Novel tissue markers in renal neoplasms using molar-scale quantitative proteomics via the total protein approach normalised with protein deglycase DJ-1 (PARK7)

IF 5.6 1区化学 Q1 CHEMISTRY, ANALYTICAL

Talanta Pub Date : 2025-07-08 DOI:10.1016/j.talanta.2025.128558

André Q. Figueiredo , Inês F. Domingos , Luís B. Carvalho , Jacek R. Wiśniewski , Dimitrios Korentzelos , Gabriela Quiroga-Garza , Rajiv Dhir , Carlos Lodeiro , José L. Capelo , Hugo M. Santos

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引用次数: 0

Abstract

Mass spectrometry-based proteomics enables large-scale protein quantification but is hindered by inter- and intra-laboratory variability, complicating data integration and biomarker discovery. This study aims to develop an optimised normalisation strategy using the ubiquitously expressed protein deglycase DJ-1 (PARK7) as an internal standard, combined with the Total Protein Approach (TPA) to improve data comparability in renal neoplasms proteomic datasets. We analysed the MS-based proteomics data of renal tissues from clear cell renal cell carcinoma (ccRCC, n = 7), papillary renal cell carcinoma (pRCC, n = 5), chromophobe renal cell carcinoma (chRCC, n = 5), renal oncocytoma (RO, n = 5), and control normal adjacent tissue (NAT, n = 5). Protein concentrations were calculated using the Total Protein Approach, and the data were normalised to PARK7 expression using a TPA reference value of 34.1 pmol/mg. TPA-PARK7 normalisation showed a trend towards reducing interquartile ranges. After normalisation, 95 % of biomarkers from non-normalised datasets remained statistically significant. Among these, 31 % of previously proposed candidate biomarkers retained their ability to distinguish between conditions, with histologically validated biomarkers (TUBB3, LAMP1, and HK1) showing improved differentiation. Additionally, 322 new statistically significant proteins were identified, and 18 new potential biomarkers for renal neoplasm were detected exclusively after TPA-PARK7 normalisation. Our findings demonstrate that using PARK7 as an internal standard, combined with the TPA, significantly enhances the statistical robustness and reliability of protein quantification in mass spectrometry-based proteomics. This normalisation strategy reduces interlaboratory variability, preserves biomarker differentiation capability, and enables novel biomarker discovery. By reducing variability, this method enhances cross-study comparability and supports the advancement of clinically relevant biomarker discovery.

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通过蛋白脱糖苷DJ-1 （PARK7）标准化的总蛋白方法，利用摩尔尺度定量蛋白质组学研究肾肿瘤中的新型组织标志物

基于质谱的蛋白质组学能够实现大规模的蛋白质定量，但受到实验室间和实验室内可变性、复杂的数据整合和生物标志物发现的阻碍。本研究旨在开发一种优化的规范化策略，使用无处不在表达的蛋白脱糖苷j -1 （PARK7）作为内部标准，结合总蛋白方法（TPA）来提高肾肿瘤蛋白质组学数据集的数据可比性。我们分析了透明细胞肾细胞癌（ccRCC, n = 7）、乳头状肾细胞癌（pRCC, n = 5）、厌色肾细胞癌（chRCC, n = 5）、肾嗜瘤细胞瘤（RO, n = 5）和对照正常邻近组织（NAT, n = 5）肾脏组织的ms - s蛋白质组学数据。使用总蛋白法计算蛋白浓度，并使用TPA参考值34.1 pmol/mg将数据归一化为PARK7表达。TPA-PARK7正态化呈减小四分位数范围的趋势。归一化后，95%来自非归一化数据集的生物标志物仍然具有统计学意义。其中，先前提出的候选生物标志物中有31%保留了区分疾病的能力，组织学验证的生物标志物（TUBB3， LAMP1和HK1）显示出更好的分化。此外，在TPA-PARK7正常化后，发现了322种新的具有统计学意义的蛋白，18种新的肾脏肿瘤潜在生物标志物。我们的研究结果表明，使用PARK7作为内标，结合TPA，显著提高了基于质谱的蛋白质组学中蛋白质定量的统计稳健性和可靠性。这种标准化策略减少了实验室间的可变性，保持了生物标志物的分化能力，并使新的生物标志物的发现成为可能。通过减少可变性，该方法增强了交叉研究的可比性，并支持临床相关生物标志物的发现。

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来源期刊

Talanta 化学-分析化学

CiteScore

12.30

自引率

4.90%

发文量

861

审稿时长

29 days

期刊介绍： Talanta provides a forum for the publication of original research papers, short communications, and critical reviews in all branches of pure and applied analytical chemistry. Papers are evaluated based on established guidelines, including the fundamental nature of the study, scientific novelty, substantial improvement or advantage over existing technology or methods, and demonstrated analytical applicability. Original research papers on fundamental studies, and on novel sensor and instrumentation developments, are encouraged. Novel or improved applications in areas such as clinical and biological chemistry, environmental analysis, geochemistry, materials science and engineering, and analytical platforms for omics development are welcome. Analytical performance of methods should be determined, including interference and matrix effects, and methods should be validated by comparison with a standard method, or analysis of a certified reference material. Simple spiking recoveries may not be sufficient. The developed method should especially comprise information on selectivity, sensitivity, detection limits, accuracy, and reliability. However, applying official validation or robustness studies to a routine method or technique does not necessarily constitute novelty. Proper statistical treatment of the data should be provided. Relevant literature should be cited, including related publications by the authors, and authors should discuss how their proposed methodology compares with previously reported methods.