Integrated multi-dimensional comparison of proteomic profiles across 54 cancer cell lines

IF 4.1 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

iScience Pub Date : 2025-09-05 DOI:10.1016/j.isci.2025.113514

Wenhao Shi , Tianlong He , Nan Wang , Annan Qian , Yuqiao Liu , Shaojun Tang , Yiying Zhu

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Abstract

Human cancer cell lines are essential model systems in biomedical research. We conducted multi-level proteomics analyses on 54 widely used cancer cell lines derived from various tissues using two prominent proteomics technologies: mass spectrometry (MS) and reverse-phase protein array (RPPA). Our analysis identified 10,088 proteins, 33,161 phosphorylation sites across 7,469 phosphoproteins, and 56,320 site-specific glycans on 14,228 glycosylation sites from 5,966 glycoproteins, along with 305 drug-relevant protein and phosphoprotein targets. Analysis of this rich dataset yielded numerous biological insights, including protein features that distinguish tissue origins and cell line-specific kinase activation patterns, reflecting signaling diversity across cancer types. These findings may inform therapeutic strategies and support rational model system selection. Additionally, MS and RPPA showed consistent fold-change estimation and provided complementary views of proteome and signaling variation. This comprehensive resource facilitates biomarker discovery, signaling analysis, and translational oncology research across diverse human tumor types.

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54种癌细胞系蛋白质组学特征的综合多维比较

人类癌细胞系是生物医学研究中必不可少的模型系统。我们使用两种主要的蛋白质组学技术：质谱（MS）和反相蛋白质阵列（RPPA），对来自不同组织的54种广泛使用的癌细胞系进行了多层次蛋白质组学分析。我们的分析确定了10,088个蛋白，7,469个磷酸化蛋白中的33,161个磷酸化位点，5,966个糖蛋白中的14,228个糖基化位点上的56,320个位点特异性聚糖，以及305个药物相关蛋白和磷酸化蛋白靶点。对这一丰富数据集的分析产生了许多生物学见解，包括区分组织起源和细胞系特异性激酶激活模式的蛋白质特征，反映了癌症类型的信号多样性。这些发现可能为治疗策略提供信息，并支持合理的模型系统选择。此外，MS和RPPA显示出一致的折叠变化估计，并提供了蛋白质组和信号变异的互补观点。这个全面的资源促进了生物标志物的发现，信号分析和转化肿瘤学研究跨越不同的人类肿瘤类型。

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来源期刊

iScience Multidisciplinary-Multidisciplinary

CiteScore

7.20

自引率

1.70%

发文量

1972

审稿时长

6 weeks

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