Evidence map›Paper›PMID 39853354›Full record

ArticleAnalytical and bioanalytical chemistry2025

Efficient extraction via titanium organic frameworks facilitates in-depth profiling of urinary exosome metabolite fingerprints.

Yijie Chen, Man Zhang, Yu Qi, Yiwen Lin, Shasha Liu, Chunhui Deng, Shuai Jiang, Nianrong Sun

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Article in Analytical and bioanalytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yijie ChenDepartment of Gastroenterology and Hepatology, Zhongshan Hospital, Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China.
Man ZhangDepartment of Chemistry, Fudan University, Shanghai, 200433, China.
Yu QiDepartment of Urology, Zhongshan Hospital, Zhongshan Hospital Wusong Branch Fudan University, Shanghai, 200032, China.
Yiwen LinDepartment of Gastroenterology and Hepatology, Zhongshan Hospital, Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China.
Shasha LiuDepartment of Chemistry, Fudan University, Shanghai, 200433, China.
Chunhui DengDepartment of Gastroenterology and Hepatology, Zhongshan Hospital, Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China. chdeng@fudan.edu.cn.
Shuai JiangDepartment of Urology, Zhongshan Hospital, Zhongshan Hospital Wusong Branch Fudan University, Shanghai, 200032, China. jiang.shuai@zs-hospital.sh.cn.
Nianrong SunDepartment of Gastroenterology and Hepatology, Zhongshan Hospital, Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China. sunnianrong@fudan.edu.cn.

Funding

National Key R&D Program of China 2018YFA0507501
6 · The paper itself

Abstract

Urinary exosome metabolite analysis has demonstrated notable advantages in uncovering disease status, yet its potential in decoding the intricacies of clear cell renal cell carcinoma (ccRCC) remains untapped. To address this, a core-shell magnetic titanium organic framework was designed to capture urinary exosomes and assist laser desorption/ionization mass spectrometry (LDI MS) to decipher the exosomal metabolic profile of ccRCC, with high sensitivity, throughput, and speed. A total of 492 urinary exosome metabolite fingerprints (UEMFs) from 176 samples were extracted for exploring the differences between ccRCC and healthy individuals. Leveraging machine learning algorithms, the exosomal metabolic profile was disclosed, achieving accurate differentiation and prediction of ccRCC patients versus healthy individuals, with an accuracy exceeding 97.3%. Furthermore, an optimized algorithm panel comprising five key features demonstrated consistent and high diagnosing accuracy rates of over 94.0% both in the training and blind test sets for ccRCC, underscoring the remarkable effectiveness and superiority of this strategy in ccRCC detection. This study not only refines the LDI MS method for metabolite analysis in urinary exosomes but also introduces a promising technical approach for unraveling the mysteries of ccRCC.

Indexed as

Carcinoma, Renal CellExosomesKidney NeoplasmsMetal-Organic FrameworksTitaniumHumansMaleMetabolomicsSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationMetal-Organic FrameworksTitaniumDiagnosisExosome MetaboliteMass spectrometryMetal–organic framework

Identifiers

PMID39853354

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.