Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio, USA.
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio, USA.
Proteomics. 2021 May;21(9):e2000103. doi: 10.1002/pmic.202000103. Epub 2021 Feb 26.
Advances in two-dimensional (2D) and three-dimensional (3D) cell culture over the last 10 years have led to the development of a plethora of methods for cultivating tumor models. More recently, cellular co-cultures have become a suitable testbed. The first portion of this review focuses on co-culturing methods that have been developed in recent years utilizing the multicellular tumor spheroid model. The latter portion describes techniques that are used to analyze the proteomes of mono- or co-cultured tumor models, with a focus on mass spectrometry (MS)-based analyses. Protein profiles are important indicators of the tumor heterogeneity. Therefore, there is a specific focus within this review on analysis by MS and MS imaging methods evaluating the proteomic profiles of 2D and 3D co-cultures. While these models are incredibly important for biological research, so far, they have not been widely explored on the proteomic level. With this review, we aim to introduce these systems to an analytical audience, with the goal of highlighting MS as an underutilized tool for proteomic analysis of tumor models.
过去 10 年中,二维 (2D) 和三维 (3D) 细胞培养技术的进步促使人们开发出了大量的肿瘤模型培养方法。最近,细胞共培养已成为一个合适的试验平台。本文的前半部分主要介绍了近年来利用多细胞肿瘤球体模型开发的共培养方法。后半部分描述了用于分析单培养或共培养肿瘤模型蛋白质组的技术,重点是基于质谱 (MS) 的分析。蛋白质图谱是肿瘤异质性的重要指标。因此,本文特别关注通过 MS 和 MS 成像方法分析二维和三维共培养物的蛋白质组谱。虽然这些模型对于生物学研究非常重要,但迄今为止,它们在蛋白质组学水平上尚未得到广泛探索。通过本文综述,我们旨在向分析人员介绍这些系统,目标是强调 MS 作为肿瘤模型蛋白质组分析中未充分利用的工具。