Oncolipidomics: Mass spectrometric quantitation of lipids in cancer research

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

HILIC/MS quantitation of low-abundant phospholipids and sphingolipids in human plasma and serum: Dysregulation in pancreatic cancer

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.

Discovery of lipid profiles in plasma-derived extracellular vesicles as biomarkers for breast cancer diagnosis

Lipids are a major component of extracellular vesicles; however, their significance in tumorigenesis and progression has not been well elucidated. As we previously found that lipid profiles drastically changed in breast tumors upon progression, we hypothesized that lipid profiles of plasma-derived extracellular vesicles could be utilized as breast cancer biomarkers. Here, we adopted modified sucrose cushion ultracentrifugation to isolate plasma-derived extracellular vesicles from breast cancer (n = 105), benign (n = 11), and healthy individuals (n = 43) in two independent cohorts (n = 126 and n = 33) and conducted targeted lipidomic analysis. We established a breast cancer diagnostic model comprising three lipids that showed favorable performance with the area under the receiver operating characteristic curve of 0.759, 0.743, and 0.804 in the training, internal validation, and external test sets, respectively. Moreover, we identified several lipids that could effectively discriminate breast cancer progression and subtypes: phosphatidylethanolamines and phosphatidylserines were relatively higher in Stage III, whereas phosphatidylcholines and sphingomyelins were higher in Stage IV; phosphatidylcholines and ceramides were correspondingly concentrated in HER2-positive patients, while lysophosphatidylcholines and polyunsaturated triglycerides were concentrated in the triple-negative breast cancer subtype. Lipid profiling of plasma-derived extracellular vesicles is a non-invasive and promising approach for diagnosing, staging, and subtyping breast cancer.

Clinical lipidomics in the era of the big data

Lipidomics as a branch of metabolomics provides unique information on the complex lipid profile in biological materials. In clinically focused studies, hundreds of lipids together with available clinical information proved to be an effective tool in the discovery of biomarkers and understanding of pathobiochemistry. However, despite the introduction of lipidomics nearly twenty years ago, only dozens of big data studies using clinical lipidomics have been published to date. In this review, we discuss the lipidomics workflow, statistical tools, and the challenges of standartisation. The consequent summary divided into major clinical areas of cardiovascular disease, cancer, diabetes mellitus, neurodegenerative and liver diseases is demonstrating the importance of clinical lipidomics. In these publications, the potential of lipidomics for prediction, diagnosis or finding new targets for the treatment of selected diseases can be seen. The first of these results have already been implemented in clinical practice in the field of cardiovascular diseases, while in other areas we can expect the application of the results summarized in this review in the near future.

Unique sphingolipid signature identifies luminal and triple-negative breast cancer subtypes

Breast cancer (luminal and triple-negative breast cancer [TNBC]) is the most common cancer among women in India and worldwide. Altered sphingolipid levels have emerged as a common phenomenon during cancer progression. However, these alterations are yet to be translated into robust diagnostic and prognostic markers for cancer. Here, we present the quantified sphingolipids of tumor and adjacent-normal tissues from patients of luminal (n = 70) and TNBC (n = 42) subtype from an Indian cohort using targeted liquid chromatography mass spectrometry. We recorded unique sphingolipid profiles that distinguished luminal and TNBC tumors in comparison to adjacent normal tissue by six-sphingolipid signatures. Moreover, systematic comparison of the profiles of luminal and TNBC tumors provided a unique five-sphingolipid signature distinguishing the two subtypes. We further identified key sphingolipids that can stratify grade II and grade III tumors of luminal and TNBC subtype as well as their lymphovascular invasion status. Therefore, we provide the right evidence to develop these candidate sphingolipids as widely acceptable marker/s capable of diagnosing luminal vs TNBC subtype of breast cancer, and predicting the disease severity by identifying the tumor grade.

Altered Plasma, Urine, and Tissue Profiles of Sulfatides and Sphingomyelins in Patients with Renal Cell Carcinoma

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.

Abstract

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.

Untargeted ultra-high-resolution mass spectrometry metabolomic profiling of blood serum in bladder cancer

Bladder cancer (BC) is a common urological cancer of high mortality and recurrence rates. Currently, cystoscopy is performed as standard examination for the diagnosis and subsequent monitoring for recurrence of the patients. Frequent expensive and invasive procedures may deterrent patients from regular follow-up screening, therefore it is important to look for new non-invasive methods to aid in the detection of recurrent and/or primary BC. In this study, ultra-high-performance liquid chromatography coupled with ultra-high-resolution mass spectrometry was employed for non-targeted metabolomic profiling of 200 human serum samples to identify biochemical signatures that differentiate BC from non-cancer controls (NCs). Univariate and multivariate statistical analyses with external validation revealed twenty-seven metabolites that differentiate between BC patients from NCs. Abundances of these metabolites displayed statistically significant differences in two independent training and validation sets. Twenty-three serum metabolites were also found to be distinguishing between low- and high-grade of BC patients and controls. Thirty-seven serum metabolites were found to differentiate between different stages of BC. The results suggest that measurement of serum metabolites may provide more facile and less invasive diagnostic methodology for detection of bladder cancer and recurrent disease management.

Reprogrammed Lipid Metabolism and the Lipid-Associated Hallmarks of Colorectal Cancer

Simple Summary

Colorectal cancer (CRC) is the third-most diagnosed cancer and the second-leading cause of cancer-related deaths worldwide. Limitations in early and accurate diagnosis of CRC gives rise to poor patient survival. Advancements in analytical techniques have improved our understanding of the cellular and metabolic changes occurring in CRC and potentiate avenues for improved diagnostic and therapeutic strategies. Lipids are metabolites with important biological functions; however, their role in CRC is poorly understood. Here, we provide an in-depth review of the recent literature concerning lipid alterations in CRC and propose eight lipid metabolism-associated hallmarks of CRC.

Abstract

Lipids have diverse structures, with multifarious regulatory functions in membrane homeostasis and bioenergetic metabolism, in mediating functional protein–lipid and protein–protein interactions, as in cell signalling and proliferation. An increasing body of evidence supports the notion that aberrant lipid metabolism involving remodelling of cellular membrane structure and changes in energy homeostasis and signalling within cancer-associated pathways play a pivotal role in the onset, progression, and maintenance of colorectal cancer (CRC) and their tumorigenic properties. Recent advances in analytical lipidome analysis technologies have enabled the comprehensive identification and structural characterization of lipids and, consequently, our understanding of the role they play in tumour progression. However, despite progress in our understanding of cancer cell metabolism and lipidomics, the key lipid-associated changes in CRC have yet not been explicitly associated with the well-established ‘hallmarks of cancer’ defined by Hanahan and Weinberg. In this review, we summarize recent findings that highlight the role of reprogrammed lipid metabolism in CRC and use this growing body of evidence to propose eight lipid metabolism-associated hallmarks of colorectal cancer, and to emphasize their importance and linkages to the established cancer hallmarks.

Dual-Mechanism-Driven Strategy for High-Coverage Detection of Serum Lipids on a Novel SALDI-MS Target

Serum lipid metabolites have been emerging as ideal biomarkers for disease diagnosis and prediction. In the current stage, nontargeted or targeted lipidomic research mainly relies on a liquid chromatography-mass spectrometry (LC-MS) platform, but future clinical applications need more robust and high-speed platforms. Surface-assisted laser desorption ionization mass spectrometry (SALDI-MS) has shown excellent advantages in the high-speed analysis of lipid metabolites. However, the platform in the positive ion mode is more inclined to target a certain class of lipids, leading to the low coverage of lipid detection and limiting its practical translation to clinical applications. Herein, we proposed a dual-mechanism-driven strategy for high-coverage detection of serum lipids on a novel SALDI-MS target, which is a composite nanostructure comprising vertical silicon nanowires (VSiNWs) decorated with AuNPs and polydopamine (VSiNW-Au-PDA). The performance of laser desorption and ionization on the target can be enhanced by charge-driven desorption coupled with thermal-driven desorption. Simultaneous detection of 236 serum lipids (S/N ≥ 5) including neutral and polar lipids can be achieved in the positive ion mode. Among these, 107 lipid peaks were successfully identified. When combined with VSiNW-Au-PDA and VSiNW chips, 479 lipid peaks can be detected in serum samples in positive and negative ion modes, respectively. Based on the platform, serum samples from 57 hepatocellular carcinoma (HCC) patients and 76 healthy controls were analyzed. After data mining, 14 lipids containing different lipid types (TAG, CE, PC) were selected as potential lipidomic biomarkers. With the assistance of an artificial neural network, a diagnostic model with a sensitivity of 92.7% and a specificity of 96% was constructed for HCC diagnosis.

Clinical lipidomics – A community-driven roadmap to translate research into clinical applications

•

Overview of current state of mass spectrometry based lipidomics.

•

Highlighting ongoing efforts towards harmonization.

•

Invitation to join international community.

Lipid metabolites, beyond triglycerides and cholesterol, have been shown to have vast potential for applications in clinical applications, with substantial societal and economical value. To successfully evolve from the current research-grade methods to assays suitable for routine clinical applications, a harmonization – if not standardization – of these mass spectrometry-based workflows is necessary. Input on clinical needs and technological capabilities must be obtained from all relevant stakeholders, including wet lab scientists, informaticians and data scientists, manufacturers, and medical professionals. In order to build bridges between this diverse group of professionals, the International Lipidomics Society and its Clinical Lipidomics Interest Group were created. This opinion article is intended to provide an overview of international efforts to tackle the issues of workflow harmonization, and to serve as an open invitation for others to join this growing community.

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.

Lipid Profiles of Human Brain Tumors Obtained by High-Resolution Negative Mode Ambient Mass Spectrometry

Alterations in cell metabolism, including changes in lipid composition occurring during malignancy, are well characterized for various tumor types. However, a significant part of studies that deal with brain tumors have been performed using cell cultures and animal models. Here, we present a dataset of 124 high-resolution negative ionization mode lipid profiles of human brain tumors resected during neurosurgery. The dataset is supplemented with 38 non-tumor pathological brain tissue samples resected during elective surgery. The change in lipid composition alterations of brain tumors enables the possibility of discriminating between malignant and healthy tissues with the implementation of ambient mass spectrometry. On the other hand, the collection of clinical samples allows the comparison of the metabolism alteration patterns in animal models or in vitro models with natural tumor samples ex vivo. The presented dataset is intended to be a data sample for bioinformaticians to test various data analysis techniques with ambient mass spectrometry profiles, or to be a source of clinically relevant data for lipidomic research in oncology.

Simple and Reproducible Derivatization with Benzoyl Chloride: Improvement of Sensitivity for Multiple Lipid Classes in RP-UHPLC/MS

The chemical derivatization of multiple lipid classes was developed using benzoyl chloride as a nonhazardous derivatization agent at ambient conditions. The derivatization procedure was optimized with standards for 4 nonpolar and 8 polar lipid classes and measured by reversed-phase ultrahigh-performance liquid chromatography-tandem mass spectrometry. The derivatization and nonderivatization approaches were compared on the basis of the calibration curves of 22 internal standards from 12 lipid classes. The new method decreased the limit of detection 9-fold for monoacylglycerols (0.9-1.0 nmol/mL), 6.5-fold for sphingoid base (0.2 nmol/mL), and 3-fold for diacylglycerols (0.9 nmol/mL). The sensitivity expressed by the ratio of calibration slopes was increased 2- to 10-fold for almost all investigated lipid classes and even more than 100-fold for monoacylglycerols. Moreover, the benzoylation reaction produces a more stable derivative of cholesterol in comparison to the easily in-source fragmented nonderivatized form and enabled the detection of fatty acids in a positive ion mode, which does not require polarity switching as for the nonderivatized form. The intralaboratory comparison with an additional operator without previous derivatization experiences shows the simplicity, robustness, and reproducibility. The stability of the derivatives was determined by periodical measurements during a one month period and five freeze/thaw cycles. The fully optimized derivatization method was applied to human plasma, which allows the detection of 169 lipid species from 11 lipid classes using the high confidence level of identification in reversed-phase (RP)-ultra high performance liquid chromatography (UHPLC)/mass spectrometry (MS). Generally, we detected more lipid species for monoacylglycerols, diacylglycerols, and sphingoid bases in comparison with previously reported papers without the derivatization.

Plasma lipidomic profiles of kidney, breast and prostate cancer patients differ from healthy controls

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.

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.

High level of phosphatidylcholines/lysophosphatidylcholine ratio in urine is associated with prostate cancer

The altered levels of phospholipids (PLs) and lysophospholipids (LPLs) in prostate cancer (CaP) and benign tissues in our previous findings prompted us to explore PLs and LPLs as potential biomarkers for CaP. Urinary lipidomics has attracted increasing attention in clinical diagnostics and prognostics for CaP. In this study, 31 prostate tissues obtained from radical prostatectomy were assessed using high‐resolution matrix‐assisted laser desorption/ionization imaging mass spectrometry (HR‐MALDI‐IMS). Urine samples were collected after digital rectal examination (DRE), and urinary lipids were extracted using the acidified Bligh‐Dyer method. The discovery set comprised 75 patients with CaP and 44 with benign prostatic hyperplasia (BPH) at Kyoto University Hospital; the validation set comprised 74 patients with CaP and 59 with BPH at Osaka University Hospital. Urinary lipidomic screening was performed using MALDI time‐of‐flight MS (MALDI‐TOF/MS). The levels of urinary lysophosphatidylcholine (LPC) and phosphatidylcholines (PCs) were compared between the CaP and BPH groups. The (PC [34:2] + PC [34:1])/LPC (16:0) ratio was significantly higher (P < .001) in CaP tissues than in benign epithelial tissues. The urinary PCs/LPC ratio was significantly higher (P < .001) in the CaP group than in the BPH group in the discovery and validation sets.

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.

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.

Intra-laboratory comparison of four analytical platforms for lipidomic quantitation using hydrophilic interaction liquid chromatography or supercritical fluid chromatography coupled to quadrupole - time-of-flight mass spectrometry

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.

[Analysis of phosphatidylcholines alterations in human glioblastoma multiform tissues ex vivo]

Significant metabolism alteration is accompanying the cell malignization process. Energy metabolism disturbance leads to the activation of de novo synthesis and beta-oxidation processes of lipids and fatty acids in a cancer cell, which becomes an indicator of pathological processes inside the cell. The majority of studies dealing with lipid metabolism alterations in glial tumors are performed using the cell lines in vitro or animal models. However, such conditions do not entirely represent the physiological conditions of cell growth or possible cells natural variability. This work presents the results of the data obtained by applying ambient mass spectrometry to human glioblastoma multiform tissues. By analyzing a relatively large cohort of primary and secondary glioblastoma samples, we identify the alterations in cells lipid composition, which accompanied the development of grade IV brain tumors. We demonstrate that primary glioblastomas, as well as ones developed from astrocytomas, are enriched with mono- and diunsaturated phosphatidylcholines (PC 26:1, 30:2, 32:1, 32:2, 34:1, 34:2). Simultaneously, the saturated and polyunsaturated phosphatidylcholines and phosphatidylethanolamines decrease. These alterations are obviously linked to the availability of the polyunsaturated fatty acids and activation of the de novo lipid synthesis and beta-oxidation pathways under the anaerobic conditions in the tumor core.

Analytical Platforms for the Determination of Phospholipid Turnover in Breast Cancer Tissue: Role of Phospholipase Activity in Breast Cancer Development

Altered lipid metabolism has been associated with the progression of various cancers, and aberrant expression of enzymes involved in the lipid metabolism has been detected in different stages of cancer. Breast cancer (BC) is one of the cancer types known to be associated with alterations in the lipid metabolism and overexpression of enzymes involved in this metabolism. It has been demonstrated that inhibition of the activity of certain enzymes, such as that of phospholipase A₂ in BC cell lines sensitizes these cells and decreases the IC₅₀ values for forthcoming therapy with traditional drugs, such as doxorubicin and tamoxifen. Moreover, other phospholipases, such as phospholipase C and D, are involved in intracellular signal transduction, which emphasizes their importance in cancer development. Finally, BC is assumed to be dependent on the diet and the composition of lipids in nutrients. Despite their importance, analytical approaches that can associate the activity of phospholipases with changes in the lipid composition and distribution in cancer tissues are not yet standardized. In this review, an overview of various analytical platforms that are applied on the study of lipids and phospholipase activity in BC tissues will be given, as well as their association with cancer diagnosis and tumor progression. The methods that are applied to tissues obtained from the BC patients will be emphasized and critically evaluated, regarding their applicability in oncology.

[The role of lipids in the classification of astrocytoma and glioblastoma using MS tumor profiling]

Express MS identification of biological tissues has become a much more accessible research method due to the application of direct specimen ionization at atmospheric pressure. In contrast to traditional methods of analysis employing GC-MS methods for determining the molecular composition of the analyzed objects it eliminates the influence of mutual ion suppression. Despite significant progress in the field of direct MS of biological tissues, the question of mass spectrometric profile attribution to a certain type of tissue still remains open. The use of modern machine learning methods and protocols (e.g., "random forests") enables us to trace possible relationships between the components of the sample MS profile and the result of brain tumor tissue classification (astrocytoma or glioblastoma). It has been shown that the most pronounced differences in the mass spectrometric profiles of these tumors are due to their lipid composition. Detection of statistically significant differences in lipid profiles of astrocytoma and glioblastoma may be used to perform an express test during surgery and inform the neurosurgeon what type of malignant tissue he is working with. The ability to accurately determine the boundaries of the neoplastic growth significantly improves the quality of both surgical intervention and postoperative rehabilitation, as well as the duration and quality of life of patients.

A visible-light activated [2 + 2] cycloaddition reaction enables pinpointing carbon-carbon double bonds in lipids

The precise location of C[double bond, length as m-dash]C bonds in bioactive molecules is critical for a deep understanding of the relationship between their structures and biological roles. However, the traditional ultraviolet light-based approaches exhibited great limitations. Here, we discovered a new type of visible-light activated [2 + 2] cycloaddition of carbonyl with C[double bond, length as m-dash]C bonds. We found that carbonyl in anthraquinone showed great reactivities towards C[double bond, length as m-dash]C bonds in lipids to form oxetanes under the irradiation of visible-light. Combined with tandem mass spectrometry, this site-specific dissociation of oxetane enabled precisely locating the C[double bond, length as m-dash]C bonds in various kinds of monounsaturated and polyunsaturated lipids. The proof-of-concept applicability of this new type of [2 + 2] photocycloaddition was validated in the global identification of unsaturated lipids in a complex human serum sample. 86 monounsaturated and polyunsaturated lipids were identified with definitive positions of C[double bond, length as m-dash]C bonds, including phospholipids and fatty acids even with up to 6 C[double bond, length as m-dash]C bonds. This study provides new insights into both the photocycloaddition reactions and the structural lipidomics.

A Systematic Review of Metabolomic and Lipidomic Candidates for Biomarkers in Radiation Injury

A large-scale nuclear event has the ability to inflict mass casualties requiring point-of-care and laboratory-based diagnostic and prognostic biomarkers to inform victim triage and appropriate medical intervention. Extensive progress has been made to develop post-exposure point-of-care biodosimetry assays and to identify biomarkers that may be used in early phase testing to predict the course of the disease. Screening for biomarkers has recently extended to identify specific metabolomic and lipidomic responses to radiation using animal models. The objective of this review was to determine which metabolites or lipids most frequently experienced perturbations post-ionizing irradiation (IR) in preclinical studies using animal models of acute radiation sickness (ARS) and delayed effects of acute radiation exposure (DEARE). Upon review of approximately 65 manuscripts published in the peer-reviewed literature, the most frequently referenced metabolites showing clear changes in IR induced injury were found to be citrulline, citric acid, creatine, taurine, carnitine, xanthine, creatinine, hypoxanthine, uric acid, and threonine. Each metabolite was evaluated by specific study parameters to determine whether trends were in agreement across several studies. A select few show agreement across variable animal models, IR doses and timepoints, indicating that they may be ubiquitous and appropriate for use in diagnostic or prognostic biomarker panels.

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.

Lipidomic characterization of exosomes isolated from human plasma using various mass spectrometry techniques

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.