期刊
JOURNAL OF PROTEOME RESEARCH
卷 20, 期 1, 页码 841-857出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c00663
关键词
lipidomics; clear cell renal cell carcinoma; biomarkers; ultraperformance liquid chromatography; mass spectrometry; machine learning; support vector machines; LASSO
资金
- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET, Argentina) [PUE 055]
- National Agency of Scientific and Technological Promotion (ANPCyT) [PRH-PICT-2015-0022, PICT-2018-02137]
- CONICET
- ANPCyT
- FOCEM-Mercosur
- Universidad Tecnologica Nacional in Argentina
- Universite de Technologie de Troyes in France
This lipid profiling study identified two discriminating lipid panels for detecting and differentiating ccRCC patients with high accuracy. The results suggest that the panels have the potential to be a powerful tool for early ccRCC diagnosis after validation in larger and diverse cohorts.
A discovery-based lipid profiling study of serum samples from a cohort that included patients with clear cell renal cell carcinoma (ccRCC) stages I, II, III, and IV (n = 112) and controls (n = 52) was performed using ultraperformance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry and machine learning techniques. Multivariate models based on support vector machines and the LASSO variable selection method yielded two discriminant lipid panels for ccRCC detection and early diagnosis. A 16-lipid panel allowed discriminating ccRCC patients from controls with 95.7% accuracy in a training set under cross-validation and 77.1% accuracy in an independent test set. A second model trained to discriminate early (I and II) from late (III and IV) stage ccRCC yielded a panel of 26 compounds that classified stage I patients from an independent test set with 82.1% accuracy. Thirteen species, including cholic acid, undecylenic acid, lauric acid, LPC(16:0/0:0), and PC(18:2/18:2), identified with level 1 exhibited significantly lower levels in samples from ccRCC patients compared to controls. Moreover, 3 alpha-hydroxy-5 alpha-androstan-17-one 3-sulfate, cis-5-dodecenoic acid, arachidonic acid, cis-13-docosenoic acid, PI(16:0/18:1), PC(16:0/18:2), and PC(O-16:0/20:4) contributed to discriminate early from late ccRCC stage patients. The results are auspicious for early ccRCC diagnosis after validation of the panels in larger and different cohorts.
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