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The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic easy-to-use checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research., Competing Interests: Conflict of interests Kaddurah-Daouk is an inventor on key patents in the field of metabolomics and hold equity in Metabolon, a biotech company in North Carolina. In addition, she holds patents licensed to Chymia LLC and PsyProtix with royalties and ownership. Kim Ekroos is the owner of Lipidomics Consulting Ltd., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Direct infusion of lipid extracts into the ion source of a mass spectrometer is a well-established method for lipid analysis. In most cases, nanofluidic devices are used for sample introduction. However, flow injection analysis (FIA) based on sample infusion from a chromatographic pump can offer a simple alternative to shotgun-based approaches. Here, we describe important modification of a method based on FIA and tandem mass spectrometry (MS/MS). We focus on minimizing contamination of the FIA/MS both to render the lipidomic platform more robust and to increase its capacity and applicability for long-sequence measurements required in clinical applications. Robust validation of the developed method confirms its suitability for lipid quantitation in human plasma analysis. Measurements of standard human plasma reference material (NIST SRM 1950) and a set of plasma samples collected from kidney cancer patients and from healthy volunteers yielded highly similar results between FIA-MS/MS and ultra-high-performance supercritical fluid chromatography (UHPSFC)/MS, thereby demonstrating that all modifications have practically no effect on the statistical output. Newly modified FIA-MS/MS allows for the quantitation of 141 lipid species in plasma (11 major lipid classes) within 5.7 min. Finally, we tested the method in a clinical laboratory of the General University Hospital in Prague. In the clinical setting, the method capacity reached 257 samples/day. We also show similar performance of the classification models trained based on the results obtained in clinical settings and the analytical laboratory at the University of Pardubice. Together, these findings demonstrate the high potential of the modified FIA-MS/MS for application in clinical laboratories to measure plasma and serum lipid profiles., (© 2023. Springer-Verlag GmbH Germany, part of Springer Nature.)

Summary: We present the LipidQuant 1.0 tool for automated data processing workflows in lipidomic quantitation based on lipid class separation coupled with high-resolution mass spectrometry. Lipid class separation workflows, such as hydrophilic interaction liquid chromatography or supercritical fluid chromatography, should be preferred in lipidomic quantitation due to the coionization of lipid class internal standards with analytes from the same class. The individual steps in the LipidQuant workflow are explained, including lipid identification, quantitation, isotopic correction and reporting results. We show the application of LipidQuant data processing to a small cohort of human serum samples., Availability and Implementation: The LipidQuant 1.0 is freely available at Zenodo https://doi.org/10.5281/zenodo.5151201 and https://holcapek.upce.cz/lipidquant.php., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Early detection of cancer is one of the unmet needs in clinical medicine. Peripheral blood analysis is a preferred method for efficient population screening, because blood collection is well embedded in clinical practice and minimally invasive for patients. Lipids are important biomolecules, and variations in lipid concentrations can reflect pathological disorders. Lipidomic profiling of human plasma by the coupling of ultrahigh-performance supercritical fluid chromatography and mass spectrometry is investigated with the aim to distinguish patients with breast, kidney, and prostate cancers from healthy controls. The mean sensitivity, specificity, and accuracy of the lipid profiling approach were 85%, 95%, and 92% for kidney cancer; 91%, 97%, and 94% for breast cancer; and 87%, 95%, and 92% for prostate cancer. No association of statistical models with tumor stage is observed. The statistically most significant lipid species for the differentiation of cancer types studied are CE 16:0, Cer 42:1, LPC 18:2, PC 36:2, PC 36:3, SM 32:1, and SM 41:1 These seven lipids represent a potential biomarker panel for kidney, breast, and prostate cancer screening, but a further verification step in a prospective study has to be performed to verify clinical utility., (© 2021. The Author(s).)

The lipidomic research is currently devoting considerable effort to the harmonization that should enable the generation of comparable and accurate quantitative lipidomic data across different laboratories and regardless of the mass spectrometry-based platform used. In the present study, we systematically investigate the effects of the experimental setup on quantitative lipidomics data obtained by two lipid class separation approaches, hydrophilic interaction liquid chromatography (HILIC) and ultrahigh-performance supercritical fluid chromatography (UHPSFC), coupled to two different quadrupole - time of flight (QTOF) mass spectrometers from the same vendor. This approach is applied for measurements of 268 human plasma samples of healthy volunteers and renal cell carcinoma patients resulting in four data sets. We investigate and visualize differences among these data sets by multivariate data analysis methods, such as principal component analysis (PCA), orthogonal partial least square discriminant analysis (OPLS-DA), box plots, and logarithmic correlations of molar concentrations of individual lipid species. The results indicate that even measurements in the same laboratory for the same samples using different analytical platforms may yield slight variations in the molar concentrations determined. The normalization to a reference sample with defined lipid concentrations can further diminish these small differences, resulting in highly homogenous molar concentrations of individual lipid species. This strategy indicates a potential approach towards the reporting of comparable quantitative results independent from the quantitative approach and mass spectrometer used, which is important for a wider acceptance of lipidomics data in various biomarker inter-laboratory studies and ring trials., (Copyright © 2021 Elsevier B.V. All rights reserved.)

In the last 2 decades, lipidomics has become one of the fastest expanding scientific disciplines in biomedical research. With an increasing number of new research groups to the field, it is even more important to design guidelines for assuring high standards of data quality. The Lipidomics Standards Initiative is a community-based endeavor for the coordination of development of these best practice guidelines in lipidomics and is embedded within the International Lipidomics Society. It is the intention of this review to highlight the most quality-relevant aspects of the lipidomics workflow, including preanalytics, sample preparation, MS, and lipid species identification and quantitation. Furthermore, this review just does not only highlights examples of best practice but also sheds light on strengths, drawbacks, and pitfalls in the lipidomic analysis workflow. While this review is neither designed to be a step-by-step protocol by itself nor dedicated to a specific application of lipidomics, it should nevertheless provide the interested reader with links and original publications to obtain a comprehensive overview concerning the state-of-the-art practices in the field., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Ultrahigh-performance supercritical fluid chromatography - mass spectrometry (UHPSFC/MS), ultrahigh-performance liquid chromatography - mass spectrometry (UHPLC/MS), and matrix-assisted laser desorption/ionization (MALDI) - MS techniques were used for the lipidomic characterization of exosomes isolated from human plasma. The high-throughput methods UHPSFC/MS and UHPLC/MS using a silica-based column containing sub-2 μm particles enabled the lipid class separation and the quantitation based on exogenous class internal standards in <7 minute run time. MALDI provided the complementary information on anionic lipid classes, such as sulfatides. The nontargeted analysis of 12 healthy volunteers was performed, and absolute molar concentration of 244 lipids in exosomes and 191 lipids in plasma belonging to 10 lipid classes were quantified. The statistical evaluation of data included principal component analysis, orthogonal partial least square discriminant analysis, S-plots, p-values, T-values, fold changes, false discovery rate, box plots, and correlation plots, which resulted in the information on lipid changes in exosomes in comparison to plasma. The major changes were detected in the composition of triacylglycerols, diacylglycerols, phosphatidylcholines, and lysophosphatidylcholines, whereby sphingomyelins, phosphatidylinositols, and sulfatides showed rather similar profiles in both biological matrices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

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.

Simple Summary: Renal cell carcinoma (RCC) is among the most common cancer types in both men and women, and its early detection significantly improves survival. Minimally-invasive blood- or urine-based tests may increase the RCC detection rate, especially before patients develop symptoms. Here, we report significant changes in concentrations of sulfatides and sphingomyelins in plasma and urine in RCC patients compared to healthy controls. For the first time, we present findings that similar alterations appear in the lipid profiles of body fluids and tissues in patients. We observe gradual changes in sulfatide and sphingomyelin concentrations with increasing tumor stage and grade. We built binary classifiers that detect RCC based on plasma and urine lipidome dysregulations, and we show that the plasma lipidome alterations enable distinguishing between early-stage RCC and controls. Our results demonstrate the considerable potential of lipid screening in biofluids for RCC detection and monitoring in clinical settings. Purpose: RCC, the most common type of kidney cancer, is associated with high mortality. A non-invasive diagnostic test remains unavailable due to the lack of RCC-specific biomarkers in body fluids. We have previously described a significantly altered profile of sulfatides in RCC tumor tissues, motivating us to investigate whether these alterations are reflected in collectible body fluids and whether they can enable RCC detection. Methods: We collected and further analyzed 143 plasma, 100 urine, and 154 tissue samples from 155 kidney cancer patients, together with 207 plasma and 70 urine samples from 214 healthy controls. Results: For the first time, we show elevated concentrations of lactosylsulfatides and decreased levels of sulfatides with hydroxylated fatty acyls in body fluids of RCC patients compared to controls. These alterations are emphasized in patients with the advanced tumor stage. Classification models are able to distinguish between controls and patients with RCC. In the case of all plasma samples, the AUC for the testing set was 0.903 (0.844–0.954), while for urine samples it was 0.867 (0.763–0.953). The models are able to efficiently detect patients with early- and late-stage RCC based on plasma samples as well. The test set sensitivities were 80.6% and 90%, and AUC values were 0.899 (0.832–0.952) and 0.981 (0.956–0.998), respectively. Conclusion: Similar trends in body fluids and tissues indicate that RCC influences lipid metabolism, and highlight the potential of the studied lipids for minimally-invasive cancer detection, including patients with early tumor stages, as demonstrated by the predictive ability of the applied classification models. [ABSTRACT FROM AUTHOR]

The article presents the discussion on newcomers and beginners entering the lipidomic field. Topics include adequate knowledge of basic analytical methodology, nomenclature, and data reporting causing confusion in data interpretation and reporting; and potential of ultrahigh-resolving power mass spectrometers, typically orbital trap analyzers, and MS imaging for the visualization of tissues.

The characterization of differences among polar lipid classes in tumors and surrounding normal tissues of 20 kidney cancer patients is performed by hydrophilic interaction liquid chromatography (HILIC) coupled to electrospray ionization mass spectrometry (ESI–MS). The detailed analysis of identified lipid classes using relative abundances of characteristic ions in negative- and positive-ion modes is used for the determination of more than 120 individual lipid species containing attached fatty acyls of different chain length and double bond number. Lipid species are described using relative abundances, providing a better visualization of lipidomic differences between tumor and normal tissues. The multivariate data analysis methods using unsupervised principal component analysis (PCA) and supervised orthogonal partial least square (OPLS) are used for the characterization of statistically significant differences in identified lipid species. Ten most significant up- and down-regulated lipids in OPLS score plots are also displayed by box plots. A notable increase of relative abundances of lipids containing four and more double bonds is detected in tumor compared to normal tissues. [ABSTRACT FROM AUTHOR]

Differences among lipidomic profiles of healthy volunteers, obese people and three groups of cardiovascular disease (CVD) patients are investigated with the goal to differentiate individual groups based on the multivariate data analysis (MDA) of lipidomic data from plasma, erythrocytes and lipoprotein fractions of more than 50 subjects. Hydrophilic interaction liquid chromatography on ultrahigh-performance liquid chromatography (HILIC-UHPLC) column coupled with electrospray ionization mass spectrometry (ESI-MS) is used for the quantitation of four classes of polar lipids (phosphatidylethanolamines, phosphatidylcholines, sphingomyelins and lysophosphatidylcholines), normal-phase UHPLC—atmospheric pressure chemical ionization MS (NP-UHPLC/APCI-MS) is applied for the quantitation of five classes of nonpolar lipids (cholesteryl esters, triacylglycerols, sterols, 1,3-diacylglycerols and 1,2-diacylglycerols) and the potential of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is tested for the fast screening of all lipids without a chromatographic separation. Obtained results are processed by unsupervised (principal component analysis) and supervised (orthogonal partial least squares) MDA approaches to highlight the largest differences among individual groups and to identify lipid molecules with the highest impact on the group differentiation. [ABSTRACT FROM AUTHOR]

Membrane lipids and their metabolism have key functions in neurotransmission. Here we provide a quantitative lipid inventory of mouse and rat synaptic junctions. To this end, we developed a multiomics extraction and analysis workflow to probe the interplay of proteins and lipids in synaptic signal transduction from the same sample. Based on this workflow, we generate hypotheses about novel mechanisms underlying complex changes in synaptic connectivity elicited by environmental stimuli. As a proof of principle, this approach reveals that in mice exposed to an enriched environment, reduced endocannabinoid synthesis and signaling is linked to increased surface expression of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) in a subset of Cannabinoid-receptor 1 positive synapses. This mechanism regulates synaptic strength in an input-specific manner. Thus, we establish a compartment-specific multiomics workflow that is suitable to extract information from complex lipid and protein networks involved in synaptic function and plasticity. [Display omitted] • A multiomics workflow reveals lipid and protein networks of synaptic junctions • An in-depth quantitative lipidome of synaptic junctions is provided • Enriched environment reduces endocannabinoid signaling at spine synapses • Reduced endocannabinoid signaling increases surface expression of AMPA receptors Borgmeyer et al. provide a resource of lipid and protein content of forebrain synaptic junctions. This Multiomics is suitable to generate hypotheses on lipid signaling pathways that are altered by enriched environment in mice. The data suggest that changes in endocannabinoid signaling might affect synaptic plasticity. [ABSTRACT FROM AUTHOR]

Glycosphingolipids (GSL) represent a highly heterogeneous class of lipids with many cellular functions, implicated in a wide spectrum of human diseases. Their isolation, detection, and comprehensive structural analysis is a challenging task due to the structural diversity of GSL molecules. In this work, GSL subclasses are isolated from human plasma using an optimized monophasic ethanol–water solvent system capable to recover a broad range of GSL species. Obtained deproteinized plasma is subsequently purified and concentrated by C18-based solid-phase extraction (SPE). The hydrophilic interaction liquid chromatography coupled to electrospray ionization linear ion trap tandem mass spectrometry (HILIC-ESI-LIT-MS/MS) is used for GSL analysis in the human plasma extract. Our results provide an in-depth profiling and structural characterization of glycosphingolipid and some phospholipid subclasses identified in the human plasma based on their retention times and the interpretation of tandem mass spectra. The structural composition of particular lipid species is readily characterized based on the detailed interpretation of mass spectrometry (MS) and tandem mass spectrometry (MS/MS) spectra and further confirmed by specific fragmentation behavior following predictable patterns, which yields to the unambiguous identification of 154 GSL species within 7 lipid subclasses and 77 phospholipids representing the highest number of GSL species ever reported in the human plasma. The developed HILIC-ESI-MS/MS method can be used for further clinical and biological research of GSL in the human blood or other biological samples. [ABSTRACT FROM AUTHOR]

Mass spectrometry combined with (ultra)high-performance liquid chromatography has proved to be the most suitable method for the analysis of glycosphingolipids (GSLs). An increasing number of studies have focused on the analysis of not only simple but also complex GSLs with the aim of clarifying their biochemical functions in animals and humans. Despite the tremendous improvements in sample preparation and analytical methods in glycosphingolipidomics, there are still several major issues that complicate the comprehensive analysis of GSLs. This review aims to provide the latest advances, developments, and instrumental innovations in the analysis of GSLs in biological samples. The current barriers and challenges facing the qualitative and quantitative analysis of GSLs are highlighted and critically assessed. Overcoming these bottlenecks is crucial for high-throughput GSLs profiling, which is essential to reveal their clinical potential and to understand their role in the pathophysiology of serious diseases, such as cancer. • Overview of recent advances and current trends in the analysis of GSLs. • Absence of a unique isolation protocol hampers the comprehensive analysis of GSLs. • Challenging separation of GSL isomers is discussed. • Lack of ISs and reference materials complicate the quantitation of GSLs. • Harmonization is urgently needed to translate lipidomics into clinical practice. [ABSTRACT FROM AUTHOR]

LipidQuant 2.1 is a software written in Matlab, which is designed for the high-throughput processing of large lipidomic data sets measured by lipid class separation coupled with quadrupole time-of-flight (QTOF) high-resolution mass spectrometry (MS). The software enables the identification of lipid species based on defined mass accuracy. The main focus is on the right lipidomic quantitation using at least one internal standard per lipid class and the implementation of an automated procedure for Type I and Type II isotopic corrections necessary for the determination of accurate molar concentrations, which is not available for the majority of existing software solutions. LipidQuant 2.1 offers three options for peak assignment, visualization of the isotopic pattern, and automated calculation of m/z for various adduct ions. The initial lipidomic database covers 31 lipid classes with more than 2900 lipid species that occur primarily in the human lipidome, but users have the full flexibility to modify and extend the database according to their needs. All algorithms and the detailed user manual are provided. The reliability of LipidQuant 2.1 is demonstrated on a set of more than 250 biological samples measured by ultrahigh-performance supercritical liquid chromatography (UHPSFC) coupled with QTOF-MS. • Open-source lipidomics software. • Identification and quantification of lipidomic data measured by lipid class separation coupled with full scan QTOF high-resolution MS. • Quantitation includes Type I and Type II isotopic corrections calculated using nonnegative regression. [ABSTRACT FROM AUTHOR]

Abstract: Lipids are important components in all biological tissues having many essential roles associated with the proper function of the organism. Their analysis in the biological tissues and body fluids is a challenging task due to the extreme sample complexity of polar lipids and to their amphiphilic character. In this work, we describe a new method for the characterization of the lipid composition in various tissues, using off-line two-dimensional coupling of hydrophilic interaction liquid chromatography (HILIC) and reversed-phase (RP) high-performance liquid chromatography coupled to electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) mass spectrometry. In the first dimension the total lipid extracts are fractioned using HILIC into individual lipid classes. In total, 19 lipid classes (+3 regioisomeric pairs) that cover a wide range of polarities are separated in one analytical run, which is the highest number of analyzed lipid classes reported so far. The lysophospholipid regioisomers are also separated in HILIC mode followed by the identification based on the characteristic ESI mass spectra. The collected fractions of the various lipid classes are further separated in the RP mode, which offers an excellent resolution of the individual lipid species. Their ESI or APCI mass spectra give correct information on the fatty acid composition and on the individual regioisomeric positions on the glycerol skeleton. Off-line coupling of both modes enables the comprehensive analysis of plant and animal samples as illustrated on the analysis of egg yolk, soya and porcine brain tissues. [Copyright &y& Elsevier]

A new hydrophilic interaction liquid chromatography - mass spectrometry method is developed for low-abundant phospholipids and sphingolipids in human plasma and serum. The optimized method involves the Cogent Silica type C hydride column, the simple sample preparation by protein precipitation, and the removal of highly abundant lipid classes using the postcolumn valve directed to waste during two elution windows. The method allows a highly confident and sensitive identification of low-abundant lipid classes in human plasma (246 lipid species from 24 lipid subclasses) based on mass accuracy and retention dependencies in both polarity modes. The method is validated for quantitation using two internal standards (if available) for each lipid class and applied to human plasma and serum samples obtained from patients with pancreatic ductal adenocarcinoma (PDAC), healthy controls, and NIST SRM 1950. Multivariate data analysis followed by various statistical projection methods is used to determine the most dysregulated lipids. Significant downregulation is observed for lysophospholipids with fatty acyl composition 16:0, 18:0, 18:1, and 18:2. Distinct trends are observed for phosphatidylethanolamines (PE) in relation to the bonding type of fatty acyls, where most PE with acyl bonds are upregulated, while ether/plasmenyl PE are downregulated. For the sphingolipid category, sphingolipids with very long N-acyl chains are downregulated, while sphingolipids with shorter N-acyl chains were upregulated in PDAC. These changes are consistently observed for various classes of sphingolipids, ranging from ceramides to glycosphingolipids, indicating a possible metabolic disorder in ceramide biosynthesis caused by PDAC. [Display omitted] • New quantitative method for low abundant lipid classes in human plasma and serum. • Lipidomic profiling of patients with pancreatic cancer and healthy controls. • Statistical evaluation and determination of the most dysregulated lipids. • Correlation of dysregulated sphingolipids and phospholipids with their metabolic pathways. [ABSTRACT FROM AUTHOR]

Effects of blood collection tubes, the time period, the sample origin, and the method used on the lipidomic profile are investigated by ultrahigh-performance supercritical fluid chromatography - mass spectrometry (UHPSFC/MS) and hydrophilic interaction liquid chromatography ultrahigh-performance liquid chromatography - mass spectrometry (HILIC-UHPLC/MS). Heparin plasma samples have been obtained from 99 healthy volunteers at three time points separated by six-month intervals together with one collection for EDTA plasma and serum. Furthermore, lipid concentrations in heparin plasma collected at two different sites are compared. 171 lipid species from eight lipid classes are quantified with UHPSFC/MS, and 122 lipid species from four lipid classes with HILIC-UHPLC/MS. The accuracy of both methods is monitored by the quantitation error using two internal standards (IS) per individual lipid classes. No significant differences in lipid profiles are observed for different time points and types of collection tubes (heparin plasma, EDTA plasma, and serum). Most pronounced lipid concentration differences are observed for the comparison of NIST SRM 1950 human plasma and mean lipid concentrations of the investigated cohort. Furthermore, differences in lipid concentrations are observed between employed methods (UHPSFC/MS vs. HILIC-UHPLC/MS), which can be compensated by the normalization using NIST SRM 1950 human plasma used as the quality control sample. Image 1 • Quality control system is developed for the quality assurance of lipidomic quantitation. • Lipidomic profiles are less influenced by the type of blood collection tubes than by the effect of time and collection site. • Method dependent measurement bias can be compensated by the reference value normalization. [ABSTRACT FROM AUTHOR]

Lipidomic analysis of biological samples in a clinical research represents challenging task for analytical methods given by the large number of samples and their extreme complexity. In this work, we compare direct infusion (DI) and chromatography – mass spectrometry (MS) lipidomic approaches represented by three analytical methods in terms of comprehensiveness, sample throughput, and validation results for the lipidomic analysis of biological samples represented by tumor tissue, surrounding normal tissue, plasma, and erythrocytes of kidney cancer patients. Methods are compared in one laboratory using the identical analytical protocol to ensure comparable conditions. Ultrahigh-performance liquid chromatography/MS (UHPLC/MS) method in hydrophilic interaction liquid chromatography mode and DI-MS method are used for this comparison as the most widely used methods for the lipidomic analysis together with ultrahigh-performance supercritical fluid chromatography/MS (UHPSFC/MS) method showing promising results in metabolomics analyses. The nontargeted analysis of pooled samples is performed using all tested methods and 610 lipid species within 23 lipid classes are identified. DI method provides the most comprehensive results due to identification of some polar lipid classes, which are not identified by UHPLC and UHPSFC methods. On the other hand, UHPSFC method provides an excellent sensitivity for less polar lipid classes and the highest sample throughput within 10 min method time. The sample consumption of DI method is 125 times higher than for other methods, while only 40 μL of organic solvent is used for one sample analysis compared to 3.5 mL and 4.9 mL in case of UHPLC and UHPSFC methods, respectively. Methods are validated for the quantitative lipidomic analysis of plasma samples with one internal standard for each lipid class. Results show applicability of all tested methods for the lipidomic analysis of biological samples depending on the analysis requirements. [ABSTRACT FROM AUTHOR]

Reversed-phase ultrahigh-performance liquid chromatography (RP-UHPLC) method using two 15 cm sub–2 μm 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 5 ppm, 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. [ABSTRACT FROM AUTHOR]

Ultrahigh-performance supercritical fluid chromatography/mass spectrometry (UHPSFC/MS) is one of the fastest analytical approaches for high-throughput lipidomic analysis covering a wide range of lipid categories and classes. Lipid class separation and lipid species separation are two main separation modes available for the UHPSFC analysis of lipids. The mechanism of the lipid class separation mode is comparable to that of hydrophilic interaction liquid chromatography (HILIC). The direct comparison of HILIC - ultrahigh-performance liquid chromatography (HILIC-UHPLC) and UHPSFC shows the applicability of UHPSFC/MS for high-throughput quantitation of both nonpolar and polar lipid classes, the faster analysis time, and comparable reproducibility and sensitivity. The retention mechanism of the lipid species separation mode is comparable to reversed-phase UHPLC, but the nonpolar character of supercritical carbon dioxide (scCO 2) provides a different selectivity compared to that of conventional RP-UHPLC. The introduction of various hyphenation interfaces to MS broadens the applicability and sensitivity range of UHPSFC/MS using scCO 2 as the main component of the mobile phase. The addition of ionic additives (volatile salts, acids, and bases) to the modifier improves the separation of medium to polar lipids. Furthermore, UHPSFC/MS has also a great potential in the chiral separation of lipids, but the field has not yet been fully explored. • UHPSFC/MS is one of the fastest analytical methods for lipidomic analysis. • Lipid class separation and lipid species separation are two basic approaches in UHPSFC. • UHPSFC/MS high-throughput lipidomic quantitation is well suited for clinical analysis. • Advantages and limitations of UHPSFC/MS and UHPLC/MS are compared. [ABSTRACT FROM AUTHOR]

Lung cancer represents one of the leading worldwide causes of cancer death, but the pathobiochemistry of this disease is still not fully understood. Here we characterize the lipidomic and metabolomic profiles of the tumor and surrounding normal tissues for 23 patients with non-small cell lung cancer. In total, 500 molecular species were identified and quantified by a combination of the lipidomic shotgun tandem mass spectrometry (MS/MS) analysis and the targeted metabolomic approach using liquid chromatography (LC) – MS/MS. The statistical evaluation includes multivariate and univariate methods with the emphasis on paired statistical approaches. Our research revealed significant changes in several biochemical pathways related to the central carbon metabolism, acylcarnitines, dipeptides as well as the disruption in the lipid metabolism observed mainly for glycerophospholipids, sphingolipids, and cholesteryl esters. • Lipidomic and metabolomic profiles measured for 23 patients tissues with non-small cell lung cancer • 500 molecular species were quantified by MS based workflows • Paired statistical evaluation performed by multivariate and univariate methods • Changed pathways related to the central carbon metabolism, acylcarnitines, dipeptides, PL, SL, and CE [ABSTRACT FROM AUTHOR]

This review summarizes available mass spectrometry (MS) based approaches for the quantitative analysis of lipids in biological samples in the cancer research, which is termed here as oncolipidomics. The methodological part shows possible configurations of stand-alone MS or MS coupled to liquid-phase separation techniques. For the characterization of various lipids with the special emphasis on methods convenient for robust high-throughput lipidomic quantitation of biological samples, such as body fluids, tissues, and cell lines. The critical assessment of lipid species dysregulated in various cancer types is provided with the goal to summarize and generalize the typical up and down regulated lipids associated with the progress of tumor growth and evaluate possible future use of lipidomic analysis in the early cancer diagnosis. • Overview of MS based methods for lipidomic analysis in cancer research. • Basic concepts in the lipidomic quantitation of biological samples. • Dysregulation of lipids in various types of cancer. [ABSTRACT FROM AUTHOR]