| Literature DB >> 34901543 |
Yao Bin1,2,3,4, Zhu Dongzhen1,2, Cui Xiaoli5, Enhe Jirigala6,7, Song Wei1,2, Li Zhao1,2, Hu Tian1,2,8, Zhu Ping4, Li Jianjun1,2, Wang Yuzhen1,2, Zhang Yijie1,2, Fu Xiaobing1,2, Huang Sha1,2.
Abstract
The therapeutic interventions of human hypertrophic scars (HHS) remain puzzle largely due to the lack of accepted models. Current HHS models are limited by their inability to mimic native scar architecture and associated pathological microenvironments. Here, we create a 3D functional HHS model by preformed cellular aggregates (PCA) bioprinting, firstly developing bioink from scar decellularized extracellular matrix (ECM) and alginate-gelatin (Alg-Gel) hydrogel with suitable physical properties to mimic the microenvironmental factors, then pre-culturing patient-derived fibroblasts in this bioink to preform the topographic cellular aggregates for sequent printing. We confirm the cell aggregates preformed in bioink displayed well defined aligned structure and formed functional scar tissue self-organization after bioprinting, hence showing the potential of creating HHS models. Notably, these HHS models exhibit characteristics of early-stage HHS in gene and protein expression, which significantly activated signaling pathway related to inflammation and cell proliferation, and recapitulate in vivo tissue dynamics of scar forming. We also use the in vitro and in vivo models to define the clinically observed effects to treatment with concurrent anti-scarring drugs, and the data show that it can be used to evaluate the potential therapeutic target for drug testing. The ideal humanized scar models we present should prove useful for studying critical mechanisms underlying HHS and to rapidly test new drug targets and develop patient-specific optimal therapeutic strategies in the future.Entities:
Keywords: 3D bioprinting; Drug screening; Hypertrophic scar model; Microenvironmental cues; Preformed cell aggregates
Year: 2021 PMID: 34901543 PMCID: PMC8636708 DOI: 10.1016/j.bioactmat.2021.09.004
Source DB: PubMed Journal: Bioact Mater ISSN: 2452-199X
Fig. 1Preparation of bioinks. (A) Schematic illustration of the whole process of fabrication of scar model. (B) HE (Scale bar = 200 μm) and SEM images (Scale bar = 100 μm) of normal dECM and scar dECM and components of native tissue and dECM. (C) Local mechanical strength of different bioinks. (D) Gelation of hydrogels and SEM images of bioinks (scale bar = 500 μm) and the related statistics. (E) Formation of cell aggregates in different bioinks with different culture time (scale bar = 200 μm). (F) Statistical analysis of diameters and numbers of cell aggregates under different pre-culture conditions (n = 3).
Fig. 2Optimization of 3D printing parameters. (A) Schematic illustration of the details of PCA bioprinting. (B) Rheological properties of pre-cultured bioinks (n = 3). (C) Optimized printing parameters for pre-cultured bioink. (D) A lattice-shaped construct with different layers and Various 3D printed constructs. (E) Live/Dead staining and the proliferation rate of cells in the 3D structure (Live cells: green, Dead cells: red, scale bar = 200 μm). (F) Alligned cell aggregates and cell distribution in 3D printed constructs with culture. (G) The structure of pre-cultured 3D bioprinted constructs (Scale bar = 100 μm) and the aligned cells (Phalloidin: green, DAPI: blue, scale bar = 25 μm) and the expression of myofibroblasts markers (α-SMA, TGFβ1: green, DAPI: blue, scale bar = 25 μm). G0: without pre-culture; D3: pre-culture for 3 days. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3Recapitulation of the pathological features of scar. (A, B) (A)The differential expression profile of normal dECM and scar dECM and (B) GO analysis of differentiated proteins. (C) The printed groups with different bioinks. (D, E) The expression of myofibroblast markers at gene (D) (Data are mean ± SEM, n = 3, *p < 0.05) and protein (E) level (α-SMA, TGFβ1, Col I: red, DAPI: blue, scale bar = 25 μm). (F) Transcriptional analysis of scar model with different combination of environmental cues and scar tissue. 1ASS: 1A3G+SFb+scar ECM, 3AS: 3A5G+SFb, 3ASS: 3A5G+SFb+scar ECM, SFt: scar tissue. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4Performance of predicted drugs in the bioprinted scar model. (A) The enrichment of gene sets from the GO database. (B) Schematic illustration of mechanism of drug screen. (C, D) The expression of pro-fibrotic molecule and anti-fibrotic molecule at gene (C) (Data are mean ± SEM, n = 3, *p < 0.05) and protein (D) level (α-SMA, TGFβ1, TGFβ3: green, DAPI: blue, scale bar = 25 μm). 3ASS: 3A5G+SFb+scar ECM, 3A–D: 3ASS+DMSO, 3A–A: 3ASS+ Abemaciclib, 3A–C: 3ASS+ Cobimetinib, 3A–T: 3ASS+ Triamcinolone acetonide. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5Transplantation of scar model into adult immunodeficient mice displays characteristics of early stage of scar and confirmed the effect of screened drugs. (A) Schematic illustration of the whole process of animal test. (B) The macroscophic images of scar formation in different groups. (C) HE (Scale bar = 200 μm) and Masson images (Scale bar = 200 μm) of scar tissue in different groups. (D) The expression of myofibroblasts markers in different groups (α-SMA, Col I: red, DAPI: blue, scale bar = 100 μm). 3A5G: 3A5G+SFb+scar ECM, 3A–C: 3ASS+ Cobimetinib, 3A–T: 3ASS+ Triamcinolone acetonide. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)