Discovery of Potential Lipid Biomarkers for Human Colorectal Cancer by In-Capillary Extraction Nanoelectrospray Ionization Mass Spectrometry

First Proof of Concept of a Click Inverse Electron Demand Diels-Alder Reaction for Assigning the Regiochemistry of Carbon-Carbon Double Bonds in Untargeted Lipidomics

Lipidomics by high-resolution mass spectrometry (HRMS) has become a prominent tool in clinical chemistry due to the proven connections between lipid dysregulation and the insurgence of pathologies. However, it is difficult to achieve structural characterization beyond the fatty acid level by HRMS, especially when it comes to the regiochemistry of carbon-carbon double bonds, which play a major role in determining the properties of cell membranes. Several approaches have been proposed for elucidating the regiochemistry of double bonds, such as derivatization before MS analysis by photochemical reactions, which have shown great potential for their versatility but have the unavoidable drawback of splitting the MS signal. Among other possible approaches for derivatizing electron-rich double bonds, the emerging inverse-electron-demand Diels-Alder (IEDDA) reaction with tetrazines stands out for its unmatchable kinetics and has found several applications in basic biology and protein imaging. In this study, a catalyst-free click IEDDA reaction was employed for the first time to pinpoint carbon-carbon double bonds in free and conjugated fatty acids. Fatty acid and glycerophospholipid regioisomers were analyzed alone and in combination, demonstrating that the IEDDA reaction had click character and allowed the obtention of diagnostic product ions following MS/MS fragmentation as well as the possibility of performing relative quantitation of lipid regioisomers. The IEDDA protocol was later employed in an untargeted lipidomics study on plasma samples of patients suffering from prostate cancer and benign prostatic conditions, confirming the applicability of the proposed reaction to complex matrices of clinical interest.

Aza-Prilezhaev Aziridination-Enabled Multidimensional Analysis of Isomeric Lipids via High-Resolution U-Shaped Mobility Analyzer-Mass Spectrometry

Unsaturated lipids constitute a significant portion of the lipidome, serving as players of multifaceted functions involving cellular signaling, membrane structure, and bioenergetics. While derivatization-assisted liquid chromatography tandem mass spectrometry (LC-MS/MS) remains the gold standard technique in lipidome, it mainly faces challenges in efficiently labeling the carbon-carbon double bond (C═C) and differentiating isomeric lipids in full dimension. This presents a need for new orthogonal methodologies. Herein, a metal- and additive-free aza-Prilezhaev aziridination (APA)-enabled ion mobility mass spectrometric method is developed for probing multiple levels of unsaturated lipid isomerization with high sensitivity. Both unsaturated polar and nonpolar lipids can be efficiently labeled in the form of N-H aziridine without significant side reactions. The signal intensity can be increased by up to 3 orders of magnitude, achieving the nM detection limit. Abundant site-specific fragmentation ions indicate C═C location and sn-position in MS/MS spectra. Better yet, a stable monoaziridination product is dominant, simplifying the spectrum for lipids with multiple double bonds. Coupled with a U-shaped mobility analyzer, identification of geometric isomers and separation of different lipid classes can be achieved. Additionally, a unique pseudo MS3 mode with UMA-QTOF MS boosts the sensitivity for generating diagnostic fragments. Overall, the current method provides a comprehensive solution for deep-profiling lipidomics, which is valuable for lipid marker discovery in disease monitoring and diagnosis.

Differential lipid analysis of oxaliplatin-sensitive and resistant HCT116 cells reveals different levels of drug-induced lipid droplet formation

Lipid droplets (LDs) are intracellular storage vesicles composed of a neutral lipid core surrounded by a glycerophospholipid membrane. LD accumulation is associated with different stages of cancer progression and stress responses resulting from chemotherapy. In previous work, a novel dual nano-electrospray ionization source and data-dependent acquisition method for measuring the relative abundances of lipid species between two extracts were described and validated. Here, this same source and method were used to determine if oxaliplatin-sensitive and resistant cells undergo similar lipid profile changes, with the goal of identifying potential signatures that could predict the effectiveness of an oxaliplatin-containing treatment. Oxaliplatin is commonly used in the treatment of colorectal cancer. When compared to a no-drug control, oxaliplatin dosing caused significant increases in triglyceride (TG) and cholesterol ester (CE) species. These increases were more pronounced in the oxaliplatin-sensitive cells than in oxaliplatin-resistant cells. The increased neutral lipid abundance correlated with LD formation, as confirmed by confocal micrographs of Nile Red-stained cells. Untargeted proteomic analyses also support LD formation after oxaliplatin treatment, with an increased abundance of LD-associated proteins in both the sensitive and resistant cells.

Selective Characterization of Olefins by Paternò-Büchi Reaction with Ultrahigh Resolution Mass Spectrometry

Petroleum olefins play important roles in various secondary processing procedures and are important feedstocks for the modern organic chemical industry. It is quite challenging to analyze petroleum olefins beyond the gas chromatography (GC)-able range using mass spectrometry (MS) due to the difficulty of soft ionization and the matrix complexity. In this work, a Paternò-Büchi (PB) reaction combined with atmospheric pressure chemical ionization and ultrahigh resolution mass spectrometry (APCI-UHRMS) was developed for selective analysis of olefins. Through the PB reaction, C═C bonds were transformed into four-membered rings of oxetane with improved polarity so that soft ionization of olefins could be achieved. The systematic optimization of PB reaction conditions, as well as MS ionization conditions, ensured a high reaction yield and a satisfied MS response. Furthermore, a sound scheme was set up to discriminate the coexisting unsaturated alkanes in complex petroleum, including linear olefins, nonlinear olefins, cycloalkanes, and aromatics, making use of their different behaviors during the PB reaction and chemical ionization. The developed strategy was successfully applied to the analysis of olefins in fluid catalytic cracking oil slurry, a complex heavy oil sample. This method extended the characterization of petroleum olefins from lower to higher with high efficiency and selectivity to provide a comprehensive molecular library for heavy petroleum samples and process optimization.

Staging of colorectal cancer using lipid biomarkers and machine learning

INTRODUCTION

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Alteration in lipid metabolism and chemokine expression are considered hallmark characteristics of malignant progression and metastasis of CRC. Validated diagnostic and prognostic biomarkers are urgently needed to define molecular heterogeneous CRC clinical stages and subtypes, as liver dominant metastasis has poor survival outcomes.

OBJECTIVES

The aim of this study was to integrate lipid changes, concentrations of chemokines, such as platelet factor 4 and interleukin 8, and gene marker status measured in plasma samples, with clinical features from patients at different CRC stages or who had progressed to stage-IV colorectal liver metastasis (CLM).

METHODS

High-resolution liquid chromatography-mass spectrometry (HR-LC-MS) was used to determine the levels of candidate lipid biomarkers in each CRC patient's preoperative plasma samples and combined with chemokine, gene and clinical data. Machine learning models were then trained using known clinical outcomes to select biomarker combinations that best classify CRC stage and group.

RESULTS

Bayesian neural net and multilinear regression-machine learning identified candidate biomarkers that classify CRC (stages I-III), CLM patients and control subjects (cancer-free or patients with polyps/diverticulitis), showing that integrating specific lipid signatures and chemokines (platelet factor-4 and interluken-8; IL-8) can improve prognostic accuracy. Gene marker status could contribute to disease prediction, but requires ubiquitous testing in clinical cohorts.

CONCLUSION

Our findings demonstrate that correlating multiple disease related features with lipid changes could improve CRC prognosis. The identified signatures could be used as reference biomarkers to predict CRC prognosis and classify stages, and monitor therapeutic intervention.

Miniature mass spectrometers and their potential for clinical point-of-care analysis

Mass spectrometry (MS) has become a powerful technique for clinical applications with high sensitivity and specificity. Different from conventional MS diagnosis in laboratory, point-of-care (POC) analyses in clinics require mass spectrometers and analytical procedures to be friendly for novice users and applicable for on-site clinical diagnosis. The recent decades have seen the progress in the development of miniature mass spectrometers, providing a promising solution for clinical POC applications. In this review, we report recent advances of miniature mass spectrometers and their exploration in clinical applications, mainly including the rapid analysis of illegal drugs, on-site monitoring of therapeutic drugs, and detection of biomarkers. With improved analytical performance, miniature mass spectrometers are also expected to apply to more and more clinical applications. Some promising POC analyses that can be performed by miniature mass spectrometers in the future are discussed. Lastly, we also provide our perspectives on the challenges in technical development of miniature mass spectrometers for clinical POC analysis.

DiffN Selection of Tandem Mass Spectrometry Precursors

Current data-dependent acquisition (DDA) approaches select precursor ions for tandem mass spectrometry (MS/MS) characterization based on their absolute intensity, known as a TopN approach. Low-abundance species may not be identified as biomarkers in a TopN approach. Herein, a new DDA approach is proposed, DiffN, which uses the relative differential intensity of ions between two samples to selectively target species undergoing the largest fold changes for MS/MS. Using a dual nano-electrospray (nESI) ionization source which allows samples contained in separate capillaries to be analyzed in parallel, the DiffN approach was developed and validated with well-defined lipid extracts. A dual nESI source and DiffN DDA approach was applied to quantify the differences in lipid abundance between two colorectal cancer cell lines. The SW480 and SW620 lines represent a matched pair from the same patient: the SW480 cells from a primary tumor and the SW620 cells from a metastatic lesion. A comparison of TopN and DiffN DDA approaches on these cancer cell samples highlights the ability of DiffN to increase the likelihood of biomarker discovery and the decreased probability of TopN to efficiently select lipid species that undergo large fold changes. The ability of the DiffN approach to efficiently select precursor ions of interest makes it a strong candidate for lipidomic analyses. This DiffN DDA approach may also apply to other molecule classes (e.g., other metabolites or proteins) that are amenable to shotgun analyses.

Metal-Polyphenol Network-Mediated Protein Encapsulation Strategy Facilitating the Separation of Proteins and Metabolites in Biospecimens

Access to both protein and metabolite biomarker information in biospecimens from trace samples remains a significant challenge, and it is necessary to separate proteins and metabolites before analysis. In this work, the Fe₃O₄@SiO₂@Proteins@Metal-polyphenol network (MPN) was successfully constructed and applied to separate metabolites and proteins. Tannic acid (TA) and Cu²⁺ were involved in the synthesis of MPN because of rapid degradation and maintaining the assay performance of proteins. There are a variety of interactions between TA and proteins, including hydrogen-bonding, hydrophobic, and ionic interactions. Moreover, benefiting from the small molecule permeability and surface adherence of MPN, proteins were encapsulated and immobilized on the surface of substrates with the growth of MPN. At the same time, endogenous metabolites remained dispersed in the supernatant. In the model sample and real biospecimen cases, the protein biomarkers (e.g., carcinoembryonic antigen and alanine aminotransferase) were encapsulated on the surface of Fe₃O₄@SiO₂, which allowed the isolation of proteins from the original matrix, as well as release and analysis in a short time. Meanwhile, the metabolites in the produced supernatant were analyzed by LC-MS/MS. By the self-assembly and disassembly of MPN, the group differences of proteins and metabolites between physiological and pathological biospecimens are correctly characterized without multisampling. Overall, an MPN-mediated separation strategy of biomarkers was proposed, and MPN facilitated a "two birds with one stone" approach, where the proteins were encapsulated and immobilized in the precipitation while endogenous metabolites distributed in the produced supernatant, opening a new chapter in the application of MPNs.

Novel Aza-Paternò-Büchi Reaction Allows Pinpointing Carbon-Carbon Double Bonds in Unsaturated Lipids by Higher Collisional Dissociation

The evaluation of double bond positions in fatty acyl chains has always been of great concern given their significance in the chemical and biochemical role of lipids. Despite being the foremost technique for lipidomics, it is difficult in practice to obtain identification beyond the fatty acyl level by the sole high-resolution mass spectrometry. Paternò–Büchi reactions of fatty acids (FAs) with ketones have been successfully proposed for pinpointing double bonds in FAs in combination with the collision-induced fragmentation technique. In the present paper, an aza-Paternò–Büchi (aPB) reaction of lipids with 6-azauracil (6-AU) was proposed for the first time for the determination of carbon–carbon double bonds in fatty acyl chains using higher collisional dissociation in the negative ion mode. The method was optimized using free FA and phospholipid analytical standards and compared to the standard Paternò–Büchi reaction with acetone. The introduction of the 6-AU moiety allowed enhancing the ionization efficiency of the FA precursor and diagnostic product ions, thanks to the presence of ionizable sites on the derivatizing agent. Moreover, the aPB derivatization allowed the obtention of deprotonated ions of phosphatidylcholines, thanks to an intramolecular methyl transfer from the phosphocholine polar heads during ionization. The workflow was finally applied for pinpointing carbon–carbon double bonds in 77 polar lipids from an yeast (Saccharomyces cerevisiae) extract.

Review of Recent Advances in Lipid Analysis of Biological Samples via Ambient Ionization Mass Spectrometry

The rapid and direct structural characterization of lipids proves to be critical for studying the functional roles of lipids in many biological processes. Among numerous analytical techniques, ambient ionization mass spectrometry (AIMS) allows for a direct molecular characterization of lipids from various complex biological samples with no/minimal sample pretreatment. Over the recent years, researchers have expanded the applications of the AIMS techniques to lipid structural elucidation via a combination with a series of derivatization strategies (e.g., the Paternò–Büchi (PB) reaction, ozone-induced dissociation (OzID), and epoxidation reaction), including carbon–carbon double bond (C=C) locations and sn-positions isomers. Herein, this review summarizes the reaction mechanisms of various derivatization strategies for C=C bond analysis, typical instrumental setup, and applications of AIMS in the structural elucidation of lipids from various biological samples (e.g., tissues, cells, and biofluids). In addition, future directions of AIMS for lipid structural elucidation are discussed.