Phosphoproteomics in cancer.
Ontology highlight
ABSTRACT:
SUBMITTER: Harsha HC
PROVIDER: S-EPMC3030978 | biostudies-other | 2010 Dec
REPOSITORIES: biostudies-other
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Project description:Proteome-wide profiling of protein phosphorylation has been widely used to reveal the underlying mechanism of diverse cellular signaling events. Yet, characterizing subcellular phosphoproteome with high spatial-temporal resolution has remained challenging. Herein, we developed a subcellular-specific uncaging-assisted biotinylation and mapping of phosphoproteome (SubMAPP) strategy to monitor the phosphorylation dynamics of subcellular proteome in living cells and animals. Our method capitalizes on the genetically encoded bioorthogonal decaging strategy, which enables the rapid activation of subcellular localized proximity labeling biotin ligase through either light illumination or small-molecule triggers. By further adopting an integrated orthogonal pull-down strategy with quantitative mass spectrometry, SubMAPP allowed for the investigation of subcellular phosphoproteome dynamics, revealing the altered phosphorylation patterns of endoplasmic reticulum (ER) luminal proteins under ER stress. Finally, we further expanded the scope of the SubMAPP strategy to primary neuron culture and living mice.
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Project description:Phosphorylation of serine, threonine and tyrosine plays significant roles in cellular signal transduction and in modifying multiple protein functions. Phosphoproteins are coordinated and regulated by a network of kinases, phosphatases and phospho-binding proteins, which modify the phosphorylation states, recognize unique phosphopeptides, or target proteins for degradation. Detailed and complete information on the structure and dynamics of these networks is required to better understand fundamental mechanisms of cellular processes and diseases. High-throughput technologies have been developed to investigate phosphoproteomes in model organisms and human diseases. Among them, mass spectrometry (MS)-based technologies are the major platforms and have been widely applied, which has led to explosive growth of phosphoproteomic data in recent years. New bioinformatics tools are needed to analyze and make sense of these data. Moreover, most research has focused on individual phosphoproteins and kinases. To gain a more complete knowledge of cellular processes, systems biology approaches, including pathways and networks modeling, have to be applied to integrate all components of the phosphorylation machinery, including kinases, phosphatases, their substrates, and phospho-binding proteins. This review presents the latest developments of bioinformatics methods and attempts to apply systems biology to analyze phosphoproteomics data generated by MS-based technologies. Challenges and future directions in this field will be also discussed.
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Project description:Background:Ovarian cancer (OC) is the seventh most common cancer worldwide for women. However, there are no sufficient diagnostic methods and few treatment options available due to poor understanding of its pathogenic mechanisms. Methods:To comprehensively analyze the phosphoproteomic characterization for OC, we took advantage of a quantitative global phosphoproteomics method, titanium(IV) immobilized metal affinity chromatography (Ti4+-IMAC) coupled to nanoscale liquid chromatography and quadrupole time-of-flight tandem mass spectrometry (nanoLC/Q-TOF-MS/MS) on ovarian tissue samples obtained from five OC patients and five matched controls. Results:A total of 722 phosphorylated sites corresponding to 534 proteins were significantly different (fold change ? 2, p < 0.01) between OC patients and the controls. Among them, 83 transcription factors mainly consisted of transcription cofactors, zf-C2H2, and chromatin remodeling factors and 29 kinases were included. Further functional analysis suggested significantly biological processes were highly enriched and involved in the pathogenesis of OC, especially fructose and mannose metabolism. Moreover, the regulatory roles of modulated pathways, including MAPK, ErbB, and GnRH signaling pathways were also identified as critical processes involved in OC. The results here highlighted key phosphorylated proteins, particularly kinases, and the corresponding cancer-related metabolic and signal pathways that played important roles in the development of OC. Additionally, the expression levels of two kinases, phosphorylated CDK (T14) and phosphorylated PRKCQ (S695), were validated by Western blot analysis in the other group of ovarian tissue samples. Conclusion:Altogether, our data not only provided novel insights into the potential biomarkers and therapy options for OC but also extended our knowledge on its pathophysiological mechanism.
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