Lipidomic differentiation between human kidney tumors and surrounding normal tissues using HILIC-HPLC/ESI-MS and multivariate data analysis

Structural characterization of sphingomyelins from tissue using electron-induced dissociation

RATIONALE

Sphingomyelins (SMs) and resulting metabolic products serve important functional and cell signaling roles and can act as potential biomarkers and therapeutic targets in many pathological disorders. SMs each contain a sphingoid base, an amide-linked fatty acyl chain, and a phosphocholine headgroup. Despite these simple building blocks, variations and modifications of both the sphingoid base and the fatty acyl chain result in a diverse array of structurally complicated SM compounds. Conventional tandem mass spectrometry (MS/MS) using the collision-induced dissociation (CID) method only provides limited structural information, necessitating other tools to unravel the structural complexity of these lipids.

METHODS

We utilize electron-induced dissociation (EID) and sequential CID/EID approaches to elucidate detailed structural features of SMs. Integrating the CID/EID method into an imaging MS workflow enables accurate identification of SMs directly from kidney tissue.

RESULTS

The application of EID enables identification of SMs at the molecular species level, identifying the sphingosine base and the amide-linked fatty acyl chains. Furthermore, removal of the phosphocholine headgroup via CID followed by sequential EID in an MS3 analysis (CID/EID) enhances the structural information obtained. CID/EID provides diagnostic fragmentation patterns revealing the hydroxylation site and double bond position in both the sphingosine base and amide-linked fatty acyl chains.

CONCLUSIONS

Detailed structural information of SMs from synthetic standards and biological tissue samples is obtained using an alternative electron-based dissociation method. Accurate characterization of SMs promises to better inform studies of tissue biochemistry, lipid metabolism, and molecular pathology.

Is Lipid Metabolism of Value in Cancer Research and Treatment? Part I- Lipid Metabolism in Cancer

For either healthy or diseased organisms, lipids are key components for cellular membranes; they play important roles in numerous cellular processes including cell growth, proliferation, differentiation, energy storage and signaling. Exercise and disease development are examples of cellular environment alterations which produce changes in these networks. There are indications that alterations in lipid metabolism contribute to the development and progression of a variety of cancers. Measuring such alterations and understanding the pathways involved is critical to fully understand cellular metabolism. The demands for this information have led to the emergence of lipidomics, which enables the large-scale study of lipids using mass spectrometry (MS) techniques. Mass spectrometry has been widely used in lipidomics and allows us to analyze detailed lipid profiles of cancers. In this article, we discuss emerging strategies for lipidomics by mass spectrometry; targeted, as opposed to global, lipid analysis provides an exciting new alternative method. Additionally, we provide an introduction to lipidomics, lipid categories and their major biological functions, along with lipidomics studies by mass spectrometry in cancer samples. Further, we summarize the importance of lipid metabolism in oncology and tumor microenvironment, some of the challenges for lipodomics, and the potential for targeted approaches for screening pharmaceutical candidates to improve the therapeutic efficacy of treatment in cancer patients.

Development of a targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry based lipidomics platform applied to a coronavirus disease severity study

The importance of lipids seen in studies of metabolism, cancer, the recent COVID-19 pandemic and other diseases has brought the field of lipidomics to the forefront of clinical research. Quantitative and comprehensive analysis is required to understand biological interactions among lipid species. However, lipidomic analysis is often challenging due to the various compositional structures, diverse physicochemical properties, and wide dynamic range of concentrations of lipids in biological systems. To study the comprehensive lipidome, a hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS)-based screening method with 1200 lipid features across 19 (sub)classes, including both nonpolar and polar lipids, has been developed. HILIC-MS/MS was selected due to its class separation property and fatty acyl chain level information. 3D models of class chromatographic retention behavior were established and evaluations of cross-class and within-class interferences were performed to avoid over-reporting these features. This targeted HILIC-MS/MS method was fully validated, with acceptable analytical parameters in terms of linearity, precision, reproducibility, and recovery. The accurate quantitation of 608 lipid species in the SRM 1950 NIST plasma was achieved using multi-internal standards per class and post-hoc correction, extending current databases by providing lipid concentrations resolved at fatty acyl chain level. The overall correlation coefficients (R2) of measured concentrations with values from literature range from 0.64 to 0.84. The applicability of the developed targeted lipidomics method was demonstrated by discovering 520 differential lipid features related to COVID-19 severity. This high coverage and targeted approach will aid in future investigations of the lipidome in various disease contexts.

Use of Multivariate Analysis to Unravel the Differences between Two Chamomile Varieties and Their Anticancer and Antioxidant Activities

BACKGROUND

Plants from the Asteraceae family were commonly used to treat various diseases. The metabolomic profile of this family consisted of bioactive flavonoids and other phenolics. Chamomile is a member of the Asteraceae family. Jordanian and European chamomile are two varieties of Matricaria chamomilla (German chamomile), which were grown under different environmental conditions, were studied. Many examples of plant varieties with significant distinction in the secondary metabolite they afford have been described in the literature. Multivariate statistical analysis was employed to measure the depth of this variation in two chamomile varieties.

METHODS

From both types, crude extracts were prepared using solvents of different polarities and tested for their biological activity. The semipolar fraction of the European variety showed anticancer and antioxidant activity. Meanwhile, the semipolar fraction of the Jordanian type exhibited only antioxidant activity. Both extracts were fractionated, and then the biological activity was again assayed.

RESULTS

European and Jordanian chamomile fractions produced dicaffeoylquinic acid isomers exhibiting antioxidant capability. Additionally, Z-glucoferulic acid was produced from the European chamomile, demonstrating antioxidant activity. The European samples afforded two major compounds, chrysosplenetin and apigenin, that displayed anticancer activity.

CONCLUSIONS

Different environmental conditions between Jordanian and European chamomile affected the type of isolated compounds. Structure elucidation was performed with HPLC-MS coupled with dereplication techniques and 2D NMR experiments.

Characterization and discrimination of volatile organic compounds and lipid profiles of truffles under different treatments by UHPLC-QE Orbitrap/MS/MS and P&T-GC-MS

The lipid profiles of the truffles with different treatments were determined by ultra-high-performance liquid chromatography-Quadrupole-Exactive Orbitrap mass spectrometry (UHPLC-QE Orbitrap/MS/MS) and the volatile organic compounds (VOCs) were identified by purge-and-trap-gas chromatography-mass spectrometry (P&T-GC-MS). A total of 37 lipid molecular species and 28 VOCs were tentatively identified. Lysophophatidylcholine (LPC), triacylglycerol (TG) and sphingomyelin (SM) in heat-drying truffles, phosphatidic acid (PA) in freeze-drying and fresh truffles might be the key lipids that bound VOCs. Furthermore, the correlation between lipids and VOCs were analyzed by 19 differential lipids and 7 VOCs. The findings indicated that TG 18:2/18:2/18:2 and Cardiolipin (CL) 16:0/16:0/18:2/18:2 might be the key lipid molecule species for the formation of 2-methoxyphenol. The study helps to understand the effect of different treatments on the lipid profiles and provides the mechanistic insights to the relationship between the lipids and VOCs of truffles.

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

Application of hybrid surface technology for improving sensitivity and peak shape of phosphorylated lipids such as phosphatidic acid and phosphatidylserine

The use of hybrid surface technology (HST), applied to the metal surfaces of an ACQUITY™ UPLC™ system and column, designed to mitigate the chelation, poor peak shape and analyte loss seen with acidic phospholipids was investigated. Compared to a conventional system significant improvements in both sensitivity, recovery and peak shape were obtained following UPLC on a CSH C18 column when the HST was used for the analysis of lysophosphatidic acid (LPA), phosphatidic acid (PA), lysophosphatidylserine (LPS), phosphatidylserine (PS), phosphatidylinositol-monophosphates (PIP), ceramide phosphate (CerP) and sphingoid base phosphate (SPBP). The benefits in chromatographic performance provided by the HST were seen particularly at low concentrations of these analytes. The HST system and column reduced peak tailing by 65-80% and peak width by 70-86% for LPA and PA. Moreover, increased signal intensities of up to 12.7 times were observed for LPA with the HST approach compared to the equivalent untreated LC system and column. The application of this methodology to the analysis of chicken egg PA and brain porcine PS extracts were accompanied by similar improvements in data quality.

Lipidomic profiling of human serum enables detection of pancreatic cancer

Pancreatic cancer has the worst prognosis among all cancers. Cancer screening of body fluids may improve the survival time prognosis of patients, who are often diagnosed too late at an incurable stage. Several studies report the dysregulation of lipid metabolism in tumor cells, suggesting that changes in the blood lipidome may accompany tumor growth. Here we show that the comprehensive mass spectrometric determination of a wide range of serum lipids reveals statistically significant differences between pancreatic cancer patients and healthy controls, as visualized by multivariate data analysis. Three phases of biomarker discovery research (discovery, qualification, and verification) are applied for 830 samples in total, which shows the dysregulation of some very long chain sphingomyelins, ceramides, and (lyso)phosphatidylcholines. The sensitivity and specificity to diagnose pancreatic cancer are over 90%, which outperforms CA 19-9, especially at an early stage, and is comparable to established diagnostic imaging methods. Furthermore, selected lipid species indicate a potential as prognostic biomarkers.

Non-targeted Lipidomics Using a Robust and Reproducible Lipid Separation Using UPLC with Charged Surface Hybrid Technology and High-Resolution Mass Spectrometry

Lipids play an important role in the energy storage, cellular signaling, and pathophysiology of diseases such as cancer, neurodegenerative diseases, infections, and diabetes. Due to high importance of diverse lipid classes in human health and disease, manipulating lipid abundance and composition is an important target for metabolic engineering. The extreme structural diversity of lipids in real biological samples is challenging for analytical techniques due to large difference in physicochemical properties of individual lipid species. This chapter describes lipidomic analysis of large sample sets requiring reliable and robust methodology. Rapid and robust methods facilitate the support of longitudinal studies allowing the transfer of methodology between laboratories. We describe a high-throughput reversed-phase LC-MS methodology using Ultra Performance Liquid Chromatography (UPLC^®) with charged surface hybrid technology and accurate mass detection for high-throughput non-targeted lipidomics. The methodology showed excellent specificity, robustness, and reproducibility for over 100 LC-MS injections.

The Colorectal Cancer Lipidome: Identification of a Robust Tumor-Specific Lipid Species Signature

OBJECTIVE

Lipidomic changes were causally linked to metabolic diseases, but the scenario for colorectal cancer (CRC) is less clear. We investigated the CRC lipidome for putative tumor-specific alterations through analysis of 3 independent retrospective patient cohorts from 2 clinical centers, to derive a clinically useful signature.

DESIGN

Quantitative comprehensive lipidomic analysis was performed using direct infusion electrospray ionization coupled with tandem mass spectrometry (ESI-MS/MS) and high-resolution mass spectrometry (HR-MS) on matched nondiseased mucosa and tumor tissue in a discovery cohort (n = 106). Results were validated in 2 independent cohorts (n = 28, and n = 20), associated with genomic and clinical data, and lipidomic data from a genetic mouse tumor model (Apc1638N).

RESULTS

Significant differences were found between tumor and normal tissue for glycero-, glycerophospho-, and sphingolipids in the discovery cohort. Comparison to the validation collectives unveiled that glycerophospholipids showed high interpatient variation and were strongly affected by preanalytical conditions, whereas glycero- and sphingolipids appeared more robust. Signatures of sphingomyelin and triacylglycerol (TG) species significantly differentiated cancerous from nondiseased tissue in both validation studies. Moreover, lipogenic enzymes were significantly up-regulated in CRC, and FASN gene expression was prognostically detrimental. The TG profile was significantly associated with postoperative disease-free survival and lymphovascular invasion, and was essentially conserved in murine digestive cancer, but not associated with microsatellite status, KRAS or BRAF mutations, or T-cell infiltration.

CONCLUSION

Analysis of the CRC lipidome revealed a robust TG-species signature with prognostic potential. A better understanding of the cancer-associated glycerolipid and sphingolipid metabolism may lead to novel therapeutic strategies.

Retention dependences support highly confident identification of lipid species in human plasma by reversed-phase UHPLC/MS

Reversed-phase ultrahigh-performance liquid chromatography-mass spectrometry (RP-UHPLC/MS) method was developed with the aim to unambiguously identify a large number of lipid species from multiple lipid classes in human plasma. The optimized RP-UHPLC/MS method employed the C18 column with sub-2-μm particles with the total run time of 25 min. The chromatographic resolution was investigated with 42 standards from 18 lipid classes. The UHPLC system was coupled to high-resolution quadrupole-time-of-flight (QTOF) mass analyzer using electrospray ionization (ESI) measuring full-scan and tandem mass spectra (MS/MS) in positive- and negative-ion modes with high mass accuracy. Our identification approach was based on m/z values measured with mass accuracy within 5 ppm tolerance in the full-scan mode, characteristic fragment ions in MS/MS, and regularity in chromatographic retention dependences for individual lipid species, which provides the highest level of confidence for reported identifications of lipid species including regioisomeric and other isobaric forms. The graphs of dependences of retention times on the carbon number or on the number of double bond(s) in fatty acyl chains were constructed to support the identification of lipid species in homologous lipid series. Our list of identified lipid species is also compared with previous publications investigating human blood samples by various MS-based approaches. In total, we have reported more than 500 lipid species representing 26 polar and nonpolar lipid classes detected in NIST Standard reference material 1950 human plasma.

Coupled Mass-Spectrometry-Based Lipidomics Machine Learning Approach for Early Detection of Clear Cell Renal Cell Carcinoma

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, 3α-hydroxy-5α-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.

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

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.

Nuclear magnetic resonance and surface-assisted laser desorption/ionization mass spectrometry-based serum metabolomics of kidney cancer

Kidney cancer is one of the most frequently diagnosed and the most lethal urinary cancer. Despite all the efforts made, no serum-specific biomarker is currently used in the clinical management of patients with this tumor. In this study, comprehensive high-resolution proton nuclear magnetic resonance spectroscopy (1H NMR) and silver-109 nanoparticle-enhanced steel target laser desorption/ionization mass spectrometry (109AgNPET LDI MS) approaches were conducted, in conjunction with multivariate data analysis, to discriminate the global serum metabolic profiles of kidney cancer (n = 50) and healthy volunteers (n = 49). Eight potential biomarkers have been identified using 1H NMR metabolomics and nine mass spectral features which differed significantly (p < 0.05) between kidney cancer patients and healthy volunteers, as observed by LDI MS. A partial least squares discriminant analysis (OPLS-DA) model generated from metabolic profiles obtained by both analytical approaches could robustly discriminate normal from cancerous samples (Q2 > 0.7), area under the receiver operative characteristic curve (ROC) AUC > 0.96. Compared with healthy human serum, kidney cancer serum had higher levels of glucose and lower levels of choline, glycerol, glycine, lactate, leucine, myo-inositol, and 1-methylhistidine. Analysis of differences between these metabolite levels in patients with different types and grades of kidney cancer was undertaken. Our results, derived from the combination of LDI MS and 1H NMR methods, suggest that serum biomarkers identified herein appeared to have great potential for use in clinical prognosis and/or diagnosis of kidney cancer. Graphical abstract.

Mass spectrometry-based lipidomics of oral squamous cell carcinoma tissue reveals aberrant cholesterol and glycerophospholipid metabolism - A Pilot study

Lipid metabolic reprogramming is one hallmark of cancer. Lipid metabolism is regulated by numerous enzymes, many of which are targeted by several drugs on the market. We aimed to characterize the lipid alterations in oral squamous cell carcinoma (OSCC) as a basis for understanding its lipid metabolism, thus identifying potential therapeutic targets. We compared lipid species, classes, and glycerophospholipid (GPL) fatty acid species between paired tumor tissue and healthy oral tongue mucosa samples from 10 OSCC patients using a QExactive mass spectrometer. After filtering the 1370 lipid species identified, we analyzed 349 species: 71 were significantly increased in OSCC. The GPL metabolism pathway was most represented by the lipids differing in OSCC (P = .005). Cholesterol and the GPLs phosphatidylcholines, phosphatidylethanolamines, and phosphatidylinositols were most significantly increased in OSCC tissue (FC 1.8, 2.0, 2.1, and 2.3 and, P = .003, P = .005, P = .002, P = .007). In conclusion, we have demonstrated a shift in the lipid metabolism in these OSCC samples by characterizing the detailed landscape. Predominantly, cholesterol and GPL metabolism were altered, suggesting that interactions with sterol regulatory binding proteins may be involved. The FA composition changes of the GPLs suggest increased de novo lipogenesis.

LC-MS-Based Plasma Metabolomics and Lipidomics Analyses for Differential Diagnosis of Bladder Cancer and Renal Cell Carcinoma

Bladder cancer (BC) and Renal cell carcinoma(RCC) are the two most frequent genitourinary cancers in China. In this study, a comprehensive liquid chromatography-mass spectrometry (LC-MS) based method, which utilizes both plasma metabolomics and lipidomics platform, has been carried out to discriminate the global plasma profiles of 64 patients with BC, 74 patients with RCC, and 141 healthy controls. Apparent separation was observed between cancer (BC and RCC) plasma samples and controls. The area under the receiving operator characteristic curve (AUC) was 0.985 and 0.993 by plasma metabolomics and lipidomics, respectively (external validation group: AUC was 0.944 and 0.976, respectively). Combined plasma metabolomics and lipidomics showed good predictive ability with an AUC of 1 (external validation group: AUC = 0.99). Then, separation was observed between the BC and RCC samples. The AUC was 0.862, 0.853 and 0.939, respectively, by plasma metabolomics, lipidomics and combined metabolomics and lipidomics (external validation group: AUC was 0.802, 0.898, and 0.942, respectively). Furthermore, we also found eight metabolites that showed good predictive ability for BC, RCC and control discrimination. This study indicated that plasma metabolomics and lipidomics may be effective for BC, RCC and control discrimination, and combined plasma metabolomics and lipidomics showed better predictive performance. This study would provide a reference for BC and RCC biomarker discovery, not only for early detection and screening, but also for differential diagnosis.

Validation of lipidomic analysis of human plasma and serum by supercritical fluid chromatography-mass spectrometry and hydrophilic interaction liquid chromatography-mass spectrometry

Ultrahigh-performance supercritical fluid chromatography-mass spectrometry (UHPSFC/MS) has a great potential for the high-throughput lipidomic quantitation of biological samples; therefore, the full optimization and method validation of UHPSFC/MS is compared here with ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC/MS) in hydrophilic interaction liquid chromatography (HILIC) mode as the second powerful technique for the lipid class separation. First, the performance of six common extraction protocols is investigated, where the Folch procedure yields the best results with regard to recovery rate, matrix effect, and precision. Then, the full optimization and analytical validation for eight lipid classes using UHPSFC/MS and HILIC-UHPLC/MS methods are performed for the same sample set and applied for the lipidomic characterization of pooled samples of human plasma, human serum, and NIST SRM 1950 human plasma. The choice of appropriate internal standards (IS) for individual lipid classes has a key importance for reliable quantitative workflows illustrated by the selectivity while validation and the calculation of the quantitation error using multiple internal standards per lipid class. Validation results confirm the applicability of both methods, but UHPSFC/MS provides some distinct advantages, such as the successful separation of both non-polar and polar lipid classes unlike to HILIC-UHPLC/MS, shorter total run times (8 vs. 10.5 min), and slightly higher robustness. Various types of correlations between methods (UHPSFC/MS and HILIC-UHPLC/MS), biological material (plasma and serum), IS (laboratory and commercially mixtures), and literature data on the standard reference material show the intra- and inter-laboratory comparison in the quantitation of lipid species from eight lipid classes, the concentration differences in serum and plasma as well as the applicability of non-commercially available internal standard mixtures for lipid quantitation.

Single cell study of adipose tissue mediated lipid droplet formation and biochemical alterations in breast cancer cells

Obesity is a known risk factor for breast cancer and a negative prognostic factor for cancer recurrence and survival. Several studies demonstrated that aggressive breast tumor cells contain higher numbers of intracellular lipid droplets (LDs). Here we applied simultaneous visualization, identification and quantification of the lipid accumulation in lipid droplets (LDs) of aggressive, human triple-negative MDA-MB-231 breast cancer cells treated with adipose tissue-conditioned medium (ACM) derived from overweight and obese patients. In addition to Oil Red O and AdipoRed fluorescent staining, label-free confocal Raman microspectroscopy (CRM) has been applied. CRM enables imaging of cell compartments as well as quantification and monitoring of specific biomolecules and metabolic processes on a single cell level. Interestingly, breast cancer cells incubated with ACM showed a significantly higher number of intracellular LDs. Cultivation of breast tumor cells with ACM of obese patients induced the formation of LDs with a 20-fold higher lipid concentration than cultivation with basal medium. This is in line with the significantly higher levels of NEFAs (non-esterified fatty acids) detected in the ACM obtained from obese patient compared to ACM obtained from overweight patients or basal medium. Further, by principal component analysis, we identified a significant increase in unsaturation, esterification and lipid to protein ratio in LDs in breast cancer cells incubated with ACM. CRM analyses might function as a valuable diagnostic tool to identify metabolic alterations in biological samples which in turn could provide more detailed insights in the pathogenesis of breast cancer in association with obesity.

Serum Lipidomic Profiling in Breast Cancer to Identify Screening, Diagnostic, and Prognostic Biomarkers

Breast cancer is the major mortality cause of women worldwide. In the course of management of breast cancer, the identification of a biomarker is important in enhancing our knowledge on cancer pathology, predicting the response to treatment, and selecting the patients who are more favorable to receive certain treatments. These biomarkers have a prognostic value. In addition to traditional breast cancer prognosis factors such as the tumor size and grade, the axillary lymph node micrometastasis, and biomarkers such as HER2/neu, newly discovered biomarkers have been discovered. Some of these factors are genetic signature in tissue or in peripheral blood. Lipid profil, a simple and accessible biological examination, has been a novel path on the prediction of breast cancer risk of occurrence and recurrence in many studies. The main goal of our review is to evaluate lipid profile and breast cancer risk with an emphasis on the prognosis value of lipid profiles in breast cancer patient management.

Dietary Bioactive Fatty Acids as Modulators of Immune Function: Implications on Human Health

Diet is major modifiable risk factor for cardiovascular disease that can influence the immune status of the individual and contribute to persistent low-grade inflammation. In recent years, there has been an increased appreciation of the role of polyunsaturated fatty acids (PUFA) in improving immune function and reduction of systemic inflammation via the modulation of pattern recognition receptors (PRR) on immune cells. Extensive research on the use of bioactive lipids such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) and their metabolites have illustrated the importance of these pro-resolving lipid mediators in modulating signaling through PRRs. While their mechanism of action, bioavailability in the blood, and their efficacy for clinical use forms an active area of research, they are found widely administered as marine animal-based supplements like fish oil and krill oil to promote health. The focus of this review will be to discuss the effect of these bioactive fatty acids and their metabolites on immune cells and the resulting inflammatory response, with a brief discussion about modern methods for their analysis using mass spectrometry-based methods.

LC-MS based metabolomic profiling for renal cell carcinoma histologic subtypes

Renal cell carcinomas (RCC) are classified according to their histological features. Accurate classification of RCC and comprehensive understanding of their metabolic dysregulation are of critical importance. Here we investigate the use of metabolomic analyses to classify the main RCC subtypes and to describe the metabolic variation for each subtype. To this end, we performed metabolomic profiling of 65 RCC frozen samples (40 clear cell, 14 papillary and 11 chromophobe) using liquid chromatography-mass spectrometry. OPLS-DA multivariate analysis based on metabolomic data showed clear discrimination of all three main subtypes of RCC (R² = 75.0%, Q² = 59.7%). The prognostic performance was evaluated using an independent cohort and showed an AUROC of 0.924, 0.991 and 1 for clear cell, papillary and chromophobe RCC, respectively. Further pathway analysis using the 21 top metabolites showed significant differences in amino acid and fatty acid metabolism between three RCC subtypes. In conclusion, this study shows that metabolomic profiling could serve as a tool that is complementary to histology for RCC subtype classification. An overview of metabolic dysregulation in RCC subtypes was established giving new insights into the understanding of their clinical behaviour and for the development of targeted therapeutic strategies.

Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression

Aberrant lipid accumulation and marked changes in cellular lipid profiles are related to breast cancer metabolism and disease progression. In vitro, these phenomena are primarily studied using cells cultured in monolayers (2D). Here, we employ multicellular spheroids, generated using the MCF10A cell line series of increasing malignancy potential, to better recapitulate the 3D microenvironmental conditions that cells experience in vivo. Breast cancer cell lipid compositions were assessed in 2D and 3D culture models as a function of malignancy using liquid chromatography coupled with mass spectrometry. Further, the spatial distribution of lipids was examined using Raman chemical imaging and lipid staining. We show that with changes in the cellular microenvironment when moving from 2D to 3D cell cultures, total lipid amounts decrease significantly, while the ratio of acylglycerols to membrane lipids increases. This ratio increase could be associated with the formation of large lipid droplets (>10 μm) that are spatially evident throughout the spheroids but absent in 2D cultures. Additionally, we found a significant difference in lipid profiles between the more and less malignant spheroids, including changes that support de novo sphingolipid production and a reduction in ether-linked lipid fractions in the invasive spheroids. These differences in lipid profiles as a function of cell malignancy and microenvironment highlight the importance of coupled spatial and lipidomic studies to better understand the connections between lipid metabolism and cancer.

Lipidomic Analysis of Cancer Cell and Tumor Tissues

Due to their role in cellular structure, energetics, and signaling, characterization of changes in cellular and extracellular lipid composition is of key importance to understand cancer biology. In addition, several mass spectrometry-based profiling as well as imaging studies have indicated that lipid molecules may be useful to augment existing biochemical and histopathological methods for diagnosis, staging, and prognosis of cancer. Therefore, analysis of lipidomic changes associated with cancer cells and tumor tissues can be useful for both fundamental and translational studies. Here, we provide a high-throughput single-extraction-based method that can be used for simultaneous lipidomic and metabolomic analysis of cancer cells or healthy or tumor tissue samples. In this chapter, a modified Bligh-Dyer method is described for extraction of lipids followed by analysis of fatty acid composition by gas chromatography-mass spectrometry (GC-MS) or untargeted lipidomics using electrospray ionization mass spectrometry (ESIMS) coupled with reverse-phase (RP) ultraperformance liquid chromatography (UPLC) followed by multivariate data analysis to identify features of interest.

HILIC/ESI-MS determination of gangliosides and other polar lipid classes in renal cell carcinoma and surrounding normal tissues

Negative-ion hydrophilic liquid chromatography-electrospray ionization mass spectrometry (HILIC/ESI-MS) method has been optimized for the quantitative analysis of ganglioside (GM3) and other polar lipid classes, such as sulfohexosylceramides (SulfoHexCer), sulfodihexosylceramides (SulfoHex2Cer), phosphatidylglycerols (PG), phosphatidylinositols (PI), lysophosphatidylinositols (LPI), and phosphatidylserines (PS). The method is fully validated for the quantitation of the studied lipids in kidney normal and tumor tissues of renal cell carcinoma (RCC) patients based on the lipid class separation and the coelution of lipid class internal standard with the species from the same lipid class. The raw data are semi-automatically processed using our software LipidQuant and statistically evaluated using multivariate data analysis (MDA) methods, which allows the complete differentiation of both groups with 100% specificity and sensitivity. In total, 21 GM3, 28 SulfoHexCer, 26 SulfoHex2Cer, 10 PG, 19 PI, 4 LPI, and 7 PS are determined in the aqueous phase of lipidomic extracts from kidney tumor tissue samples and surrounding normal tissue samples of 20 RCC patients. S-plots allow the identification of most upregulated (PI 40:5, PI 40:4, GM3 34:1, and GM3 42:2) and most downregulated (PI 32:0, PI 34:0, PS 36:4, and LPI 16:0) lipids, which are primarily responsible for the differentiation of tumor and normal groups. Another confirmation of most dysregulated lipids is performed by the calculation of fold changes together with T and p values to highlight their statistical significance. The comparison of HILIC/ESI-MS data and matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) data confirms that lipid dysregulation patterns are similar for both methods. Graphical abstract ᅟ.

Metabolomic study of human tissue and urine in clear cell renal carcinoma by LC-HRMS and PLS-DA

Renal cell carcinoma (RCC) is the most prevalent and lethal malignancy of the kidney. Despite all the efforts made, no tissue biomarker is currently used in the clinical management of patients with kidney cancer. A search for possible biomarkers in urine for clear cell renal cell carcinoma (ccRCC) has been conducted. Non-targeted metabolomic analyses were performed on paired samples of surgically removed renal cancer and normal tissue, as well as on urine samples. Extracts were analyzed by liquid chromatography/high-resolution mass spectrometry (LC-HRMS). Hydroxybutyrylcarnitine, decanoylcarnitine, propanoylcarnitine, carnitine, dodecanoylcarnitine, and norepinephrine sulfate were found in much higher concentrations in both cancer tissues (compared with the paired normal tissue) and in urine of cancer patients (compared with control urine). In contrast, riboflavin and acetylaspartylglutamate (NAAG) were present at significantly higher concentrations both in normal kidney tissue as well as in urine samples of healthy persons. This preliminary study resulted in the identification of several compounds that may be considered potential clear cell renal carcinoma biomarkers. Graphical abstract PLS-DA plot based on LC-MS data for normal and cancer human tissue samples. The aim of this work was the identification of up- and downregulated compounds that could potentially serve as renal cancer biomarkers.

Phospholipids as cancer biomarkers: Mass spectrometry-based analysis

Lipids, particularly phospholipids (PLs), are key components of cellular membrane. PLs play important and diverse roles in cells such as chemical-energy storage, cellular signaling, cell membranes, and cell-cell interactions in tissues. All these cellular processes are pertinent to cells that undergo transformation, cancer progression, and metastasis. Thus, there is a strong possibility that some classes of PLs are expected to present in cancer cells and tissues in cellular physiology. The mass spectrometric soft-ionization techniques, electrospray ionization (ESI), and matrix-assisted laser desorption/ionization (MALDI) are well-established in the proteomics field, have been used for lipidomic analysis in cancer research. This review focused on the applications of mass spectrometry (MS) mainly on ESI-MS and MALDI-MS in the structural characterization, molecular composition and key roles of various PLs present in cancer cells, tissues, blood, and urine, and on their importance for cancer-related problems as well as challenges for development of novel PL-based biomarkers. The profiling of PLs helps to rationalize their functions in biological systems, and will also provide diagnostic information to elucidate mechanisms behind the control of cancer, diabetes, and neurodegenerative diseases. The investigation of cellular PLs with MS methods suggests new insights on various cancer diseases and clinical applications in the drug discovery and development of biomarkers for various PL-related different cancer diseases. PL profiling in tissues, cells and body fluids also reflect the general condition of the whole organism and can indicate the existence of cancer and other diseases. PL profiling with MS opens new prospects to assess alterations of PLs in cancer, screening specific biomarkers and provide a basis for the development of novel therapeutic strategies. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:107-138, 2018.

Lipidomic Analysis: From Archaea to Mammals

Lipids are among the most important organic compounds found in all living cells, from primitive archaebacteria to flowering plants or mammalian cells. They form part of cell walls and constitute cell storage material. Their biosynthesis and metabolism play key roles in faraway topics such as biofuel production (third-generation biofuels produced by microorganisms, e.g. algae) and human diseases such as adrenoleukodystrophy, Zellweger syndrome, or Refsum disease. Current lipidomic analysis requires fast and accurate processing of samples and especially their characterization. Because the number of possible lipids and, more specifically, molecular species of lipids is of the order of hundreds to thousands, it is necessary to process huge amounts of data in a short time. There are two basic approaches to lipidomic analysis: shotgun and liquid chromatography-mass spectometry. Both methods have their pros and cons. This review deals with lipidomics not according to the type of ionization or the lipid classes analyzed but according to the types of samples (organisms) under study. Thus, it is divided into lipidomic analysis of archaebacteria, bacteria, yeast, fungi, algae, plants, and animals.

Plasma lipidomics profiling identified lipid biomarkers in distinguishing early-stage breast cancer from benign lesions

BACKGROUND

Breast cancer is very common and highly fatal in women. Current non-invasive detection methods like mammograms are unsatisfactory. Lipidomics, a promising detection method, may serve as a novel prognostic approach for breast cancer in high-risk patients.

RESULTS

According the predictive model, the combination of 15 lipid species had high diagnostic value. In the training set, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the combination of these 15 lipid species were 83.3%, 92.7%, 89.7%, and 87.9%, respectively. The AUC in the training set was 0.926 (95% CI 0.869-0.982). Similar results were found in the validation set, with the sensitivity, specificity, PPV and NPV at 81.0%, 94.5%, 91.9%, and 86.7%, respectively. The AUC was 0.938 (95% CI 0.889-0.986) in the validation set.

METHODS

Using triple quadrupole liquid chromatography electrospray ionization tandem mass spectrometry, this study was to detect global lipid profiling of a total of 194 plasma samples from 84 patients with early-stage breast cancer (stage 0-II) and 110 patients with benign breast disease included in a training set and a validation set. A binary logistic regression was used to build a predictive model for evaluating the lipid species as potential biomarkers in the diagnosis of breast cancer.

CONCLUSIONS

The combination of these 15 lipid species as a panel could be used as plasma biomarkers for the diagnosis of breast cancer.

Plasma lipid profiling and diagnostic biomarkers for oral squamous cell carcinoma

Biological requirements for tumor cell proliferation include the sustained increase of structural, energetic, signal transduction and biosynthetic precursors. Because lipids participate in membrane construction, energy storage, and cell signaling. We hypothesized that the differences in lipids between malignant carcinoma and normal controls could be reflected in the bio-fluids. A total of 100 pre-operative plasma samples were collected from 50 oral squamous cell carcinoma (OSCC), 50 normal patients and characterize by lipid profiling using ultra performance liquid chromatography/electro spray ionization mass spectrometry (UPLC-MS). The lipid profiles of the OSCC and control samples as well as the different stages were compared. Differentially expressed lipids were categorized as glycerophospholipids and sphingolipids. All glycerophospholipids were decreased, especially phosphatidylcholine and phosphoethanolamine plasmalogens, whereas sphingolipids were increased in the OSCC patients compared to the controls. We further identified 12 staging related lipids, which could be utilized to discriminate early stage patients from advanced stage patients. In the future, the differential lipids may provide biologists with additional information regarding lipid metabolism and guide clinicians in making individualized therapeutic decisions if these results are confirmed in a larger study.

Potential plasma lipid biomarkers in early-stage breast cancer

OBJECTIVE

To find new biomarkers for early diagnosis of breast cancer.

RESULTS

847 lipid species were identified from 78 plasma samples (37 breast cancer samples and 41 healthy controls) by ultra HPLC coupled with quadrupole time-of-flight tandem mass spectrometry. These include 321 glycerophospholipids (GPs), 265 glycerolipids (GLs), 91 sphingolipids (SPs), 77 fatty acyls (FAs), 68 sterol lipids (STs), 18 prenol lipids (PRs), 6 polyketides (PKs), and 1 saccharolipid (SL). Separation was observed from an orthogonal signal correction Partial Least Square Discrimination Analysis model. Based on this analysis, six differentiating lipids were identified: PC (20:2/20:5), PC (22:0/24:1), TG (12:0/14:1), and DG (18:1/18:2) had high levels, whereas PE (15:0/19:1) and N-palmitoyl proline had low levels in the breast cancer samples compared with the healthy controls. Furthermore, significant differences in metabolites were found among some clinical characteristics.

CONCLUSIONS

Our results reveal that six specific lipids could serve as potential biomarkers for early diagnosis of breast cancer.

Metabolomic and Lipidomic Profiling Identifies The Role of the RNA Editing Pathway in Endometrial Carcinogenesis

Endometrial cancer (EC) remains the most common malignancy of the genital tract among women in developed countries. Although much research has been performed at genomic, transcriptomic and proteomic level, there is still a significant gap in the metabolomic studies of EC. In order to gain insights into altered metabolic pathways in the onset and progression of EC carcinogenesis, we used high resolution mass spectrometry to characterize the metabolomic and lipidomic profile of 39 human EC and 17 healthy endometrial tissue samples. Several pathways including lipids, Kynurenine pathway, endocannabinoids signaling pathway and the RNA editing pathway were found to be dysregulated in EC. The dysregulation of the RNA editing pathway was further investigated in an independent set of 183 human EC tissues and matched controls, using orthogonal approaches. We found that ADAR2 is overexpressed in EC and that the increase in expression positively correlates with the aggressiveness of the tumor. Furthermore, silencing of ADAR2 in three EC cell lines resulted in a decreased proliferation rate, increased apoptosis, and reduced migration capabilities in vitro. Taken together, our results suggest that ADAR2 functions as an oncogene in endometrial carcinogenesis and could be a potential target for improving EC treatment strategies.

MALDI Orbitrap Mass Spectrometry Profiling of Dysregulated Sulfoglycosphingolipids in Renal Cell Carcinoma Tissues

Matrix-assisted laser desorption/ionization coupled with Orbitrap mass spectrometry (MALDI-Orbitrap-MS) is used for the clinical study of patients with renal cell carcinoma (RCC), as the most common type of kidney cancer. Significant changes in sulfoglycosphingolipid abundances between tumor and autologous normal kidney tissues are observed. First, sulfoglycosphingolipid species in studied RCC samples are identified using high mass accuracy full scan and tandem mass spectra. Subsequently, optimization, method validation, and statistical evaluation of MALDI-MS data for 158 tissues of 80 patients are discussed. More than 120 sulfoglycosphingolipids containing one to five hexosyl units are identified in human RCC samples based on the systematic study of their fragmentation behavior. Many of them are recorded here for the first time. Multivariate data analysis (MDA) methods, i.e., unsupervised principal component analysis (PCA) and supervised orthogonal partial least square discriminant analysis (OPLS-DA), are used for the visualization of differences between normal and tumor samples to reveal the most up- and downregulated lipids in tumor tissues. Obtained results are closely correlated with MALDI mass spectrometry imaging (MSI) and histologic staining. Important steps of the present MALDI-Orbitrap-MS approach are also discussed, such as the selection of best matrix, correct normalization, validation for semiquantitative study, and problems with possible isobaric interferences on closed masses in full scan mass spectra. Graphical Abstract ᅟ.

Lysophosphatidylcholine acyltransferase 1 upregulation and concomitant phospholipid alterations in clear cell renal cell carcinoma

Background

The involvement of lipid metabolism in tumourigenesis and the progression of clear cell renal cell carcinoma (ccRCC) have been reported. However, the role of phospholipid profile alterations in ccRCC has not yet been systematically explored. In the present study, we compared the phospholipid compositions between ccRCC and paired normal renal tissues.

Methods

The phospholipid compositions of paired ccRCC and normal renal tissues were evaluated using liquid chromatography tandem mass spectrometry (LC/MS/MS). To evaluate the mRNA and protein levels of lysophosphatidylcholine acyltransferase (LPCAT), which converts lysophosphatidylcholine (LPC) to phosphatidylcholine (PC), qRT-PCR, western blotting and immunohistochemistry were performed. The correlations of LPCAT1 expression with clinicopathological features and prognosis were assessed. In addition, siRNAs were used to knockdown LPCAT1 expression in ccRCC cell lines, and its effect on cell proliferation, cell cycle, migration and invasion were investigated.

Results

The phospholipid compositions of ccRCC and normal renal tissues were significantly different. Multiple LPC species were decreased and corresponding PC species were increased in cancer tissues. The mRNA and protein levels of LPCAT1 were up-regulated in ccRCC tissues compared with normal renal tissues, and LPCAT1 expression was significantly correlated with unfavourable pathological features (higher tumour grade, higher TNM stage and larger tumour size) and overall survival. In cell line experiments, LPCAT1 knockdown depleted PCs, inhibited cell proliferation, migration and invasion and induced cell cycle arrest at the G0/G1 phase.

Conclusion

Selective changes in PC and LPC composition were observed in ccRCC tissues. The overexpression of LPCAT1 promotes the development and progression of ccRCC, likely through the conversion of LPC to PC.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-017-0525-1) contains supplementary material, which is available to authorized users.

Analytical Techniques in Lipidomics: State of the Art

Current studies related to lipid identification and determination, or lipidomics in biological samples, are one of the most important issues in modern bioanalytical chemistry. There are many articles dedicated to specific analytical strategies used in lipidomics in various kinds of biological samples. However, in such literature, there is a lack of articles dedicated to a comprehensive review of the actual analytical methodologies used in lipidomics. The aim of this article is to characterize the lipidomics methods used in modern bioanalysis according to the methodological point of view: (1) chromatography/separation methods, (2) spectroscopic methods and (3) mass spectrometry and also hyphenated methods. In the first part, we discussed thin layer chromatography (TLC), high-pressure liquid chromatography (HPLC), gas chromatography (GC) and capillary electrophoresis (CE). The second part includes spectroscopic techniques such as Raman spectroscopy (RS), Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (NMR). The third part is a synthetic review of mass spectrometry, matrix-assisted laser desorption/ionization (MALDI), hyphenated methods, which include liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and also multidimensional techniques. Other aspects are the possibilities of the application of the described methods in lipidomics studies. Due to the fact that the exploration of new methods of lipidomics analysis and their applications in clinical and medical studies are still challenging for researchers working in life science, we hope that this review article will be very useful for readers.

Altered lipid metabolism in the aging kidney identified by three layered omic analysis

Aging-associated diseases and their comorbidities affect the life of a constantly growing proportion of the population in developed countries. At the center of these comorbidities are changes of kidney structure and function as age-related chronic kidney disease predisposes to the development of cardiovascular diseases such as stroke, myocardial infarction or heart failure. To detect molecular mechanisms involved in kidney aging, we analyzed gene expression profiles of kidneys from adult and aged wild-type mice by transcriptomic, proteomic and targeted lipidomic methodologies. Interestingly, transcriptome and proteome analyses revealed differential expression of genes primarily involved in lipid metabolism and immune response. Additional lipidomic analyses uncovered significant age-related differences in the total amount of phosphatidylethanolamines, phosphatidylcholines and sphingomyelins as well as in subspecies of phosphatidylserines and ceramides with age. By integration of these datasets we identified Aldh1a1, a key enzyme in vitamin A metabolism specifically expressed in the medullary ascending limb, as one of the most prominent upregulated proteins in old kidneys. Moreover, ceramidase Asah1 was highly expressed in aged kidneys, consistent with a decrease in ceramide C16. In summary, our data suggest that changes in lipid metabolism are involved in the process of kidney aging and in the development of chronic kidney disease.

Off-line mixed-mode liquid chromatography coupled with reversed phase high performance liquid chromatography-high resolution mass spectrometry to improve coverage in lipidomics analysis

The confident identification and in-depth profiling of molecular lipid species remain to be a challenge in lipidomics analysis. In this work, an off-line two-dimensional mixed-mode and reversed-phase liquid chromatography (RPLC) method combined with high-field quadrupole orbitrap mass spectrometer (Q Exactive HF) was developed to profile lipids from complex biological samples. In the first dimension, 22 different lipid classes were separated on a monolithic silica column with elution order from neutral to polar lipids. A total of 13 fractions were collected and run on a RPLC C30 column in the second dimension for further separation of the lipid molecular species based on their hydrophobicity, with the elution order being determined by both the length and degree of unsaturation in the fatty-acyl chain. The method was applied to analyze lipids extracted from rat plasma and rat liver. Fatty acid methyl ester analysis by gas chromatography-mass spectrometry was used to identify the fatty acyls from total lipid extracts, which provided a more confident identification of the lipid species present in these samples. More than 800 lipids were identified in each sample and their molecular structures were confidentially confirmed using tandem mass spectrometry (MS/MS). The number of lipid molecular species identified in both rat plasma and rat liver by this off-line two-dimensional method is approximately twice of that by one-dimensional RPLC-MS/MS employing a C30 column. This off-line two-dimensional mixed-mode LC-RPLC-MS/MS method is a promising technique for comprehensive lipid profiling in complex biological matrices.

Advances in Lipidomics for Cancer Biomarkers Discovery

Lipids play critical functions in cellular survival, proliferation, interaction and death, since they are involved in chemical-energy storage, cellular signaling, cell membranes, and cell-cell interactions. These cellular processes are strongly related to carcinogenesis pathways, particularly to transformation, progression, and metastasis, suggesting the bioactive lipids are mediators of a number of oncogenic processes. The current review gives a synopsis of a lipidomic approach in tumor characterization; we provide an overview on potential lipid biomarkers in the oncology field and on the principal lipidomic methodologies applied. The novel lipidomic biomarkers are reviewed in an effort to underline their role in diagnosis, in prognostic characterization and in prediction of therapeutic outcomes. A lipidomic investigation through mass spectrometry highlights new insights on molecular mechanisms underlying cancer disease. This new understanding will promote clinical applications in drug discovery and personalized therapy.

Lipidomics: Techniques, Applications, and Outcomes Related to Biomedical Sciences

Lipidomics is a newly emerged discipline that studies cellular lipids on a large scale based on analytical chemistry principles and technological tools, particularly mass spectrometry. Recently, techniques have greatly advanced and novel applications of lipidomics in the biomedical sciences have emerged. This review provides a timely update on these aspects. After briefly introducing the lipidomics discipline, we compare mass spectrometry-based techniques for analysis of lipids and summarize very recent applications of lipidomics in health and disease. Finally, we discuss the status of the field, future directions, and advantages and limitations of the field.

Lipidomic Perturbations in Lung, Kidney, and Liver Tissues of p53 Knockout Mice Analyzed by Nanoflow UPLC-ESI-MS/MS

Lipids are important signaling molecules regulating biological processes under normal and diseased conditions. Although p53 mutation is well-known for causing cancer, the relationship between p53-related tumorigenesis and altered lipid profile is unclear. We profiled differences in lipid expressions in liver, lung, and kidney in p53 knockout (KO) mice by high-speed quantitative analysis of 320 lipids (399 species identified) using nanoflow ultrahigh performance liquid chromatography-tandem mass spectrometry (nUPLC-MS/MS). Lung tissues were most severely affected by the lack of p53 gene, as shown by significant reduction (24-44%, P < 0.05) in total phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), diacylglycerol (DG), and triacylglycerol (TG), and significant increases (30-50%) in phosphatidylserine (PS), phosphatidylinositol (PI), and monohexosylceramide (MHC). MHC levels increased in all tissues. Dihexosylceramide (DHC) level decreased only in kidney tissue. Most PI, PS, and phosphatidic acid (PA) species showing significant increases contained a saturated acyl chain (18:0) in lung and liver tissues. Neutral glycerolipids (16:0/22:0-DG and most TGs with saturated and monounsaturated acyl chains) decreased 2-4-fold in the liver tissue. Our results suggest that the lack of p53 and altered lipid profiles are closely related, but as their changes vary from one tissue to another, the lipid alterations are tissue-specific.

Retention behavior of lipids in reversed-phase ultrahigh-performance liquid chromatography-electrospray ionization mass spectrometry

Reversed-phase ultrahigh-performance liquid chromatography (RP-UHPLC) method using two 15cm sub-2μm particles octadecylsilica gel columns is developed with the goal to separate and unambiguously identify a large number of lipid species in biological samples. The identification is performed by the coupling with high-resolution tandem mass spectrometry (MS/MS) using quadrupole - time-of-flight (QTOF) instrument. Electrospray ionization (ESI) full scan and tandem mass spectra are measured in both polarity modes with the mass accuracy better than 5ppm, which provides a high confidence of lipid identification. Over 400 lipid species covering 14 polar and nonpolar lipid classes from 5 lipid categories are identified in total lipid extracts of human plasma, human urine and porcine brain. The general dependences of relative retention times on relative carbon number or relative double bond number are constructed and fit with the second degree polynomial regression. The regular retention patterns in homologous lipid series provide additional identification point for UHPLC/MS lipidomic analysis, which increases the confidence of lipid identification. The reprocessing of previously published data by our and other groups measured in the RP mode and ultrahigh-performance supercritical fluid chromatography on the silica column shows more generic applicability of the polynomial regression for the description of retention behavior and the prediction of retention times. The novelty of this work is the characterization of general trends in the retention behavior of lipids within logical series with constant fatty acyl length or double bond number, which may be used as an additional criterion to increase the confidence of lipid identification.

Lipid Profiling of In Vitro Cell Models of Adipogenic Differentiation: Relationships With Mouse Adipose Tissues

Our objective was to characterize lipid profiles in cell models of adipocyte differentiation in comparison to mouse adipose tissues in vivo. A novel lipid extraction strategy was combined with global lipid profiling using direct infusion and sequential precursor ion fragmentation, termed MS/MS(ALL) . Perirenal and inguinal white adipose tissue and interscapular brown adipose tissues from adult C57BL/6J mice were analyzed. 3T3-L1 preadipocytes, ear mesenchymal progenitor cells, and brown adipose-derived BAT-C1 cells were also characterized. Over 3000 unique lipid species were quantified. Principal component analysis showed that perirenal versus inguinal white adipose tissues varied in lipid composition of triacyl- and diacylglycerols, sphingomyelins, glycerophospholipids and, notably, cardiolipin CL 72:3. In contrast, hexosylceramides and sphingomyelins distinguished brown from white adipose. Adipocyte differentiation models showed broad differences in lipid composition among themselves, upon adipogenic differentiation, and with adipose tissues. Palmitoyl triacylglycerides predominate in 3T3-L1 differentiation models, whereas cardiolipin CL 72:1 and SM 45:4 were abundant in brown adipose-derived cell differentiation models, respectively. MS/MS(ALL) data suggest new lipid biomarkers for tissue-specific lipid contributions to adipogenesis, thus providing a foundation for using in vitro models of adipogenesis to reflect potential changes in adipose tissues in vivo. J. Cell. Biochem. 117: 2182-2193, 2016. © 2016 Wiley Periodicals, Inc.