Dataset Information

Hierarchical Vessel Network-Supported Tumor Model-on-a-Chip Constructed by Induced Spontaneous Anastomosis.

ABSTRACT: The vascular system in living tissues is a highly organized system that consists of vessels with various diameters for nutrient delivery and waste transport. In recent years, many vessel construction methods have been developed for building vascularized on-chip tissue models. These methods usually focused on constructing vessels at a single scale. In this work, a method that can build a hierarchical and perfusable vessel networks was developed. By providing flow stimuli and proper HUVEC concentration, spontaneous anastomosis between endothelialized lumens and the self-assembled capillary network was induced; thus, a perfusable network containing vessels at different scales was achieved. With this simple method, an in vivo-like hierarchical vessel-supported tumor model was prepared and its application in anticancer drug testing was demonstrated. The tumor growth rate was predicted by combining computational fluid dynamics simulation and a tumor growth mathematical model to understand the vessel perfusability effect on tumor growth rate in the hierarchical vessel network. Compared to the tumor model without capillary vessels, the hierarchical vessel-supported tumor shows a significantly higher growth rate and drug delivery efficiency.

SUBMITTER: Zhou Y

PROVIDER: S-EPMC10249001 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Hierarchical Vessel Network-Supported Tumor Model-on-a-Chip Constructed by Induced Spontaneous Anastomosis.

Zhou Yuyuan Y Wu Yue Y Paul Ratul R Qin Xiaochen X Liu Yaling Y

ACS applied materials & interfaces 20230124 5

The vascular system in living tissues is a highly organized system that consists of vessels with various diameters for nutrient delivery and waste transport. In recent years, many vessel construction methods have been developed for building vascularized on-chip tissue models. These methods usually focused on constructing vessels at a single scale. In this work, a method that can build a hierarchical and perfusable vessel networks was developed. By providing flow stimuli and proper HUVEC concentr ...[more]

PMID: 36693007

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Project description:Endothelial mechanobiology is a key consideration in the progression of vascular dysfunction, including atherosclerosis. However mechanistic connections between the clinically associated physical stimuli, vessel stiffness and shear stress, and how they interact to modulate plaque progression remain incompletely characterized. Vessel-chip systems are excellent candidates for modeling vascular mechanobiology as they may be engineered from the ground up, guided by the mechanical parameters present in human arteries and veins, to recapitulate key features of the vasculature. Here, we report extensive validation of a vessel-chip model of endothelial yes-associated protein (YAP) mechanobiology, a protein sensitive to both matrix stiffness and shearing forces and, importantly, implicated in atherosclerotic progression. Our model captures the established endothelial mechanoresponse, with endothelial alignment, elongation, reduction of adhesion molecules, and YAP cytoplasmic retention under high laminar shear. Conversely, we observed disturbed morphology, inflammation, and nuclear partitioning under low, high, and high oscillatory shear. Examining targets of YAP transcriptional co-activation, connective tissue growth factor (CTGF) is strongly downregulated by high laminar shear, whereas it is strongly upregulated by low shear or oscillatory flow. Ankyrin repeat domain 1 (ANKRD1) is only upregulated by high oscillatory shear. Verteporfin inhibition of YAP reduced the expression of CTGF but did not affect ANKRD1. Lastly, substrate stiffness modulated the endothelial shear mechanoresponse. Under high shear, softer substrates showed the lowest nuclear localization of YAP whereas stiffer substrates increased nuclear localization. Low shear strongly increased nuclear localization of YAP across stiffnesses. Together, we have validated a model of endothelial mechanobiology and describe a clinically relevant biological connection between matrix stiffness, shear stress, and endothelial activation via YAP mechanobiology.

Project description:BackgroundGlobal profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF) partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks.ResultsIn this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2) were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM). A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes.We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study) and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes) and targeted TFs (25% of common TFs). The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells.ConclusionsOur study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to further study the underlying mechanisms in breast cancer cells or other human diseases.

Dataset Information

Hierarchical Vessel Network-Supported Tumor Model-on-a-Chip Constructed by Induced Spontaneous Anastomosis.

Publications

Hierarchical Vessel Network-Supported Tumor Model-on-a-Chip Constructed by Induced Spontaneous Anastomosis.

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