Metal ion-enhanced ZIC-cHILIC StageTip for N-Glycoproteomic and Phosphoproteomic Profiling in EGFR-mutated Lung Cancer Cells.

IF 6.1 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Yi-Ju Chen, Yan-Lin Chen, Kun-Hao Chang, Hsiang-Chun Cheng, Chiao-Chun Chang, Yu-Ju Chen
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引用次数: 0

Abstract

Surface glycosylation and intracellular phosphorylation regulates the cell-cell communication and signaling cascades. Due to complex glycosylation and dynamic phosphorylation, exploring their interplay remains technically challenging. In this study, we reported a tandem ZIC-cHILIC StageTip strategy for streamlined and simultaneous (sialo)glycoproteomic and phosphoproteomic profiling. We first demonstrated that Fe ions expand the utility of ZIC-cHILIC strategy to phosphoproteomic analysis with greatly enhanced >4-fold coverage and high specificity for mono-phosphopeptides (95%). The Fe-ZIC-cHILIC tandem tips, leveraging stepwise fractionation, enable large-scale coverage of 10,536 glycopeptides, including highly confident 4,285 sialoglycopeptpides, and 11,329 phosphopeptides in a single cell type. To study the mechanism underlying the tyrosine kinase inhibitor (TKI) resistance in non-small cell lung cancer (NSCLC), application of the strategy to 4 NSCLC cells harboring different EGFR mutations reveals significantly differential 1,559 glycopeptides and 1,949 phosphopeptides either in EGFR mutation or TKI resistant cells. Without protein immunoprecipitation, the approach identified FDA-approved drug targets, such as EGFR, ERBB2, MET, and integrin family members. Most prominent alterations were observed in EGFR (auto-phosphorylation Y1197 and 10 bi- and triantennary fucosyl-sialo glycans at N603), downstream PI3K-Akt pathway (ERBB2-T1240, MET-S990/T992, AKT-S124/S126) and integrin family (sialo-fucosyl glycans), suggesting site-specific alteration between N-glycosylation and phosphorylation interplay in the TKI resistant L858R-T790M mutant NSCLC cells. The glycoproteomic and phosphoproteomic landscape may help to unravel the complex modification alterations underlying the resistant mechanism, offering insights for improving therapeutic strategies and patient outcomes.

金属离子增强的ZIC-cHILIC StageTip用于egfr突变肺癌细胞的n-糖蛋白组学和磷蛋白组学分析。
表面糖基化和细胞内磷酸化调节细胞间通讯和信号级联反应。由于复杂的糖基化和动态磷酸化,探索它们的相互作用在技术上仍然具有挑战性。在这项研究中,我们报道了一种串联ZIC-cHILIC StageTip策略,用于流线型和同时(sialo)糖蛋白质组学和磷蛋白质组学分析。我们首先证明了铁离子将ZIC-cHILIC策略扩展到磷酸蛋白质组学分析,极大地提高了bbbb4倍的覆盖率和对单磷酸多肽的高特异性(95%)。Fe-ZIC-cHILIC串联尖端,利用逐步分离,可以大规模覆盖10,536个糖肽,包括高度自信的4,285个唾液糖肽和11,329个单个细胞类型的磷酸肽。为了研究酪氨酸激酶抑制剂(TKI)在非小细胞肺癌(NSCLC)中耐药的机制,将该策略应用于4个具有不同EGFR突变的NSCLC细胞,发现在EGFR突变或TKI耐药细胞中有1,559个糖肽和1,949个磷酸肽显著差异。在没有蛋白免疫沉淀的情况下,该方法确定了fda批准的药物靶点,如EGFR、ERBB2、MET和整合素家族成员。最显著的改变发生在EGFR(自磷酸化Y1197和10双链和三链聚焦基-sialo glycans in N603),下游PI3K-Akt通路(ERBB2-T1240, MET-S990/T992, AKT-S124/S126)和整合素家族(sialo- focusyl glycans),提示在TKI耐药L858R-T790M突变型NSCLC细胞中n -糖基化和磷酸化相互作用之间的位点特异性改变。糖蛋白组学和磷蛋白组学研究可能有助于揭示耐药机制背后的复杂修饰改变,为改善治疗策略和患者预后提供见解。
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来源期刊
Molecular & Cellular Proteomics
Molecular & Cellular Proteomics 生物-生化研究方法
CiteScore
11.50
自引率
4.30%
发文量
131
审稿时长
84 days
期刊介绍: The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes
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