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Cell子刊:超40种癌症类型的949个癌症细胞系的蛋白质图谱公布

2022-08-10 转化医学网 转化医学网

通过深度学习的方式开发出189种药物敏感性预测的生物标志物,对肿瘤科学研究及药物应用有深远意义。

导读:蛋白质组研究,是在整体水平上研究细胞、组织乃至整个生命体内蛋白质组成及其活动规律的科学,由此从蛋白质水平上获得关于疾病发生、细胞代谢等过程整体而全面的认识。而蛋白质组学存在标准化、高通量的的特点,可提高将候选生物标志物和药物靶标转化为临床应用的效率,已成为癌症系统生物学的重要组成部分。

8月8日,《Cancer Cell》通过一项研究“Pan-cancer proteomic map of 949 human cell lines”公布了超过 40 种癌症类型的 949 种人类癌细胞系的泛癌蛋白质组图谱,并发现有 8498 种蛋白质具有广泛的转录后调控现象,并基于深度学习的发现药物反应相关的生物标志物。

Doi: 10.1016/j.ccell.2022.06.010.

研究背景

01

蛋白质的直接测量可以深入了解细胞的动态分子行为,并可以加深我们对于基因型与表型关系的理解,然而,癌症的复杂性和基因组学无法准确预测蛋白质组。仅靠基因组学通常不足以为许多患者的临床护理提供信息和指导,因此,蛋白质组的测量有可能扩大我们对癌症表型的理解并改进诊断和治疗选择。

细胞系是理解细胞过程和癌基因驱动特征的重要模型,然而,癌细胞系的蛋白质组学受限于癌症类型的范围或样本数量,在很大程度上无法获取。迄今为止,癌症脆弱性的生物标志物主要基于基因组和转录组测量,因此,通过蛋白质组研究癌症细胞系发现癌症的弱点至关重要。

研究过程

02

1.对 949 个癌症细胞系进行蛋白质组学检测:为了构建泛癌蛋白质组图谱,研究人员通过MIA-MS法(每组6个重复)对来自 28 个组织和 40 多种不同遗传学及组织学的 949 种人类癌细胞系进行蛋白质检测,然后进行量化收集完整的蛋白质组学数据,在每个细胞系的重复之间观察到高度相关性,并发现与其他蛋白质相比,富含细胞类型的蛋白质在转录组和蛋白质组之间具有更高的相关性。因此,这些蛋白质可以代表在转录和翻译之间更高度保守的细胞类型特异性过程,且蛋白质组数据与细胞谱系的总体一致性(图1 )。

图1. 949 个人类癌细胞系的泛癌蛋白质组图谱

2.癌细胞的具体蛋白组改变:为探究何种驱动因素在肿瘤生物学行为中扮演重要角色,研究人员进行多组学因子分析,发现上皮间质转化 (EMT) 经典标志物波形蛋白和 E-钙粘蛋白在多种癌症中显著高表达,且EMT基因集富集分析的评分也显著上调。此外,该蛋白质组学亦揭示了不同不同细胞表型(耐药、肿瘤发生等)的代表性因子,研究人员发现这些癌细胞中的蛋白质存在表达差异,因此推测这些蛋白质存在转录后调控的现象(图2)。

图2. 不同癌细胞类型的转录后调控

3. 癌细胞特异性标志物:为进一步通过蛋白组组学开发出可以预测药物反应的生物标志物,研究人员通过蛋白质组学与检测药物敏感性相结合的方式确定了189种药物的敏感性标志物,并通过深度学习的方式评估了这种药物-蛋白相互作用,精确表征何种蛋白质适用于对应药物(图3)。

图3. 蛋白质生物标志物

研究意义

03

这项研究公布了一个大型泛癌蛋白质组图,提供了超越现有组学数据的大量蛋白水平的癌症数据-量化了代表 28 种组织和 40 多种组织学不同的癌症类型的 949 种人类癌细胞系中的 8,498 种蛋白质和广泛的基因型。通过深度学习的方式开发出189种药物敏感性预测的生物标志物,对肿瘤科学研究及药物应用有深远意义。

参考资料:

https://www.sciencedirect.com/science/article/pii/S1535610822002744

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    2022-09-16 维他命
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    2022-09-26 zhwj
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    2022-08-10 ms5000000518166734

    学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习学习

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