecture, biology and physiology of the blood vessel wall, and is highly responsive to changes in hemodynamics, inflammatory milieu, and drug treatments [4][5][6]. Our results indicate that iPSC-derived vascular cells exhibit an immature phenotype and that hemodynamic coculture of iEC:iSMC restores a high degree of similarity to that of pEC:pSMC.…”

Transcriptional profiling suggests that Nevirapine and Ritonavir cause drug induced liver injury through distinct mechanisms in primary human hepatocytes

“…Our rigorous data analysis algorithms have been previously published(37). Briefly, following RNA deep sequencing, the reads were aligned to a standard hg19 human transcriptome.…”