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PCAS:利用临床蛋白质组肿瘤分析联盟数据进行多维癌症研究的综合工具。

PCAS: An Integrated Tool for Multi-Dimensional Cancer Research Utilizing Clinical Proteomic Tumor Analysis Consortium Data.

机构信息

School of Public Health, Suzhou Medical College of Soochow University, Suzhou 215123, China.

出版信息

Int J Mol Sci. 2024 Jun 18;25(12):6690. doi: 10.3390/ijms25126690.

DOI:10.3390/ijms25126690
PMID:38928396
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11203781/
Abstract

Proteomics offers a robust method for quantifying proteins and elucidating their roles in cellular functions, surpassing the insights provided by transcriptomics. The Clinical Proteomic Tumor Analysis Consortium database, enriched with comprehensive cancer proteomics data including phosphorylation and ubiquitination profiles, alongside transcriptomics data from the Genomic Data Commons, allow for integrative molecular studies of cancer. The ProteoCancer Analysis Suite (PCAS), our newly developed R package and Shinyapp, leverages these resources to facilitate in-depth analyses of proteomics, phosphoproteomics, and transcriptomics, enhancing our understanding of the tumor microenvironment through features like immune infiltration and drug sensitivity analysis. This tool aids in identifying critical signaling pathways and therapeutic targets, particularly through its detailed phosphoproteomic analysis. To demonstrate the functionality of the PCAS, we conducted an analysis of GAPDH across multiple cancer types, revealing a significant upregulation of protein levels, which is consistent with its important biological and clinical significance in tumors, as indicated in our prior research. Further experiments were used to validate the findings performed using the tool. In conclusion, the PCAS is a powerful and valuable tool for conducting comprehensive proteomic analyses, significantly enhancing our ability to uncover oncogenic mechanisms and identify potential therapeutic targets in cancer research.

摘要

蛋白质组学提供了一种强大的方法来定量蛋白质,并阐明它们在细胞功能中的作用,超越了转录组学提供的见解。临床蛋白质组肿瘤分析联盟数据库,富含综合癌症蛋白质组学数据,包括磷酸化和泛素化谱,以及基因组数据公共数据库的转录组学数据,允许对癌症进行综合分子研究。我们新开发的 R 包和 Shinyapp——ProteoCancer 分析套件 (PCAS),利用这些资源促进蛋白质组学、磷酸化蛋白质组学和转录组学的深入分析,通过免疫浸润和药物敏感性分析等功能增强我们对肿瘤微环境的理解。该工具通过其详细的磷酸化蛋白质组学分析有助于确定关键的信号通路和治疗靶点。为了演示 PCAS 的功能,我们对多个癌症类型进行了 GAPDH 的分析,发现蛋白质水平显著上调,这与其在肿瘤中的重要生物学和临床意义一致,正如我们之前的研究所示。进一步的实验用于验证该工具执行的发现。总之,PCAS 是进行全面蛋白质组学分析的强大而有价值的工具,大大提高了我们在癌症研究中发现致癌机制和确定潜在治疗靶点的能力。

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本文引用的文献

1
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Comput Struct Biotechnol J. 2023 Aug 9;21:4056-4069. doi: 10.1016/j.csbj.2023.07.034. eCollection 2023.
2
Dissecting the role of protein phosphorylation: a chemical biology toolbox.解析蛋白质磷酸化的作用:化学生物学工具包。
Chem Soc Rev. 2022 Jul 4;51(13):5691-5730. doi: 10.1039/d1cs00991e.
3
Pathological implication of protein post-translational modifications in cancer.蛋白质翻译后修饰在癌症中的病理意义
LMO2在泛癌分析中作为一种潜在的免疫治疗标志物具有价值,并抑制透明细胞肾细胞癌的进展。
Transl Oncol. 2025 Jul;57:102409. doi: 10.1016/j.tranon.2025.102409. Epub 2025 May 10.
4
Increased expression of DNAJC7 promotes the progression of hepatocellular carcinoma by influencing the cell cycle and immune microenvironment.DNAJC7表达增加通过影响细胞周期和免疫微环境促进肝细胞癌进展。
J Cancer Res Clin Oncol. 2025 May 2;151(5):154. doi: 10.1007/s00432-025-06202-0.
5
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Front Immunol. 2024 Dec 19;15:1512445. doi: 10.3389/fimmu.2024.1512445. eCollection 2024.
6
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4
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7
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9
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