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

Pathophysiological roles and applications of glycosphingolipids in the diagnosis and treatment of cancer diseases

Glycosphingolipids (GSLs) are major amphiphilic glycolipids present on the surface of living cell membranes. They have important biological functions, including maintaining plasma membrane stability, regulating signal transduction, and mediating cell recognition and adhesion. Specific GSLs and related enzymes are abnormally expressed in many cancer diseases and affect the malignant characteristics of tumors. The regulatory roles of GSLs in signaling pathways suggest that they are involved in tumor pathogenesis. GSLs have therefore been widely studied as diagnostic markers of cancer diseases and important targets of immunotherapy. This review describes the tumor-related biological functions of GSLs and systematically introduces recent progress in using diverse GSLs and related enzymes to diagnose and treat tumor diseases. Development of drugs and biomarkers for personalized cancer therapy based on GSL structure is also discussed. These advances, combined with recent progress in the preparation of GSLs derivatives through synthetic biology technologies, suggest a strong future for the use of customized GSL libraries in treating human diseases.

Robust quantitation of gangliosides and sulfatides in human brain using UHPLC-MRM-MS: Method development and application in Alzheimer's disease

Gangliosides (GAs) and sulfatides (STs) are acidic glycosphingolipids that are particularly abundant in the nervous system and are closely related to aging and neurodegenerative disorders. To explore their roles in brain diseases, in-depth molecular profiling, including structural variations of sphingoid backbone, fatty acyl group, and sugar chain of GAs and STs was performed. A total of 210 GAs and 38 STs were characterized in the inferior frontal gyrus (IFG) of human brain, with 90 GAs discovered in brain tissues for the first time. Influential MS parameters for detecting GAs and STs in multiple reaction monitoring (MRM) mode were systematically examined and optimized to minimize in-source fragmentation, resulting in remarkable signal intensity enhancement for GAs and STs, especially for polysialylated species. To eliminate analytical variations, isotopic interference-free internal standards were prepared by simple and fast reduction reaction. The final established method facilitated the simultaneous quantitation of 184 GAs and 30 STs from 25 subtypes, which represents the highest number of GAs quantitated among all quantitation methods recorded in literature so far. The method was further validated and applied to reveal the aberrant change of GAs and STs in the IFG of 12 Alzheimer's disease (AD) patients. Four GAs exhibited high classification capacity for AD (AUC ≥0.80) and were thereby considered the most promising signatures for AD. These findings suggested the close correlation between GAs and the pathogenesis of AD, highlighting the achievements of our robust method for investigating the roles of GAs and STs in various physiological states and diseases.

Comprehensive characterization of complex glycosphingolipids in human pancreatic cancer tissues

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common causes of cancer-related deaths worldwide, accounting for 90% of primary pancreatic tumors with an average 5-year survival rate of less than 10%. PDAC exhibits aggressive biology, which, together with late detection, results in most PDAC patients presenting with unresectable, locally advanced, or metastatic disease. In-depth lipid profiling and screening of potential biomarkers currently appear to be a promising approach for early detection of PDAC or other cancers. Here, we isolated and characterized complex glycosphingolipids (GSL) from normal and tumor pancreatic tissues of patients with PDAC using a combination of TLC, chemical staining, carbohydrate-recognized ligand-binding assay, and LC/ESI-MS². The major neutral GSL identified were GSL with the terminal blood groups A, B, H, Le^a, Le^b, Le^x, Le^y, P1, and PX2 determinants together with globo- (Gb₃ and Gb₄) and neolacto-series GSL (nLc₄ and nLc₆). We also revealed that the neutral GSL profiles and their relative amounts differ between normal and tumor tissues. Additionally, the normal and tumor pancreatic tissues differ in type 1/2 core chains. Sulfatides and GM₃ gangliosides were the predominant acidic GSL along with the minor sialyl-nLc₄/nLc₆ and sialyl-Le^a/Le^x. The comprehensive analysis of GSL in human PDAC tissues extends the GSL coverage and provides an important platform for further studies of GSL alterations; therefore, it could contribute to the development of new biomarkers and therapeutic approaches.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

A new update of MALDI-TOF mass spectrometry in lipid research

Matrix-assisted laser desorption and ionization (MALDI) mass spectrometry (MS) is an indispensable tool in modern lipid research since it is fast, sensitive, tolerates sample impurities and provides spectra without major analyte fragmentation. We will discuss some methodological aspects, the related ion-forming processes and the MALDI MS characteristics of the different lipid classes (with the focus on glycerophospholipids) and the progress, which was achieved during the last ten years. Particular attention will be given to quantitative aspects of MALDI MS since this is widely considered as the most serious drawback of the method. Although the detailed role of the matrix is not yet completely understood, it will be explicitly shown that the careful choice of the matrix is crucial (besides the careful evaluation of the positive and negative ion mass spectra) in order to be able to detect all lipid classes of interest. Two developments will be highlighted: spatially resolved Imaging MS is nowadays well established and the distribution of lipids in tissues merits increasing interest because lipids are readily detectable and represent ubiquitous compounds. It will also be shown that a combination of MALDI MS with thin-layer chromatography (TLC) enables a fast spatially resolved screening of an entire TLC plate which makes the method competitive with LC/MS.

Lipidomic Analysis of Archival Pathology Specimens Identifies Altered Lipid Signatures in Ovarian Clear Cell Carcinoma

Cancer metabolism is associated with the enhanced lipogenesis required for rapid growth and proliferation. However, the magnitude of dysregulation of diverse lipid species still requires significant characterization, particularly in ovarian clear cell carcinoma (OCCC). Here, we have implemented a robust sample preparation workflow together with targeted LC-MS/MS to identify the lipidomic changes in formalin-fixed paraffin-embedded specimens from OCCC compared to tumor-free ovarian tissue. We quantitated 340 lipid species, representing 28 lipid classes. We observed differential regulation of diverse lipid species belonging to several glycerophospholipid classes and trihexosylceramide. A number of unsaturated lipid species were increased in OCCC, whereas saturated lipid species showed a decrease in OCCC compared to the controls. We also carried out total fatty acid analysis and observed an increase in the levels of several unsaturated fatty acids with a concomitant increase in the index of stearoyl-CoA desaturase (SCD) in OCCC. We confirmed the upregulation of SCD (the rate-limiting enzyme for the synthesis of monounsaturated fatty acids) by immunohistochemistry (IHC) assays. Hence, by carrying out a mass spectrometry analysis of archival tissue samples, we were able to provide insights into lipidomic alterations in OCCC.

Mass spectrometry in the lipid study of cancer

Introduction: Cancer is a heterogeneous disease that exploits various metabolic pathways to meet the demand for increased energy and structural components. Lipids are biomolecules that play essential roles as high energy sources, mediators, and structural components of biological membranes. Accumulating evidence has established that altered lipid metabolism is a hallmark of cancer.Areas covered: Mass spectrometry (MS) is a label-free analytical tool that can simultaneously identify and quantify hundreds of analytes. To date, comprehensive lipid studies exclusively rely on this technique. Here, we reviewed the use of MS in the study of lipids in various cancers and discuss its instrumental limitations and challenges.Expert opinion: MS and MS imaging have significantly contributed to revealing altered lipid metabolism in a variety of cancers. Currently, a single MS approach cannot profile the entire lipidome because of its lack of sensitivity and specificity for all lipid classes. For the metabolic pathway investigation, lipid study requires the integration of MS with other molecular approaches. Future developments regarding the high spatial resolution, mass resolution, and sensitivity of MS instruments are warranted.

Predicting lecithin concentration from differential mobility spectrometry measurements with linear regression models and neural networks

Differential mobility spectrometry (DMS) analysis of electrosurgical smoke can be used to distinguish cancerous and healthy tissues. Mass spectrometry studies of surgical smoke have revealed phospholipids as the key compounds enabling this discrimination. Lecithin is a mixture of phospholipids encountered in tissues. We hypothesized that DMS is capable of detecting and quantifying lecithin from water solution in headspace chamber, paving way for analysis of surgical smoke. We measured different lecithin concentrations in a biologically relevant range considering healthy and cancerous tissues with DMS and trained regression models to predict the analyte concentration. The models were internally cross-validated and externally validated. The best cross-validation results were obtained with convolutional neural networks, with root mean square error (RMSE) = 0.38 mg/ml. This is the first demonstration of estimation of analyte concentration from DMS measurements with neural networks. The best external validation results were acquired with sparse linear regression methods, with RMSE varying from 0.40 mg/ml to 0.41 mg/ml. The results demonstrate that DMS is sufficiently sensitive to detect biologically relevant changes in phospholipid concentration, potentially explaining its ability to detect cancerous tissue. In the future, we aim to reproduce the results by using surgical smoke as the medium. In this scenario, the complex background of surgical smoke will be the main challenge to overcome. Predicting concentration with neural networks also lays the foundation for wider analytical usage of DMS.

Comprehensive Identification of Glycosphingolipids in Human Plasma Using Hydrophilic Interaction Liquid Chromatography-Electrospray Ionization Mass Spectrometry

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.

Characterizing gangliosides in six sea cucumber species by HILIC-ESI-MS/MS

An HILIC-ESI-MS/MS method was established to analyze ganglioside (GLS) in sea cucumbers. In total, 17 GLS subclasses were detected in six sea cucumber species. The basic sea cucumber GLSs (SC-GLSs) were elucidated as NeuGc2-6Glc1-1Cer (SC-GM₄). The polymerization degree of the sialic acid (Sia) of SC-GLSs can be up to 4, and the linkage among Sias was mostly determined to be 2-8 or 2-11. Neu5Gc, sulfated and fucosylated NeuGc prevalently existed in SC-GLSs. Moreover, a new SC-GLSs structure with phosphoinositidyled Sia was first observed in Bohadschia marmorata. For the first time, we demonstrated that the content of SC-GD₄, which is the dominant GLS in sea cucumbers, was 27-67%. Minor GLSs characterized as SC-GT₂(Neu5GcMe) and SC-GQ₂(Neu5GcMe) were also discovered. Additionally, SC-GD₄ and SC-GD₄(1S) could significantly promote the differentiation of PC12 cells with structure-selectivity (p < 0.05). Our results provide insights into SC-GLSs to elucidate their Sia substituent and core saccharide chain linkage.

LICAR: An Application for Isotopic Correction of Targeted Lipidomic Data Acquired with Class-Based Chromatographic Separations Using Multiple Reaction Monitoring

Lipidomics is developing as an important area in biomedical and clinical research. Reliable quantification of lipid species is required for clinical translation of lipidomic studies. Hydrophilic interaction chromatography (HILIC), normal-phase liquid chromatography (NPLC), and supercritical fluid chromatography (SFC) are commonly used techniques in lipidomics and provide class-based separation of lipids. While co-elution of lipid species and their internal standards is an advantage for accurate quantification, it leads to isotopic overlap between species of the same lipid class. In shotgun lipidomics, isotopic correction is typically done based on elemental formulas of precursor ions. In multiple reaction monitoring (MRM) analyses, however, this approach should not be used, as the overall contribution of heavy isotopes to the MRM transitions' intensities depends on their location in the molecule with respect to the fragmentation pattern. We present an algorithm, provided in the R programming language, for isotopic correction in class-based separation using MRM, extracting relevant structural information from MRM transitions to apply adequate isotopic correction factors. Using standards, we show that our algorithm accurately estimates the isotopic contribution of isotopologues to MRM transitions' measured intensities. Using human plasma as an example, we demonstrate the necessity of adequate isotopic correction for accurate quantitation of lipids measured by MRM with class-based chromatographic separation. We show that over a third of the measured phosphatidylcholine species had their intensity corrected by more than 10%. This isotopic correction algorithm and R-implemented application enable a more accurate quantification of lipids in class-based separation-MRM, a prerequisite for successful translation of lipidomic applications.

Laser Ablation Remote-Electrospray Ionisation Mass Spectrometry (LARESI MSI) Imaging-New Method for Detection and Spatial Localization of Metabolites and Mycotoxins Produced by Moulds

To date, no method has been developed to assess the distribution of mycotoxins on the surface of grains, or other plant material, and the depth of their penetration into the interior. The Infrared (IR) Laser Ablation-Remote-Electrospray Ionization (LARESI) platform coupled to a tandem mass spectrometer (MS/MS), measuring in selected reaction monitoring (SRM) mode, was employed for the targeted imaging of selected metabolites of Aspergillus fumigatus, including mycotoxins in biological objects for the first time. This methodology allowed for the localisation of grain metabolites and fungal metabolites of grain infected by this mould. The distribution of metabolites in spelt grain was differentiated: fumigaclavine C, fumitremorgin C, and fumiquinazoline D were located mainly in the embryo, brevianamide F in the seed coat, and fumagillin in the endosperm. The LARESI mass spectrometry imaging method can be used in the future for the metabolomic analysis of mould metabolites in various plants and agricultural products.

Nuclear magnetic resonance and surface-assisted laser desorption/ionization mass spectrometry-based metabolome profiling of urine samples from kidney cancer patients

Kidney cancer is one of the most frequently diagnosed cancers of the urinary tract in the world. Despite significant advances in kidney cancer treatment, no urine specific biomarker is currently used to guide therapeutic interventions. In an effort to address this knowledge gap, metabolic profiling of urine samples from 50 patients with kidney cancer and 50 healthy volunteers was undertaken using high-resolution proton nuclear magnetic resonance spectroscopy (¹H NMR) and silver-109 nanoparticle enhanced steel target laser desorption/ionization mass spectrometry (¹⁰⁹AgNPET LDI MS). Twelve potential urine biomarkers of kidney cancer were identified and quantified using one-dimensional (1D) ¹H NMR metabolomics. Seven mass spectral features which differed significantly in abundance (p < 0.05) between kidney cancer patients and healthy volunteers were also detected using ¹⁰⁹AgNPET-based laser desorption/ionization mass spectrometry (LDI MS). This work provides a framework to expand biomarker discovery that could be used as useful diagnostic or prognostic of kidney cancer progression.

Metabolomics in renal cell carcinoma: From biomarker identification to pathomechanism insights

Renal cell carcinoma (RCC) is a frequently diagnosed cancer with high prevalence, which is inversely associated with survival benefit. Although myriad studies have shed light on disease causality, unfortunately, thus far, RCC diagnosis is faced with numerous obstacles partly due to the insufficient knowledge of effective biomarkers, hinting deeper mechanistic understanding are urgently needed. Metabolites are recognized as final proxies for gene-environment interactions and physiological homeostasis as they reflect dynamic processes that are ongoing or have been taken place, and metabolomics may therefore offer a far more productive and cost-effective route to disease discovery, particularly within the arena for new biomarker identification. In this review, we primarily expatiate recent advances in metabolomics that may be amenable to novel biomarkers or therapeutic targets for RCC, which may expand our armaments to win more bettles against RCC.

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.

SWATH-MS for metabolomics and lipidomics: critical aspects of qualitative and quantitative analysis

INTRODUCTION

While liquid chromatography coupled to mass spectrometric detection in the selected reaction monitoring detection mode offers the best quantification sensitivity for omics, the number of target analytes is limited, must be predefined and specific methods developed. Data independent acquisition (DIA), including SWATH using quadrupole time of flight or orbitrap mass spectrometers and generic acquisition methods, has emerged as a powerful alternative technique for quantitative and qualitative analyses since it can cover a wide range of analytes without predefinition.

OBJECTIVES

Here we review the current state of DIA, SWATH-MS and highlight novel acquisition strategies for metabolomics and lipidomics and opportunities for data analysis tools.

METHOD

Different databases were searched for papers that report developments and applications of DIA and in particular SWATH-MS in metabolomics and lipidomics.

RESULTS

DIA methods generate digital sample records that can be mined retrospectively as further knowledge is gained and, with standardized acquisition schemes, used in multiple studies. The different chemical spaces of metabolites and lipids require different specificities, hence different acquisition and data processing approaches must be considered for their analysis.

CONCLUSIONS

Although the hardware and acquisition modes are well defined for SWATH-MS, a major challenge for routine use remains the lack of appropriate software tools capable of handling large datasets and large numbers of analytes.

Localization of Metabolites of Human Kidney Tissue with Infrared Laser-Based Selected Reaction Monitoring Mass Spectrometry Imaging and Silver-109 Nanoparticle-Based Surface Assisted Laser Desorption/Ionization Mass Spectrometry Imaging

Infrared (IR) laser ablation-remote-electrospray ionization (LARESI) platform coupled to a tandem mass spectrometer (MS/MS) operated in selected reaction monitoring (SRM) or multiple reaction monitoring (MRM) modes was developed and employed for imaging of target metabolites in human kidney cancer tissue. SRM or MRM modes were employed to avoid artifacts that are present in full scan MS mode. Four tissue samples containing both cancerous and noncancerous regions, obtained from three patients with renal cell carcinoma (RCC), were imaged. Sixteen endogenous metabolites that were reported in the literature as varying in abundance between cancerous and noncancerous areas in various human tissues were selected for analysis. Target metabolites comprised ten amino acids, four nucleosides and nucleobases, lactate, and vitamin E. For comparison purposes, images of the same metabolites were obtained with ultraviolet (UV) desorption/ionization mass spectrometry imaging (UV-LDI-MSI) using monoisotopic silver-109 nanoparticle-enhanced target (¹⁰⁹AgNPET) in full-scan MS mode. The acquired MS images revealed differences in abundances of selected metabolites between cancerous and noncancerous regions of the kidney tissue. Importantly, the two imaging methods offered similar results. This study demonstrates the applicability of the novel ambient LARESI SRM/MRM MSI method to both investigating and discovering cancer biomarkers in human tissue.

Mass spectrometry imaging to detect lipid biomarkers and disease signatures in cancer

BACKGROUND

Current methods to identify, classify, and predict tumor behavior mostly rely on histology, immunohistochemistry, and molecular determinants. However, better predictive markers are required for tumor diagnosis and evaluation. Due, in part, to recent technological advancements, metabolomics and lipid biomarkers have become a promising area in cancer research. Therefore, there is a necessity for novel and complementary techniques to identify and visualize these molecular markers within tumors and surrounding tissue.

RECENT FINDINGS

Since its introduction, mass spectrometry imaging (MSI) has proven to be a powerful tool for mapping analytes in biological tissues. By adding the label-free specificity of mass spectrometry to the detailed spatial information of traditional histology, hundreds of lipids can be imaged simultaneously within a tumor. MSI provides highly detailed lipid maps for comparing intra-tumor, tumor margin, and healthy regions to identify biomarkers, patterns of disease, and potential therapeutic targets. In this manuscript, recent advancement in sample preparation and MSI technologies are discussed with special emphasis on cancer lipid research to identify tumor biomarkers.

CONCLUSION

MSI offers a unique approach for biomolecular characterization of tumor tissues and provides valuable complementary information to histology for lipid biomarker discovery and tumor classification in clinical and research cancer applications.

Kidney Lipidomics by Mass Spectrometry Imaging: A Focus on the Glomerulus

Lipid disorders have been associated with glomerulopathies, a distinct type of renal pathologies, such as nephrotic syndrome. Global analyses targeting kidney lipids in this pathophysiologic context have been extensively performed, but most often regardless of the architectural and functional complexity of the kidney. The new developments in mass spectrometry imaging technologies have opened a promising field in localized lipidomic studies focused on this organ. In this article, we revisit the main works having employed the Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF) technology, and the few reports on the use of TOF-Secondary Ion Mass Spectrometry (TOF-SIMS). We also present a first analysis of mouse kidney cortex sections by cluster TOF-SIMS. The latter represents a good option for high resolution lipid imaging when frozen unfixed histological samples are available. The advantages and drawbacks of this developing field are discussed.

Reversed phase UHPLC/ESI-MS determination of oxylipins in human plasma: a case study of female breast cancer

The ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC/MS) method was optimized and validated for the determination of oxylipins in human plasma using the targeted approach with selected reaction monitoring (SRM) in the negative-ion electrospray ionization (ESI) mode. Reversed phase UHPLC separation on an octadecylsilica column enabled the analysis of 63 oxylipins including numerous isomeric species within 12-min run time. The method was validated (calibration curve, linearity, limit of detection, limit of quantification, carry-over, precision, accuracy, recovery rate, and matrix effect) and applied to 40 human female plasma samples from breast cancer patients and age-matched healthy volunteers (control). Thirty-six oxylipins were detected in human plasma with concentrations above the limit of detection, and 21 of them were quantified with concentrations above the limit of quantitation. The concentrations determined in healthy controls are in a good agreement with previously reported data on human plasma. Quantitative data were statistically evaluated by multivariate data analysis (MDA) methods including principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA). S-plot and box plots showed that 13-HODE, 9-HODE, 13-HOTrE, 9-HOTrE, and 12-HHTrE were the most upregulated oxylipin species in plasma of breast cancer patients.