Global lipidomics reveals two plasma lipids as novel biomarkers for the detection of squamous cell lung cancer: A pilot study

Yu, Zhengping; Chen, Hankui; Zhu, Yong; Ai, Junmei; Li, Yan; Gu, Wei; Borgia, Jeffrey A.; Zhang, Jicai; Jiang, Bin; Chen, Wei; Deng, Youping

doi:10.3892/ol.2018.8740

Cited by 13 publications

(13 citation statements)

References 28 publications

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“…The quality or performance of the predicted models were evaluated by developed in previous studies [28] . In details, we used the receiver operating characteristic (ROC) curve, which was obtained by calculating the sensitivity and specificity of the test at every possible cut-off point, and plotting sensitivity (the proportion of true positive results) against 1-specificity (the proportion of false positive results) as described previously [29] . Briefly, the area under the ROC curve (AUC) was a reflection of how good the potential biomarker was at distinguishing NSCLC patients and healthy individuals.…”

Section: Methodsmentioning

confidence: 99%

A circular network of coregulated sphingolipids dictates lung cancer growth and progression

Meng

Zhao

et al. 2021

eBioMedicine

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Background Sphingolipid metabolism is among the top dysregulated pathways in non-small cell lung carcinomas (NSCLC). However, the molecular control of sphingolipid metabolic reprogramming in cancer progression remains unclear. Methods We first determined the correlation between sphingolipid metabolic gene expression and patient prognosis. We then carried out sphingolipidomics analysis of health individual and NSCLC patient sera as well as B3GNT5 and GAL3ST1 genetically perturbed NSCLC cell lines. We used these cell lines to perform tumorigenesis study to determine the cellular role of B3GNT5 and GAL3ST1 in cancer growth and progression. Findings The expression of B3GNT5 and GAL3ST1 among sphingolipid metabolic enzymes is most significantly associated with patient prognosis, whilst sphingolipidomics analysis of healthy individual and NSCLC patient sera identifies their metabolites, lacto/neolacto-series glycosphingolipid and sulfatide species, as potential biomarkers that were more effective than current clinical biomarkers for staging patients. Further network analysis of the sphingolipidomes reveals a circular network of coregulated sphingolipids, indicating that the lacto/neolacto-series glycosphingolipid/sulfatide balance functions as a checkpoint to determine sphingolipid metabolic reprograming during patient progression. Sphingolipidomics analysis of B3GNT5/GAL3ST1 genetically perturbed NSCLC cell lines confirms their key regulatory role in sphingolipid metabolism, while B3GNT5 and GAL3ST1 expression has an opposite role on tumorigenesis. Interpretation Our results provide new insights whereby B3GNT5 and GAL3ST1 differentially regulate sphingolipid metabolism in lung cancer growth and progression. Funding This work was supported by the Natural Science Foundation of China (81872142, 81920108028); Guangzhou Science and Technology Program (201904020008); Guangdong Science and Technology Department (2020A0505100029, 2019A1515011802, 2020A1515011280, 2020B1212060018, 2020B1212030004); China Postdoctoral Science Foundation (2019M650226, 2019M650227).

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Section: Methodsmentioning

confidence: 99%

A circular network of coregulated sphingolipids dictates lung cancer growth and progression

Meng

Zhao

et al. 2021

eBioMedicine

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“…With the advancement in mass spectrometric instruments over the last few decades, more studies are being conducted focusing on lipids and their role in various disease pathologies, examples of which include diabetes, 1,2 obesity, 3 cystic fibrosis, 4 and many types of cancers. [5][6][7][8][9] Due to the high content of lipids in the brain and central nervous system, Alzheimer's disease and many other neurological diseases such as multiple sclerosis, epilepsy, schizophrenia, and Parkinson's disease have been associated with faulty lipid metabolism. [10][11][12][13][14] Numerous lipidomics studies have established a correlation between altered lipid metabolism and Alzheimer's disease.…”

Section: Introductionmentioning

confidence: 99%

“…Lipidomics has been one of the most rapidly developing branches of science over the last decade due to the potential of linking lipids to different human health issues. With the advancement in mass spectrometric instruments over the last few decades, more studies are being conducted focusing on lipids and their role in various disease pathologies, examples of which include diabetes, 1,2 obesity, 3 cystic fibrosis, 4 and many types of cancers 5–9 . Due to the high content of lipids in the brain and central nervous system, Alzheimer's disease and many other neurological diseases such as multiple sclerosis, epilepsy, schizophrenia, and Parkinson's disease have been associated with faulty lipid metabolism 10–14 .…”

Section: Introductionmentioning

confidence: 99%

Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma

Khan

Codreanu

Goyal

et al. 2020

Rapid Comm Mass Spectrometry

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The Lipidyzer platform was recently updated on a SCIEX QTRAP 6500+ mass spectrometer and offers a targeted lipidomics assay including 1150 different lipids. We evaluated this targeted approach using human plasma samples and compared the results against a global untargeted lipidomics method using a highresolution Q Exactive HF Orbitrap mass spectrometer. Methods: Lipids from human plasma samples (N = 5) were extracted using a modified Bligh-Dyer approach. A global untargeted analysis was performed using a Thermo Orbitrap Q Exactive HF mass spectrometer, followed by data analysis using Progenesis QI software. Multiple reaction monitoring (MRM)-based targeted analysis was performed using a QTRAP 6500+ mass spectrometer, followed by data analysis using SCIEX OS software. The samples were injected on three separate days to assess reproducibility for both approaches. Results: Overall, 465 lipids were identified from 11 lipid classes in both approaches, of which 159 were similar between the methods, 168 lipids were unique to the MRM approach, and 138 lipids were unique to the untargeted approach. Phosphatidylcholine and phosphatidylethanolamine species were the most commonly identified using the untargeted approach, while triacylglycerol species were the most commonly identified using the targeted MRM approach. The targeted MRM approach had more consistent relative abundances across the three days than the untargeted approach. Overall, the coefficient of variation for inter-day comparisons across all lipid classes was 23% for the untargeted approach and 9% for the targeted MRM approach. Conclusions: The targeted MRM approach identified similar numbers of lipids to a conventional untargeted approach, but had better representation of 11 lipid classes commonly identified by both approaches. Based on the separation methods employed, the conventional untargeted approach could better detect phosphatidylcholine and sphingomyelin lipid classes. The targeted MRM approach had lower inter-day variability than the untargeted approach when tested using a small group of plasma samples. These studies highlight the advantages in using targeted MRM approaches for human plasma lipidomics analysis.

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“…Lipidomics was proposed as one of the important research fields of metabolomics in 2003 [ 10 ]. Its research interest mainly focuses on the relative changes between composition and concentration of lipids in cells and in biological fluids [ 11 ], which can play an important diagnostic role in various cancers, such as ovarian cancer [ 12 ], kidney cancer [ 13 ], esophageal squamous cell carcinoma [ 14 ] and lung cancer [ 15 , 16 ]. Furthermore, many studies have shown the correlation between dyslipidemia and BPH or prostate cancer [ 17 – 20 ].…”

Section: Introductionmentioning

confidence: 99%

Identification of plasma lipid species as promising diagnostic markers for prostate cancer

Chen

Zhu

Jijiwa

et al. 2020

BMC Med Inform Decis Mak

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Background Prostate cancer is a very common and highly fatal in men. Current non-invasive detection methods like serum biomarker are unsatisfactory. Biomarkers with high accuracy for diagnostic of prostate cancer are urgently needed. Many lipid species have been found related to various cancers. The purpose of our study is to explore the diagnostic value of lipids for prostate cancer. Results Using triple quadruple liquid chromatography electrospray ionization tandem mass spectrometry, we performed lipidomics profiling of 367 lipids on a total 114 plasma samples from 30 patients with prostate cancer, 38 patients with benign prostatic hyperplasia (BPH), and 46 male healthy controls to evaluate the lipids as potential biomarkers in the diagnosis of prostate cancer. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database was used to construct the potential mechanism pathway. After statistical analysis, five lipids were identified as a panel of potential biomarkers for the detection of prostate cancer between prostate cancer group and the BPH group; the sensitivity, specificity, and area under curve (AUC) of the combination of these five lipids were 73.3, 81.6%, and 0.800, respectively. We also identified another panel of five lipids in distinguishing between prostate cancer group and the control group with predictive values of sensitivity at 76.7%, specificity at 80.4%, and AUC at 0.836, respectively. The glycerophospholipid metabolism pathway of the selected lipids was considered as the target pathway. Conclusions Our study indicated that the identified plasma lipid biomarkers have potential in the diagnosis of prostate cancer.

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Global lipidomics reveals two plasma lipids as novel biomarkers for the detection of squamous cell lung cancer: A pilot study

Cited by 13 publications

References 28 publications

A circular network of coregulated sphingolipids dictates lung cancer growth and progression

A circular network of coregulated sphingolipids dictates lung cancer growth and progression

Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma

Identification of plasma lipid species as promising diagnostic markers for prostate cancer

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