三维(3D)癌症模型正在彻底改变研究,允许通过使用体外系统来概括体内反应,比传统的单层文化更复杂和生理相关。卵巢癌(OvCa)等癌症容易产生耐药性,通常是致命的,并将从3D文化模拟的增强建模中受益匪浅。然而,当前的模型往往达不到预测的响应,由于缺乏标准化的方法和既定的协议,可重复性受到限制。这项荟萃分析旨在评估3DOvCa模型的当前范围以及大量3D培养物呈现的遗传谱差异。对2012-2022年的文献(Pubmed.gov)进行分析,以确定除RNA测序和微阵列数据外,还具有3D和2D单层配对数据的研究。从数据来看,发现19个细胞系在其基因表达谱中显示出差异调节,这取决于生物支架(即,琼脂糖,胶原蛋白,或Matrigel)与2D细胞培养物相比。在2D与2D中差异表达的顶级基因3D包括C3、CXCL1、2和8、IL1B、SLP1,FN1,IL6,DDIT4,PI3,LAMC2,CCL20,MMP1,IFI27,CFB,ANGPTL4。2D与2D的顶级丰富基因集3D包括IFN-α和IFN-γ反应,TNF-α信号,IL-6-JAK-STAT3信号,血管生成,刺猬信号,凋亡,上皮-间质转化,缺氧,和炎症反应。我们对众多支架的横向比较使我们能够突出这些支架在转录景观中可能引起的变异性,并确定关键基因和生物过程,这些基因和生物过程是3D培养物中生长的癌细胞的标志。需要未来的研究来确定哪一种是研究肿瘤微环境的最合适的体外/临床前模型。
Three-dimensional (3D) cancer models are revolutionising research, allowing for the recapitulation of an in vivo-like response through the use of an in vitro system, which is more complex and physiologically relevant than traditional monolayer cultures. Cancers such as ovarian (OvCa) are prone to developing resistance, are often lethal, and stand to benefit greatly from the enhanced modelling emulated by 3D cultures. However, the current models often fall short of the predicted response, where reproducibility is limited owing to the lack of standardised methodology and established protocols. This meta-analysis aims to assess the current scope of 3D OvCa models and the differences in the genetic profiles presented by a vast array of 3D cultures. An analysis of the literature (Pubmed.gov) spanning 2012-2022 was used to identify studies with paired data of 3D and
2D monolayer counterparts in addition to RNA sequencing and microarray data. From the data, 19 cell lines were found to show differential regulation in their gene expression profiles depending on the bio-scaffold (i.e., agarose, collagen, or Matrigel) compared to
2D cell cultures. The top genes differentially expressed in
2D vs. 3D included C3, CXCL1, 2, and 8, IL1B, SLP1, FN1, IL6, DDIT4, PI3, LAMC2, CCL20, MMP1, IFI27, CFB, and ANGPTL4. The top enriched gene sets for
2D vs. 3D included IFN-α and IFN-γ response, TNF-α signalling, IL-6-JAK-STAT3 signalling, angiogenesis, hedgehog signalling, apoptosis, epithelial-mesenchymal transition, hypoxia, and inflammatory response. Our transversal comparison of numerous scaffolds allowed us to highlight the variability that can be induced by these scaffolds in the transcriptional landscape and identify key genes and biological processes that are hallmarks of cancer cells grown in 3D cultures. Future studies are needed to identify which is the most appropriate in vitro/preclinical model to study tumour microenvironments.