Plasma lysophosphatidylcholine levels: potential biomarkers for colorectal cancer

Lipid metabolism in cancer: Exploring phospholipids as potential biomarkers

Aberrant lipid metabolism is increasingly recognized as a hallmark of cancer, contributing to tumor growth, metastatic dissemination, and resistance to therapy. Cancer cells reprogram key metabolic pathways-including de novo lipogenesis, lipid uptake, and phospholipid remodeling-to sustain malignant progression and adapt to microenvironmental demands. This review summarizes current insights into the role of lipid metabolic reprogramming in oncogenesis and highlights recent advances in lipidomics that have revealed cancer type- and stage-specific lipid signatures with diagnostic and prognostic relevance. We emphasize the dual potential of lipid metabolic pathways-particularly those involving phospholipids-as sources of clinically relevant biomarkers and therapeutic targets. Enzymes and transporters involved in these pathways have emerged as promising candidates for both diagnostic applications and pharmacological intervention. We also examine persistent challenges hindering the clinical translation of lipid-based approaches, including analytical variability, insufficient biological validation, and the lack of standardized integration into clinical workflows. Furthermore, the review explores strategies to overcome these barriers, highlighting the importance of incorporating lipidomics into multi-omics frameworks, supported by advanced computational tools and AI-driven analytics, to decipher the complexity of tumor-associated metabolic networks. We discuss how such integrative approaches can facilitate the identification of actionable metabolic targets, improve the specificity and robustness of lipid-based biomarkers, and enhance patient stratification in the context of precision oncology.

Plasma-based untargeted metabolomics reveals potential biomarkers for screening and distinguishing of ovarian tumors

Ovarian cancer (OC), a leading cause of gynecological cancer mortality, is frequently detected at advanced stages due to asymptomatic early progression. This study investigates plasma-based untargeted metabolomics for identifying biomarkers to screen and differentiate ovarian tumors (OT). Plasma samples from OC, benign ovarian tumors (BOT), and healthy controls (HC) were analyzed. Samples were randomized into train and test sets, with differential metabolites screened via two-tailed Student's t-test and partial least squares discriminant analysis. ROC models evaluated discriminatory capacity. Key metabolites demonstrated high predictive value: TMAO and hippuric acid distinguished OT from HC (AUC > 0.95), while linoleic acid, alpha-linolenic acid, and arachidonic acid (AUC > 0.9) further supported OT screening. Kynurenine differentiated OC from BOT (AUC = 0.808). Reduced levels of specific lysophosphatidylcholines (LPC (17:0/0:0), LPC (15:0/0:0)) also distinguished OT from HC (AUC = 0.771-0.89). These findings suggest plasma metabolomics holds promise for noninvasive biomarker discovery in OT screening and distinguishing between malignant and benign cases, though further validation of metabolite quantification is warranted prior to clinical application.

UPLC-Q-TOF-MS-based unbiased serum metabolomics investigation of cholangiocarcinoma

Objective

Cholangiocarcinoma (CCA) is a highly aggressive malignancy, and early diagnosis remains challenging. Metabolic biomarkers are increasingly recognized as promising tools for the early detection of cancer. However, a comprehensive exploration of metabolic alterations in CCA, especially from a global metabolic perspective, has yet to be fully realized. To identify reliable metabolic markers for the early diagnosis of CCA and to explore its potential pathogenesis through an in-depth analysis of global metabolism.

Methods

Serum samples from 30 CCA patients and 31 healthy individuals were analyzed using an unbiased UPLC-Q-TOF-MS based metabolomics approach. Principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) were applied to identify potential biomarkers. High-resolution MS/MS and available standards were used to further confirm the identified metabolites. A systematic metabolic pathway analysis was conducted to interpret the biological roles of these biomarkers and explore their relevance to CCA progression.

Results

A total of 25 marker metabolites were identified, including lysophosphatidylcholines (LysoPCs), phosphatidylcholines (PCs), organic acids, sphinganine, and ketoleucine. These metabolites effectively distinguished CCA patients from healthy controls, with an AUC of 0.995 for increased biomarkers and 0.992 for decreased biomarkers in positive mode. In negative mode, the AUC for increased and decreased biomarkers was 0.899 and 0.976, respectively. The metabolic pathway analysis revealed critical biological functions linked to these biomarkers, offering insights into the molecular mechanisms underlying CCA initiation and progression.

Conclusion

This study identifies novel metabolic biomarkers for the early diagnosis of CCA and provides a deeper understanding of the metabolic alterations associated with the disease. These findings could contribute to the development of diagnostic strategies and therapeutic interventions for CCA.

FASN promotes lipid metabolism and progression in colorectal cancer via the SP1/PLA2G4B axis

Abnormal metabolic reprogramming is essential for tumorigenesis, metastasis, and the regulation of immune responses. Fatty acid synthase (FASN), a key enzyme in lipid metabolism, plays a crucial role in these processes. However, the relationship between FASN-mediated lipid reprogramming and the immune response in colorectal cancer (CRC) remains unclear. The present study demonstrated that FASN expression is elevated in CRC tissues and is significantly associated with poor prognosis. Functional experiments revealed that FASN promotes proliferation, migration, invasion, and phosphatidylcholine (PC) production in CRC cells. Additionally, in vivo experiments revealed that FASN knockdown significantly inhibits tumor growth and the spread of CRC cells to the lungs. Mechanistically, FASN, which is upregulated in CRC tissues, drives cancer cell proliferation, metastasis, and PC metabolism through the SP1/PLA2G4B axis, subsequently suppressing the antitumor response of natural killer (NK) cells in a PC-dependent manner. These findings provide new insights into lipid metabolism and the immunobiology of CRC, suggesting potential targets for the treatment and prevention of CRC. Schematic diagram showing the mechanism by which FASN promotes cancer cell proliferation, metastasis, and PC metabolism in CRC via the SP1/PLA2G4B axis, subsequently suppressing the antitumor response of NK cells in a PC-dependent manner. FFA free fatty acid, LPA lysophosphatidic acid, PA phosphatidate, DAG diglyceride, PC phosphatidylcholine, LPC lysophosphatidylcholine, CE cholesterol ester, TAG triacylglycerol.

Identification of metabolite biomarkers for pancreatic neuroendocrine tumours using a metabolomic approach

IMPORTANCE

Metabolic flexibility, a key hallmark of cancer, reflects aberrant tumour changes associated with metabolites. The metabolic plasticity of pancreatic neuroendocrine tumours (pNETs) remains largely unexplored. Notably, the heterogeneity of pNETs complicates their diagnosis, prognosis, and therapeutic management.

OBJECTIVE

Here, we compared the plasma metabolomic profiles of patients with pNET and non-cancerous individuals to understand metabolic dysregulation.

DESIGN, SETTING, PARTICIPANTS, INTERVENTION AND MEASURE

Plasma metabolic profiles of 76 patients with pNETs and 38 non-cancerous individuals were analyzed using LC-MS/MS and FIA-MS/MS (Biocrates AbsoluteIDQ p180 kit). Statistical analyses, including univariate and multivariate methods, were performed along with the generation of receiver operating characteristic (ROC) curves for metabolomic signature identification.

RESULTS

Compared with non-cancerous individuals, patients with pNET exhibited elevated levels of phosphoglyceride metabolites and reduced acylcarnitine levels, indicating an upregulation of fatty acid oxidation (FAO), which is crucial for the energy metabolism of pNET cells and one-carbon metabolism metabolites. Elevated glutamate levels and decreased lipid metabolite levels have been observed in patients with metastatic pNETs. Patients with the germline MEN1 mutations showed lower amino acid metabolites and FAO, with increased metabolites related to leucine catabolism and lipid metabolism, compared to non-MEN1 mutated patients. The highest area under the ROC curve was observed in patients with pNET harbouring MEN1 mutations.

CONCLUSION AND RELEVANCE

This study highlights the distinct plasma metabolic signatures of pNETs, including the critical role of FAO and elevated glutamate levels in metastasis, supporting the energy and biosynthetic needs of rapidly proliferating tumour cells. Mapping of these dysregulated metabolites may facilitate the identification of new therapeutic targets for pNETs management.

Diagnostic Accuracy of Ambient Mass Spectrometry with Blood Plasma in a Murine Glioma Model Using Machine Learning

OBJECTIVE

Malignant glioma progresses rapidly and shows poor prognosis, but clinically applicable blood plasma-based biochemical tumor markers remain lacking. This study aimed to develop a diagnostic system using probe electrospray ionization mass spectrometry (PESI-MS) and a machine-learning logistic regression model to detect plasma changes at various time points in a murine glioma model.

METHODS

We used a syngeneic intracranial orthotopic murine model with GL261 glioma cells. Blood plasmas were collected before and 3, 7, and 14 days after intracranial transplantation of glioma cells (tumor group, n = 7) or injection of phosphate-buffered saline (control group, n = 8). Mass spectra from those samples were obtained using PESI-MS and compared between control and tumor groups. We explored changes in mass spectra at the 3 time points (3, 7, and 14 days) after transplantation. The performance of machine-learning logistic regression-based diagnosis algorithm was evaluated to clarify the potential utility for early diagnosis.

RESULTS

Sixteen significant mass spectrum peaks were identified between the tumor and control groups. Multiple logistic regression analysis revealed 5 key mass spectra, achieving sensitivity of 0.875 and specificity of 0.943 for tumor discrimination. The area under the receiver operating characteristic curve was 0.981, outperforming analyses of individual spectra.

CONCLUSIONS

These results indicate that PESI-MS combined with machine learning-based diagnostics in blood plasma could be a promising approach to accurate detection of malignant glioma.

Evaluation of Lipid Changes During the Drying Process of Cordyceps sinensis by Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS)-Based Lipidomics Technique

Comprehensive analysis of the lipid content in Cordyceps sinensis samples is essential for optimizing their effective use. Understanding the lipid profile can significantly enhance the application of this valuable fungus across various fields, including nutrition and medicine. However, to date, there is limited knowledge regarding the effects of different drying methods on the quality of lipids present in Cordyceps sinensis. In this study, we employed a broadly targeted lipidomic strategy to conduct a comprehensive analysis of the lipid composition in Cordyceps sinensis subjected to various drying methods. A comprehensive analysis identified a total of 765 distinct lipid species from fresh Cordyceps sinensis (FC), vacuum-freeze-dried Cordyceps sinensis (VG), oven-dried Cordyceps sinensis (OG), and air-dried Cordyceps sinensis (AG). Among these, glycerophospholipids (GP) were the most abundant, followed by glycerides (GL) and sphingolipids (SP). In this study, a total of 659 lipids demonstrated statistically significant differences, as indicated by a p-value (p) < 1. Among these lipids, triglycerides (TG) exhibited the highest concentration, followed by several others, including ceramide-ascorbic acid (Cer-AS), phosphatidylethanolamine (PE), lysophosphatidylcholine (LPC), and phosphatidylserine (PS). OG was the fastest drying method; however, PCA and OPLS-DA analyses indicated that the most significant changes in the lipids of Cordyceps sinensis were observed under the OG method. Specifically, 517 differentially accumulated lipids were significantly down-regulated, while only 10 lipids were significantly up-regulated. This disparity may be attributed to the degradation and oxidation of lipids. The metabolic pathways of glycerolipid, glycerophospholipid, and cholesterol are critical during the drying process of Cordyceps sinensis. This study provides valuable insights that can enhance quality control and offer guidelines for the appropriate storage of this medicinal fungus.

Dietary fructose enhances tumour growth indirectly via interorgan lipid transfer

Fructose consumption has increased considerably over the past five decades, largely due to the widespread use of high-fructose corn syrup as a sweetener1. It has been proposed that fructose promotes the growth of some tumours directly by serving as a fuel2,3. Here we show that fructose supplementation enhances tumour growth in animal models of melanoma, breast cancer and cervical cancer without causing weight gain or insulin resistance. The cancer cells themselves were unable to use fructose readily as a nutrient because they did not express ketohexokinase-C (KHK-C). Primary hepatocytes did express KHK-C, resulting in fructolysis and the excretion of a variety of lipid species, including lysophosphatidylcholines (LPCs). In co-culture experiments, hepatocyte-derived LPCs were consumed by cancer cells and used to generate phosphatidylcholines, the major phospholipid of cell membranes. In vivo, supplementation with high-fructose corn syrup increased several LPC species by more than sevenfold in the serum. Administration of LPCs to mice was sufficient to increase tumour growth. Pharmacological inhibition of ketohexokinase had no direct effect on cancer cells, but it decreased circulating LPC levels and prevented fructose-mediated tumour growth in vivo. These findings reveal that fructose supplementation increases circulating nutrients such as LPCs, which can enhance tumour growth through a cell non-autonomous mechanism.

Metabolomics analysis reveals resembling metabolites between humanized γδ TCR mice and human plasma

Gamma delta (γδ) T cells, which reside in mucosal and epithelial tissues, are integral to immune responses and are involved in various cancers, autoimmune, and infectious diseases. To study human γδ T cells to a translational level, we developed γδ humanized TCR-T1 (HuTCR-T1) mice using our TruHumanization platform. We compared the metabolomic profiles from plasma samples of wild-type (WT), γδ HuTCR-T1 mice, and humans using UHPLC-MS/MS. Untargeted metabolomics and lipidomics were used to screen all detectable metabolites. Principal component analysis revealed that the metabolomic profiles of γδ HuTCR-T1 mice closely resemble those of humans, with a clear segregation of metabolites between γδ HuTCR-T1 and WT mice. Most humanized γδ metabolites were classified as lipids, followed by organic compounds and amino acids. Pathway analysis identified significant alterations in the metabolism of tryptophan, tyrosine, sphingolipids, and glycerophospholipids, shifting these pathways towards a more human-like profile. Immunophenotyping showed that γδ HuTCR-T1 mice maintained normal proportions of both lymphoid and myeloid immune cell populations, closely resembling WT mice, with only a few exceptions. These findings demonstrate that the γδ HuTCR-T1 mouse model exhibits a metabolomic profile that is remarkably similar to that of humans, highlighting its potential as a relevant model for investigating the role of metabolites in disease development and progression. This model also offers an opportunity to discover therapeutic human TCRs.

Combining metabolomics and machine learning to discover biomarkers for early-stage breast cancer diagnosis

There is an urgent need for better biomarkers for the detection of early-stage breast cancer. Utilizing untargeted metabolomics and lipidomics in conjunction with advanced data mining approaches for metabolism-centric biomarker discovery and validation may enhance the identification and validation of novel biomarkers for breast cancer screening. In this study, we employed a multimodal omics approach to identify and validate potential biomarkers capable of differentiating between patients with breast cancer and those with benign tumors. Our findings indicated that ether-linked phosphatidylcholine exhibited a significant difference between invasive ductal carcinoma and benign tumors, including cases with inconsistent mammography results. We observed alterations in numerous lipid species, including sphingomyelin, triacylglycerol, and free fatty acids, in the breast cancer group. Furthermore, we identified several dysregulated hydrophilic metabolites in breast cancer, such as glutamate, glycochenodeoxycholate, and dimethyluric acid. Through robust multivariate receiver operating characteristic analysis utilizing machine learning models, either linear support vector machines or random forest models, we successfully distinguished between cancerous and benign cases with promising outcomes. These results emphasize the potential of metabolic biomarkers to complement other criteria in breast cancer screening. Future studies are essential to further validate the metabolic biomarkers identified in our study and to develop assays for clinical applications.

Gut microbiome and plasma lipidome analysis reveals a specific impact of Clostridioides difficile infection on intestinal bacterial communities and sterol metabolism

Clostridioides difficile infection (CDI) causes alterations in the intestinal microbiota, frequently associated with changes in the gut metabolism of bile acids and cholesterol. In addition to the impact on microbiome composition and given the metabolic changes occurring during CDI, our work focuses on the importance to know the effects at the local and systemic levels, both during the infection and its treatment, by paying particular attention to plasma lipid metabolism due to its relationship with CDI pathogenesis. Specific changes, characterized by a loss of microbial richness and diversity and related to a reduction in short-chain acid-producing bacteria and an increase in bile salt hydrolase-producing bacteria, were observed in the gut microbiota of CDI patients, especially in those suffering from recurrent CDI (RCDI). However, gut microbiota showed its ability to restore itself after treatment, resembling healthy individuals, in those patients treated by fecal microbiome transfer (FMT), in contrast with those treated with antibiotics, and displaying increased levels of Eubacterium coprostanoligenes, a cholesterol-reducing anaerobe. Interestingly, changes in plasma lipidome revealed a global depletion in circulating lipids in CDI, with the largest impact on cholesteryl esters. CDI patients also showed a specific and consistent decrease in the levels of lipid species containing linoleic acid-an essential fatty acid-which were only partially recovered after antibiotic treatment. Analysis of the plasma lipidome reflects CDI impact on the gut microbiota and its metabolism, evidencing changes in sterol and fatty acid metabolism that are possibly related to specific alterations observed in gut microbial communities of CDI patients.

IMPORTANCE

There is increasing evidence about the influence the changes in microbiota and its metabolism has on numerous diseases and infections such as Clostridioides difficile infection (CDI). The knowledge of these changes at local and systemic levels can help us manage this infection to avoid recurrences and apply the best therapies, such as fecal microbiota transfer (FMT). This study shows a better restoration of the gut in FMT-treated patients than in antibiotic-treated patients, resembling healthy controls and showing increased levels of cholesterol-reducing bacteria. Furthermore, it evidences the CDI impact on plasma lipidome. We observed in CDI patients a global depletion in circulating lipids, particularly cholesteryl esters, and a specific decrease in linoleic acid-containing lipids, an essential fatty acid. Our observations could impact CDI management because the lipid content was only partially recovered after treatment, suggesting that continued nutritional support, aiming to restore healthy lipid levels, could be essential for a full recovery.

Lipid biomarkers in colorectal cancer, with particular emphasis on exosomes - current status and future inferences

INTRODUCTION

Colorectal cancer (CRC) is one of the most deadly cancers on a global scale. Diagnosis of CRC is challenging and it is often detected at a late stage. Identification of relevant biomarkers could lead to the development of effective diagnostic methods for CRC.

AREAS COVERED

We reviewed the literature on lipid (including exosomal) biomarkers that have the potential to become common, minimally invasive and effective diagnostic tools for CRC. We showed that differences in lipid levels (single compounds and entire panels) make it possible to classify patients into diseased or healthy groups, determine the stage of CRC, as well as accompanying inflammation and immune reactions associated with tumorigenesis. We also discussed exosomes which are important components of the tumor microenvironment that influence tumor progression and for which only a small number of studies were conducted so far in this area.

EXPERT OPINION

A rapid development in the field of lipid-based biomarkers, including exosomal lipid biomarkers, is expected as growing evidence shows their potential application and good accuracy. However, one of the major issues that needs to be addressed within this topic is to translate findings into a noninvasive and versatile diagnostic test robustly validated in clinical conditions.

"Find Me" and "Eat Me" signals: tools to drive phagocytic processes for modulating antitumor immunity

Phagocytosis, a vital defense mechanism, involves the recognition and elimination of foreign substances by cells. Phagocytes, such as neutrophils and macrophages, rapidly respond to invaders; macrophages are especially important in later stages of the immune response. They detect "find me" signals to locate apoptotic cells and migrate toward them. Apoptotic cells then send "eat me" signals that are recognized by phagocytes via specific receptors. "Find me" and "eat me" signals can be strategically harnessed to modulate antitumor immunity in support of cancer therapy. These signals, such as calreticulin and phosphatidylserine, mediate potent pro-phagocytic effects, thereby promoting the engulfment of dying cells or their remnants by macrophages, neutrophils, and dendritic cells and inducing tumor cell death. This review summarizes the phagocytic "find me" and "eat me" signals, including their concepts, signaling mechanisms, involved ligands, and functions. Furthermore, we delineate the relationships between "find me" and "eat me" signaling molecules and tumors, especially the roles of these molecules in tumor initiation, progression, diagnosis, and patient prognosis. The interplay of these signals with tumor biology is elucidated, and specific approaches to modulate "find me" and "eat me" signals and enhance antitumor immunity are explored. Additionally, novel therapeutic strategies that combine "find me" and "eat me" signals to better bridge innate and adaptive immunity in the treatment of cancer patients are discussed.

Distinctive Lipid Characteristics of Colorectal Cancer Revealed through Non-targeted Lipidomics Analysis of Tongue Coating

The metabolites and microbiota in tongue coating display distinct characteristics in certain digestive disorders, yet their relationship with colorectal cancer (CRC) remains unexplored. Here, we employed liquid chromatography coupled with tandem mass spectrometry to analyze the lipid composition of tongue coating using a nontargeted approach in 30 individuals with colorectal adenomas (CRA), 32 with CRC, and 30 healthy controls (HC). We identified 21 tongue coating lipids that effectively distinguished CRC from HC (AUC = 0.89), and 9 lipids that differentiated CRC from CRA (AUC = 0.9). Furthermore, we observed significant alterations in the tongue coating lipid composition in the CRC group compared to HC/CRA groups. As the adenoma-cancer sequence progressed, there was an increase in long-chain unsaturated triglycerides (TG) levels and a decrease in phosphatidylethanolamine plasmalogen (PE-P) levels. Furthermore, we noted a positive correlation between N-acyl ornithine (NAOrn), sphingomyelin (SM), and ceramide phosphoethanolamine (PE-Cer), potentially produced by members of the Bacteroidetes phylum. The levels of inflammatory lipid metabolite 12-HETE showed a decreasing trend with colorectal tumor progression, indicating the potential involvement of tongue coating microbiota and tumor immune regulation in early CRC development. Our findings highlight the potential utility of tongue coating lipid analysis as a noninvasive tool for CRC diagnosis.

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

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

Lysophosphatidylserine: A Signaling Lipid with Implications in Human Diseases

Lysophosphatidylserine (lyso-PS) has emerged as yet another important signaling lysophospholipid in mammals, and deregulation in its metabolism has been directly linked to an array of human autoimmune and neurological disorders. It has an indispensable role in several biological processes in humans, and therefore, cellular concentrations of lyso-PS are tightly regulated to ensure optimal signaling and functioning in physiological settings. Given its biological importance, the past two decades have seen an explosion in the available literature toward our understanding of diverse aspects of lyso-PS metabolism and signaling and its association with human diseases. In this Review, we aim to comprehensively summarize different aspects of lyso-PS, such as its structure, biodistribution, chemical synthesis, and SAR studies with some synthetic analogs. From a biochemical perspective, we provide an exhaustive coverage of the diverse biological activities modulated by lyso-PSs, such as its metabolism and the receptors that respond to them in humans. We also briefly discuss the human diseases associated with aberrant lyso-PS metabolism and signaling and posit some future directions that may advance our understanding of lyso-PS-mediated mammalian physiology.

Alterations in Plasma Lipid Profile before and after Surgical Removal of Soft Tissue Sarcoma

Soft tissue sarcoma (STS) is a relatively rare malignancy, accounting for about 1% of all adult cancers. It is known to have more than 70 subtypes. Its rarity, coupled with its various subtypes, makes early diagnosis challenging. The current standard treatment for STS is surgical removal. To identify the prognosis and pathophysiology of STS, we conducted untargeted metabolic profiling on pre-operative and post-operative plasma samples from 24 STS patients who underwent surgical tumor removal. Profiling was conducted using ultra-high-performance liquid chromatography-quadrupole time-of-flight/mass spectrometry. Thirty-nine putative metabolites, including phospholipids and acyl-carnitines were identified, indicating changes in lipid metabolism. Phospholipids exhibited an increase in the post-operative samples, while acyl-carnitines showed a decrease. Notably, the levels of pre-operative lysophosphatidylcholine (LPC) O-18:0 and LPC O-16:2 were significantly lower in patients who experienced recurrence after surgery compared to those who did not. Metabolic profiling may identify aggressive tumors that are susceptible to lipid synthase inhibitors. We believe that these findings could contribute to the elucidation of the pathophysiology of STS and the development of further metabolic studies in this rare malignancy.

Identification of novel biomarkers in the early diagnosis of malignant melanoma by untargeted liquid chromatography coupled to high-resolution mass spectrometry-based metabolomics: a pilot study

BACKGROUND

Malignant melanoma (MM) is a highly aggressive form of skin cancer whose incidence continues to rise worldwide. If diagnosed at an early stage, it has an excellent prognosis, but mortality increases significantly at advanced stages after distant spread. Unfortunately, early detection of aggressive melanoma remains a challenge.

OBJECTIVES

To identify novel blood-circulating biomarkers that may be useful in the diagnosis of MM to guide patient counselling and appropriate disease management.

METHODS

In this study, 105 serum samples from 26 healthy patients and 79 with MM were analysed using an untargeted approach by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to compare the metabolomic profiles of both conditions. Resulting data were subjected to both univariate and multivariate statistical analysis to select robust biomarkers. The classification model obtained from this analysis was further validated with an independent cohort of 12 patients with stage I MM.

RESULTS

We successfully identified several lipidic metabolites differentially expressed in patients with stage I MM vs. healthy controls. Three of these metabolites were used to develop a classification model, which exhibited exceptional precision (0.92) and accuracy (0.94) when validated on an independent sample.

CONCLUSIONS

These results demonstrate that metabolomics using LC-HRMS is a powerful tool to identify and quantify metabolites in bodily fluids that could serve as potential early diagnostic markers for MM.

Identification of Plasma Lipid Alterations Associated with Melanoma Metastasis

The aim of this study was to apply a state-of-the-art quantitative lipidomic profiling platform to uncover lipid alterations predictive of melanoma progression. Our study included 151 melanoma patients; of these, 83 were without metastasis and 68 with metastases. Plasma samples were analyzed using a targeted Lipidyzer™ platform, covering 13 lipid classes and over 1100 lipid species. Following quality control filters, 802 lipid species were included in the subsequent analyses. Total plasma lipid contents were significantly reduced in patients with metastasis. Specifically, levels of two out of the thirteen lipid classes (free fatty acids (FFAs) and lactosylceramides (LCERs)) were significantly decreased in patients with metastasis. Three lipids (CE(12:0), FFA(24:1), and TAG47:2-FA16:1) were identified as more effective predictors of melanoma metastasis than the well-known markers LDH and S100B. Furthermore, the predictive value substantially improved upon combining the lipid markers. We observed an increase in the cumulative levels of five lysophosphatidylcholines (LPC(16:0); LPC(18:0); LPC(18:1); LPC(18:2); LPC(20:4)), each individually associated with an elevated risk of lymph node metastasis but not cutaneous or distant metastasis. Additionally, seventeen lipid molecules were linked to patient survival, four of which (CE(12:0), CE(14:0), CE(15:0), SM(14:0)) overlapped with the lipid panel predicting metastasis. This study represents the first comprehensive investigation of the plasma lipidome of melanoma patients to date. Our findings suggest that plasma lipid profiles may serve as important biomarkers for predicting clinical outcomes of melanoma patients, including the presence of metastasis, and may also serve as indicators of patient survival.

Profiling of serum metabolome of breast cancer: multi-cancer features discriminate between healthy women and patients with breast cancer

Introduction

The progression of solid cancers is manifested at the systemic level as molecular changes in the metabolome of body fluids, an emerging source of cancer biomarkers.

Methods

We analyzed quantitatively the serum metabolite profile using high-resolution mass spectrometry. Metabolic profiles were compared between breast cancer patients (n=112) and two groups of healthy women (from Poland and Norway; n=95 and n=112, respectively) with similar age distributions.

Results

Despite differences between both cohorts of controls, a set of 43 metabolites and lipids uniformly discriminated against breast cancer patients and healthy women. Moreover, smaller groups of female patients with other types of solid cancers (colorectal, head and neck, and lung cancers) were analyzed, which revealed a set of 42 metabolites and lipids that uniformly differentiated all three cancer types from both cohorts of healthy women. A common part of both sets, which could be called a multi-cancer signature, contained 23 compounds, which included reduced levels of a few amino acids (alanine, aspartate, glutamine, histidine, phenylalanine, and leucine/isoleucine), lysophosphatidylcholines (exemplified by LPC(18:0)), and diglycerides. Interestingly, a reduced concentration of the most abundant cholesteryl ester (CE(18:2)) typical for other cancers was the least significant in the serum of breast cancer patients. Components present in a multi-cancer signature enabled the establishment of a well-performing breast cancer classifier, which predicted cancer with a very high precision in independent groups of women (AUC>0.95).

Discussion

In conclusion, metabolites critical for discriminating breast cancer patients from controls included components of hypothetical multi-cancer signature, which indicated wider potential applicability of a general serum metabolome cancer biomarker.

Cationic amphiphilic drugs induce accumulation of cytolytic lysoglycerophospholipids in the lysosomes of cancer cells and block their recycling into common membrane glycerophospholipids

Lysosomes are acidic organelles responsible for lipid catabolism, and their functions can be disrupted by cationic amphiphilic drugs that neutralize lumenal pH and thereby inhibit most lysosomal hydrolases. These drugs can also induce lysosomal membrane permeabilization and cancer cell death, but the underlying mechanism remains elusive. Here, we uncover that the cationic amphiphilic drugs induce a substantial accumulation of cytolytic lysoglycerophospholipids within the lysosomes of cancer cells, and thereby prevent the recycling of lysoglycerophospholipids to produce common membrane glycerophospholipids. Using quantitative mass spectrometry-based shotgun lipidomics, we demonstrate that structurally diverse cationic amphiphilic drugs, along with other types of lysosomal pH-neutralizing reagents, elevate the amounts of lysoglycerophospholipids in MCF7 breast carcinoma cells. Lysoglycerophospholipids constitute ∼11 mol% of total glycerophospholipids in lysosomes purified from MCF7 cells, compared with ∼1 mol% in the cell lysates. Treatment with cationic amphiphilic drug siramesine further elevates the lysosomal lysoglycerophospholipid content to ∼24 mol% of total glycerophospholipids. Exogenously added traceable lysophosphatidylcholine is rapidly acylated to form diacylphosphatidylcholine, but siramesine treatment sequesters the lysophosphatidylcholine in the lysosomes and prevents it from undergoing acylation. These findings shed light on the unexplored role of lysosomes in the recycling of lysoglycerophospholipids and uncover the mechanism of action of promising anticancer agents.

Circulating metabolic markers after surgery identify patients at risk for severe postoperative complications: a prospective cohort study in colorectal cancer

BACKGROUND

Early detection of postoperative complications after colorectal cancer (CRC) surgery is associated with improved outcomes. The aim was to investigate early metabolomics signatures capable to detect patients at risk for severe postoperative complications after CRC surgery.

MATERIALS AND METHODS

Prospective cohort study of patients undergoing CRC surgery from 2015 to 2018. Plasma samples were collected before and after surgery, and analyzed by mass spectrometry obtaining 188 metabolites and 21 ratios. Postoperative complications were registered with Clavien-Dindo Classification and Comprehensive Complication Index.

RESULTS

One hundred forty-six patients were included. Surgery substantially modified metabolome and metabolic changes after surgery were quantitatively associated with the severity of postoperative complications. The strongest positive relationship with both Clavien-Dindo and Comprehensive Complication Index (β=4.09 and 63.05, P <0.001) corresponded to kynurenine/tryptophan, against an inverse relationship with lysophosphatidylcholines (LPCs) and phosphatidylcholines (PCs). Patients with LPC18:2/PCa36:2 below the cut-off 0.084 µM/µM resulted in a sevenfold higher risk of major complications (OR=7.38, 95% CI: 2.82-21.25, P <0.001), while kynurenine/tryptophan above 0.067 µM/µM a ninefold (OR=9.35, 95% CI: 3.03-32.66, P <0.001). Hexadecanoylcarnitine below 0.093 µM displayed a 12-fold higher risk of anastomotic leakage-related complications (OR=11.99, 95% CI: 2.62-80.79, P =0.004).

CONCLUSION

Surgery-induced phospholipids and amino acid dysregulation is associated with the severity of postoperative complications after CRC surgery, including anastomotic leakage-related outcomes. The authors provide quantitative insight on metabolic markers, measuring vulnerability to postoperative morbidity that might help guide early decision-making and improve surgical outcomes.

Metabolomic Signatures of Exposure to Nitrate and Trihalomethanes in Drinking Water and Colorectal Cancer Risk in a Spanish Multicentric Study (MCC-Spain)

We investigated the metabolomic profile associated with exposure to trihalomethanes (THMs) and nitrate in drinking water and with colorectal cancer risk in 296 cases and 295 controls from the Multi Case-Control Spain project. Untargeted metabolomic analysis was conducted in blood samples using ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. A variety of univariate and multivariate association analyses were conducted after data quality control, normalization, and imputation. Linear regression and partial least-squares analyses were conducted for chloroform, brominated THMs, total THMs, and nitrate among controls and for case-control status, together with a N-integration model discriminating colorectal cancer cases from controls through interrogation of correlations between the exposure variables and the metabolomic features. Results revealed a total of 568 metabolomic features associated with at least one water contaminant or colorectal cancer. Annotated metabolites and pathway analysis suggest a number of pathways as potentially involved in the link between exposure to these water contaminants and colorectal cancer, including nicotinamide, cytochrome P-450, and tyrosine metabolism. These findings provide insights into the underlying biological mechanisms and potential biomarkers associated with water contaminant exposure and colorectal cancer risk. Further research in this area is needed to better understand the causal relationship and the public health implications.

UHPLC-HRMS-based serum untargeted lipidomics: Phosphatidylcholines and sphingomyelins are the main disturbed lipid markers to distinguish colorectal advanced adenoma from cancer

Colorectal advanced adenoma (CAA) is a key precancerous lesion of colorectal cancer (CRC), and early diagnosis can lessen CRC morbidity and mortality. Although abnormal lipid metabolism is associated with the development of CRC, there are no studies on the biomarkers and mechanism of lipid metabolism linked to CAA carcinogenesis. Hence, we performed a lipidomics study of serum samples from 46 CAA, and 50 CRC patients by the ultra high-performance liquid chromatography tandem high resolution mass spectrometry (UHPLC-HRMS) in both electrospray ionization (ESI) modes. Differential lipids were selected by univariate and multivariate statistics analysis, and their diagnostic performance was evaluated using a receiver operating characteristic curve (ROC) analysis. Combining P < 0.05 and variable importance in projection (VIP) > 1, 59 differential lipids were obtained totally. Ten of them showed good discriminant ability for CAA and CRC (AUC > 0.900). Especially, the lipid panel consisting of PC 44:5, PC 35:6e, and SM d40:3 showed the highest selection frequency and outperformed (AUC = 0.952). Additionally, phosphatidylcholine (PC) and sphingomyelin (SM) were the main differential and high-performance lipids. In short, this is the first study to explore the biomarkers and mechanism for CAA-CRC sequence with large-scale serum lipidomics. The findings should provide valuable reference and new clues for the development of diagnostic and therapeutic strategies of CRC.

Probing interaction of atherogenic lysophosphatidylcholine with functionalized graphene nanosheets: theoretical modelling and experimental validation

CONTEXT

The potential of graphene derivatives for theranostic applications depends on their compatibility with cellular and biomolecular components. Lysophosphatidylcholine (LPC), a lipid component present in oxidized low-density lipoproteins, microvesicles and free circulation in blood, plays a critical role in the pathophysiology of various diseases. Using density functional theory-based methods, we systematically investigated the interaction of atherogenic LPC molecule with different derivatives of graphene, including pristine graphene, graphene with defect, N-doped graphene, amine-functionalized graphene, various graphene oxides and hydroxylated graphene oxides. We observed that the adsorption of LPC on graphene derivatives is highly selective based on the orientation of the functional groups of LPC interacting with the surface of the derivatives. Hydroxylated graphene oxide exhibited the strongest interaction with LPC with adsorption energy of - 2.1 eV due to the interaction between the hydroxyl group on graphene and the phosphate group of LPC. The presence of aqueous medium further enhanced this interaction indicating favourable adsorption of LPC and graphene oxide in biological systems. Such strong interaction leads to substantial change in the electronic structure of the LPC molecule, which results in the activation of this molecule. In contrast, amine-modified graphene showed the least interaction. These theoretical results are in line with our experimental fluorescence spectroscopic data of LPC/1-anilino-8-napthalene sulfonic acid complex. Our present comprehensive investigation employing both theoretical and experimental methods provides a deeper understanding of graphene-lipid interaction, which holds paramount importance in the design and fabrication of graphene-based nanomaterials for biomedical applications.

METHODS

In this study, we employed the density functional theory-based methods to investigate the electronic and structural properties of graphene derivatives and LPC molecule using the Quantum Espresso package. The exchange-correlation functional was described within generalized gradient approximation (GGA) as parameterized by Perdew, Burke and Ernzerhof (PBE). The valence electrons were represented using plane wave basis sets. `The Grimme's dispersion method was used to include the van der Waals dispersion correction.

Paired microbiome and metabolome analyses associate bile acid changes with colorectal cancer progression

Colorectal cancer (CRC) is driven by genomic alterations in concert with dietary influences, with the gut microbiome implicated as an effector in disease development and progression. While meta-analyses have provided mechanistic insight into patients with CRC, study heterogeneity has limited causal associations. Using multi-omics studies on genetically controlled cohorts of mice, we identify diet as the major driver of microbial and metabolomic differences, with reductions in α diversity and widespread changes in cecal metabolites seen in high-fat diet (HFD)-fed mice. In addition, non-classic amino acid conjugation of the bile acid cholic acid (AA-CA) increased with HFD. We show that AA-CAs impact intestinal stem cell growth and demonstrate that Ileibacterium valens and Ruminococcus gnavus are able to synthesize these AA-CAs. This multi-omics dataset implicates diet-induced shifts in the microbiome and the metabolome in disease progression and has potential utility in future diagnostic and therapeutic developments.

Rectal Cancer Tissue Lipidome Differs According to Response to Neoadjuvant Therapy

Rectal cancer (RC) is a gastrointestinal cancer with a poor prognosis. While some studies have shown metabolic reprogramming to be linked to RC development, it is difficult to define biomolecules, like lipids, that help to understand cancer progression and response to therapy. The present study investigated the relative lipid abundance in tumoral tissue associated with neoadjuvant therapy response using untargeted liquid chromatography-mass spectrometry lipidomics. Locally advanced rectal cancer (LARC) patients (n = 13), clinically staged as T3-4 were biopsied before neoadjuvant chemoradiotherapy (nCRT). Tissue samples collected before nCRT (staging) and afterwards (restaging) were analyzed to discover lipidomic differences in RC cancerous tissue from Responders (n = 7) and Non-responders (n = 6) to nCRT. The limma method was used to test differences between groups and to select relevant feature lipids from tissue samples. Simple glycosphingolipids and differences in some residues of glycerophospholipids were more abundant in the Non-responder group before and after nCRT. Oxidized glycerophospholipids were more abundant in samples of Non-responders, especially those collected after nCRT. This work identified potential lipids in tissue samples that take part in, or may explain, nCRT failure. These results could potentially provide a lipid-based explanation for nCRT response and also help in understanding the molecular basis of RC and nCRT effects on the tissue matrix.

Characterization of Lipid Alterations by Oncogenic PIK3CA Mutations Using Untargeted Lipidomics in Breast Cancer

Lipids play crucial biological roles in health and disease, including in cancers. The phosphatidylinositol 3-kinase (PI3K) signaling pathway is a pivotal promoter of cell growth and proliferation in various types of cancer. The somatic mutations in PIK3CA, the gene coding for the catalytic subunit p110α of PI3K, are frequently present in cancer cells, including breast cancer. Although the most prominent mutants, represented by single amino acid substitutions in the helical domain in exon 9 (E545K) and the kinase domain in exon 20 (H1047R) are known to cause a gain of PI3K function, activate AKT signaling and induce oncogenic transformation, the effect of these mutations on cellular lipid profiles has not been studied. We carried out untargeted lipidomics using liquid chromatography-tandem mass spectrometry to detect the lipid alterations in mammary gland epithelial MCF10A cells with isogenic knockin of these mutations. A total of 536 species of lipids were analyzed. We found that the levels of monosialogangliosides, signaling molecules known to enhance cell motility through PI3K/AKT pathway, were significantly higher in both mutants. In addition, triglycerides and ceramides, lipid molecules known to be involved in promoting lipid droplet production, cancer cell migration and invasion, were increased, whereas lysophosphatidylcholines and phosphatidylcholines that are known to inhibit cancer cell motility were decreased in both mutants. Our results provide novel insights into a potential link between altered lipid profile and carcinogenesis caused by the PIK3CA hotspot mutations. In addition, we suggest untargeted lipidomics offers prospects for precision/personalized medicine by unpacking new molecular substrates of cancer biology.

Metabolic profiles of lung adenocarcinoma via peripheral blood and diagnostic model construction

The metabolic profile of cancerous cells is shifted to meet the cellular demand required for proliferation and growth. Here we show the features of cancer metabolic profiles using peripheral blood of healthy control subjects (n = 78) and lung adenocarcinoma (LUAD) patients (n = 64). Among 121 detected metabolites, diagnosis of LUAD is based on arginine, lysophosphatidylcholine-acyl (Lyso.PC.a) C16:0, and PC-diacyl (PC.aa) C38:3. Network analysis revealed that network heterogeneity, diameter, and shortest path were decreased in LUAD. On the contrary, these parameters were increased in advanced-stage compared to early-stage LUAD. Clustering coefficient, network density, and average degree were increased in LUAD compared to the healthy control, whereas these topologic parameters were decreased in advanced-stage compared to early-stage LUAD. Public LUAD data verified that the genes encoding enzymes for arginine (NOS, ARG, AZIN) and for Lyso.PC and PC (CHK, PCYT, LPCAT) were related with overall survival. Further studies are required to verify these results with larger samples and other histologic types of lung cancer.

Lysophospholipids and their producing enzymes: Their pathological roles and potential as pathological biomarkers

Accumulating evidence suggests that lysophospholipids (LPL) serve as lipid mediators that exert their diverse pathophysiological functions via G protein-coupled receptors. These include lysophosphatidic acid (LPA), sphingosine 1-phosphate (S1P), lysophosphatidylserine (LysoPS) and lysophosphatidylinositol (LPI). Unlike S1P, which is produced intracellularly and secreted from various cell types, some LPLs, such as LPA, LysoPS and LPI, are produced in lesions, especially under pathological conditions, where they positively or negatively regulate disease progression through their autacoid-like actions. Although these LPLs are minor components of the cell membrane, recent developments in mass spectrometry techniques have made it possible to detect and quantify them in a variety of biological fluids, including plasma, serum, urine and cerebrospinal fluid. The synthetic enzymes of LPA and LysoPS are also present in these biological fluids, which also can be detected by antibody-based methods. Importantly, their levels have been found to dramatically increase during various pathological conditions. Thus, LPLs and their synthetic enzymes in these biological fluids are potential biomarkers. This review discusses the potential of these LPLs and LPL-related molecules as pathological biomarkers, including methods and problems in their measurement.

The Pathological Effects of Circulating Hydrophobic Bile Acids in Alzheimer's Disease

Recent clinical studies have revealed that the serum levels of toxic hydrophobic bile acids (deoxy cholic acid, lithocholic acid [LCA], and glycoursodeoxycholic acid) are significantly higher in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) when compared to control subjects. The elevated serum bile acids may be the result of hepatic peroxisomal dysfunction. Circulating hydrophobic bile acids are able to disrupt the blood-brain barrier and promote the formation of amyloid-β plaques through enhancing the oxidation of docosahexaenoic acid. Hydrophobic bile acid may find their ways into the neurons via the apical sodium-dependent bile acid transporter. It has been shown that hydrophobic bile acids impose their pathological effects by activating farnesoid X receptor and suppressing bile acid synthesis in the brain, blocking NMDA receptors, lowering brain oxysterol levels, and interfering with 17β-estradiol actions such as LCA by binding to E2 receptors (molecular modelling data exclusive to this paper). Hydrophobic bile acids may interfere with the sonic hedgehog signaling through alteration of cell membrane rafts and reducing brain 24(S)-hydroxycholesterol. This article will 1) analyze the pathological roles of circulating hydrophobic bile acids in the brain, 2) propose therapeutic approaches, and 3) conclude that consideration be given to reducing/monitoring toxic bile acid levels in patients with AD or aMCI, prior/in combination with other treatments.

Determination of lysophosphatidylcholine using peroxidase-mimic PVP/PtRu nanozyme

Lysophosphatidylcholine (LPC) can be used as a biomarker for diseases such as cancer, diabetes, atherosclerosis, and sepsis. In this study, we demonstrated the ability of nanozymes to displace the natural derived enzyme in enzyme-based assays for the measurement of LPC. Synthesized polyvinylpyrrolidone-stabilized platinum-ruthenium nanozymes (PVP/PtRu NZs) had a uniform size of 2.48 ± 0.24 nm and superb peroxidase-mimicking activity. We demonstrated that the nanozymes had high activity over a wide pH and temperature range and high stability after long-term storage. The LPC concentration could be accurately analyzed through the absorbance and fluorescence signals generated by the peroxidation reaction using the synthesized nanozyme with substrates such as 3,3',5,5'-tetramethylbenzidine (TMB) and 10-acetyl-3,7-dihydroxyphenoxazine (Ampliflu™ Red). LPC at a concentration of 0-400 µM was used for the analysis, and the coefficient of determination (R²) was 0.977, and the limit of detection (LOD) was 23.1 µM by colorimetric assay. In the fluorometric assay, the R² was 0.999, and the LOD was 8.97 µM. The spiked recovery values for the determination of LPC concentration in human serum samples were 102-115%. Based on these results, we declared that PVP/PtRu NZs had an ability comparable to that of the native enzyme horseradish peroxidase (HRP) in the enzyme-based LPC detection method.

The remodeling roles of lipid metabolism in colorectal cancer cells and immune microenvironment

Lipid is a key component of plasma membrane, which plays an important role in the regulation of various cell biological behaviors, including cell proliferation, growth, differentiation and intracellular signal transduction. Studies have shown that abnormal lipid metabolism is involved in many malignant processes, including colorectal cancer (CRC). Lipid metabolism in CRC cells can be regulated not only by intracellular signals, but also by various components in the tumor microenvironment, including various cells, cytokines, DNA, RNA, and nutrients including lipids. In contrast, abnormal lipid metabolism provides energy and nutrition support for abnormal malignant growth and distal metastasis of CRC cells. In this review, we highlight the remodeling roles of lipid metabolism crosstalk between the CRC cells and the components of tumor microenvironment.

Lipid Biomarkers in Liquid Biopsies: Novel Opportunities for Cancer Diagnosis

Altered cellular metabolism is a well-established hallmark of cancer. Although most studies have focused on the metabolism of glucose and glutamine, the upregulation of lipid metabolism is also frequent in cells undergoing oncogenic transformation. In fact, cancer cells need to meet the enhanced demand of plasma membrane synthesis and energy production to support their proliferation. Moreover, lipids are precursors of signaling molecules, termed lipid mediators, which play a role in shaping the tumor microenvironment. Recent methodological advances in lipid analysis have prompted studies aimed at investigating the whole lipid content of a sample (lipidome) to unravel the complexity of lipid changes in cancer patient biofluids. This review focuses on the application of mass spectrometry-based lipidomics for the discovery of cancer biomarkers. Here, we have summarized the main lipid alteration in cancer patients' biofluids and uncovered their potential use for the early detection of the disease and treatment selection. We also discuss the advantages of using biofluid-derived extracellular vesicles as a platform for lipid biomarker discovery. These vesicles have a molecular signature that is a fingerprint of their originating cells. Hence, the analysis of their molecular cargo has emerged as a promising strategy for the identification of sensitive and specific biomarkers compared to the analysis of the unprocessed biofluid.

Comparison between Sickle Cell Disease Patients and Healthy Donors: Untargeted Lipidomic Study of Erythrocytes

Sickle cell disease (SCD) is one of the most common severe monogenic disorders in the world caused by a mutation on HBB gene and characterized by hemoglobin polymerization, erythrocyte rigidity, vaso-occlusion, chronic anemia, hemolysis, and vasculopathy. Recently, the scientific community has focused on the multiple genetic and clinical profiles of SCD. However, the lipid composition of sickle cells has received little attention in the literature. According to recent studies, changes in the lipid profile are strongly linked to several disorders. Therefore, the aim of this study is to dig deeper into lipidomic analysis of erythrocytes in order to highlight any variations between healthy and patient subjects. 241 lipid molecular species divided into 17 classes have been annotated and quantified. Lipidomic profiling of SCD patients showed that over 24% of total lipids were altered most of which are phospholipids. In-depth study of significant changes in lipid metabolism can give an indication of the enzymes and genes involved. In a systems biology scenario, these variations can be useful to improve the understanding of the biochemical basis of SCD and to try to make a score system that could be predictive for the severity of clinical manifestations.

Standard Water Generating Vials for Lipophilic Compounds

The study of non-polar compounds in aqueous environments has always been challenging due to their poor solubility in aqueous media. The low affinity of non-polar compounds toward polar solutions facilitates their attachment to glassware, which results in unstable sample concentrations. To address this challenge, and to enable the preparation of a stable mixture of hydrophobic compounds in an aquatic environment, we introduce an in-vial standard water generating system consisting of a vial containing appropriate aqueous solution and a polydimethylsiloxane thin film spiked with target compounds. In this system, a solution with a stable analyte concentration is attained once equilibrium between the thin-film and aqueous solution has been achieved. The developed standard water system was studied using endocannabinoids and phospholipids as model hydrophobic compounds of biological importance, with results indicating that the concentration of hydrophobic compounds in water can remain stable over multiple days. The results also showed that analytes released from the thin film can compensate for analyte loss due to extractions with solid-phase microextraction fibers, thereby re-establishing equilibrium. Thus, the vial is suitable for the repeatable generation of non-polar standards for routine analysis and quality control. The results of this work show that the developed system is stable and reproducible and therefore appropriate for studies requiring the measurement of free concentrations and accurate quantification.

Lysophosphatidylcholine inhibits lung cancer cell proliferation by regulating fatty acid metabolism enzyme long-chain acyl-coenzyme A synthase 5

Lung cancer is a widespread malignancy with a high death rate and disorder of lipid metabolism. Lysophosphatidylcholine (lysoPC) has anti-tumour effects, although the underlying mechanism is not entirely known. The purpose of this study aims at defining changes in lysoPC in lung cancer patients, the effects of lysoPC on lung cancer cells and molecular mechanisms. Lung cancer cell sensitivity to lysoPC was evaluated and decisive roles of long-chain acyl-coenzyme A synthase 5 (ACSL5) in lysoPC regulation were defined by comprehensively evaluating transcriptomic changes of ACSL5-downregulated epithelia. ACSL5 over-expressed in ciliated, club and Goblet cells in lung cancer patients, different from other lung diseases. LysoPC inhibited lung cancer cell proliferation, by inducing mitochondrial dysfunction, altering lipid metabolisms, increasing fatty acid oxidation and reprograming ACSL5/phosphoinositide 3-kinase/extracellular signal-regulated kinase-regulated triacylglycerol-lysoPC balance. Thus, this study provides a general new basis for the discovery of reprogramming metabolisms and metabolites as a new strategy of lung cancer precision medicine.

Dietary inclusion of nitrite-containing frankfurter exacerbates colorectal cancer pathology and alters metabolism in APCmin mice

Colorectal cancer (CRC) is the second most prevelant malignancy in Europe and diet is an important modifiable risk factor. Processed meat consumption, including meats with preservative salts such as sodium nitrite, have been implicated in CRC pathogenesis. This study investigated how the CRC pathology and metabolic status of adenomatous polyposis coli (APC) multiple intestinal neoplasia (min) mice was perturbed following 8 weeks of pork meat consumption. Dietary inclusions (15%) of either nitrite-free pork, nitrite-free sausage, or nitrite-containing sausage (frankfurter) were compared against a parallel control group (100% chow). Comprehensive studies investigated: gastrointestinal tract histology (tumours), aberrant crypt foci (ACF), mucin deplin foci (MDF), lipid peroxidation (urine and serum), faecal microbiota, and serum metabolomics (599 metabolites). After 8 weeks mice consuming the frankfurter diet had 53% more (P = 0.014) gastrointestinal tumours than control, although ACF and MDF did not differ. Urine and serum lipid peroxidation markers were 59% (P = 0.001) and 108% (P = 0.001) higher, respectively in the frankfurter group. Gut dysbiosis was evident in these mice with comparably fewer Bacteriodes and more Firmicutes. Fasting serum levels of trimethylamine N-oxide (TMAO) and numerous triglycerides were elevated. Various serum phosphotidylcholine species were decreased. These results demonstrate that nitrite-containing sausages may exaccerbate the development of CRC pathology in APC^Min mice to a greater extent than nitrite-free sausages, and this is associated with greater lipid peroxidation, wide-ranging metabolic alternation and gut dysbiosis.

A polyamine-centric, blood-based metabolite panel predictive of poor response to CAR-T cell therapy in large B cell lymphoma

Anti-CD19 chimeric antigen receptor (CAR) T cell therapy for relapsed or refractory (r/r) large B cell lymphoma (LBCL) results in durable response in only a subset of patients. MYC overexpression in LBCL tumors is associated with poor response to treatment. We tested whether an MYC-driven polyamine signature, as a liquid biopsy, is predictive of response to anti-CD19 CAR-T therapy in patients with r/r LBCL. Elevated plasma acetylated polyamines were associated with non-durable response. Concordantly, increased expression of spermidine synthase, a key enzyme that regulates levels of acetylated spermidine, was prognostic for survival in r/r LBCL. A broad metabolite screen identified additional markers that resulted in a 6-marker panel (6MetP) consisting of acetylspermidine, diacetylspermidine, and lysophospholipids, which was validated in an independent set from another institution as predictive of non-durable response to CAR-T therapy. A polyamine centric metabolomics liquid biopsy panel has predictive value for response to CAR-T therapy in r/r LBCL.

Non-Targeted Serum Lipidomics Analysis and Potential Biomarkers of Laryngeal Cancer Based on UHPLC-QTOF-MS

Laryngeal cancer is a common head and neck malignant cancer type. However, effective biomarkers for diagnosis are lacking and pathogenesis is unclear. Lipidomics is a powerful tool for identifying biomarkers and explaining disease mechanisms. Hence, in this study, non-targeted lipidomics based on ultra-performance liquid chromatography-quadrupole time of flight-mass spectrometry (UHPLC-QTOF-MS) were applied to screen the differential lipid metabolites in serum and allowed for exploration of the remodeled lipid metabolism of laryngeal cancer, laryngeal benign tumor patients, and healthy crowds. Multivariate analysis and univariate analysis were combined to screen for differential lipid metabolites among the three groups. The results showed that, across a total of 57 lipid metabolic markers that were screened, the regulation of the lipid metabolism network occurred mainly in phosphatidylcholine (PC), lysophosphatidylcholine (LPC), and sphingomyelin (SM) metabolism. Of note, the concentration levels of sphingolipids 42:2 (SM 42:2) and sphingolipids 42:3 (SM 42:3) correlated with laryngeal cancer progression and were both significantly different among the three groups. Both of them could be considered as potential biomarkers for diagnosis and indicators for monitoring the progression of laryngeal cancer. From the perspective of lipidomics, this study not only revealed the regulatory changes in the lipid metabolism network, but also provided a new possibility for screening biomarkers in laryngeal cancer.

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.

Metabolic-Dysregulation-Based iEESI-MS Reveals Potential Biomarkers Associated with Early-Stage and Progressive Colorectal Cancer

The application of rapid and accurate diagnostic methods can improve colorectal cancer (CRC) survival rates dramatically. Here, we used a non-targeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry (iEESI-MS) to detect metabolite ions associated with the progression of CRC from 172 tissues (45 stage I/II CRC, 41 stage III/IV CRC, and 86 well-matched normal tissues). A support vector machine (SVM) model based on 10 differential metabolite ions for differentiating early-stage CRC from normal tissues was built with a good prediction accuracy of 92.6%. The biomarker panel consisting of lysophosphatidylcholine (LPC) (18:0) has good diagnostic potential in differentiating early-stage CRC from advanced-stage CRC. We showed that the down-regulation of LPC (18:0) in tumor tissues is associated with CRC progression and related to the regulation of the epidermal growth factor receptor. Pathway analysis showed that metabolic pathways in CRC are related to glycerophospholipid metabolism and purine metabolism. In conclusion, we built an SVM model with good performance to distinguish between early-stage CRC and normal groups based on iEESI-MS and found that LPC (18:0) is associated with the progression of CRC.

Structural identification of lysophosphatidylcholines as activating ligands for orphan receptor GPR119

Lysophosphatidylcholine (LPC) is an essential mediator in human lipid metabolism and is associated with a variety of diseases, but the exact identity of LPC receptors remains controversial. Through extensive biochemical and structural analyses, we have identified the orphan receptor GPR119 as the receptor for LPC. The structure of the GPR119-G-protein complex without any added ligands reveals a density map that fits well with LPC, which is further confirmed by mass spectrometry and functional studies. As LPCs are abundant on the cell membrane, their preoccupancy in the receptor may lead to 'constitutive activity' of GPR119. The structure of GPR119 bound to APD668, a clinical drug candidate for type 2 diabetes, reveals an exceedingly similar binding mode to LPC. Together, these data highlight structural evidence for LPC function in regulating glucose-dependent insulin secretion through direct binding and activation of GPR119, and provide structural templates for drug design targeting GPR119.

Metabolic detection of malignant brain gliomas through plasma lipidomic analysis and support vector machine-based machine learning

Background

Most malignant brain gliomas (MBGs) are associated with dismal outcomes, mainly due to their late diagnosis. Current diagnostic methods for MBGs are based on imaging and histological examination, which limits their early detection. Here, we aimed to identify reliable plasma lipid biomarkers for non-invasive diagnosis for MBGs.

Methods

Untargeted lipidomic analysis was firstly performed using a discovery cohort (n=107). The data were processed by a support vector machine (SVM)-based discriminating model to retrieve a panel of candidate biomarkers. Then, a targeted quantification method was developed, and the SVM-based diagnostic model was constructed using a training cohort (n=750) and tested using a test cohort (n=225). Finally, the performance of the diagnostic model was further evaluated in an independent validation cohort (n=920) enrolled from multiple medical centers.

Findings

A panel of 11 plasma lipids was identified as candidate biomarkers with an accuracy of 0.999. The diagnostic model developed achieved a high performance in distinguishing MBGs patients from normal controls with an area under the receiver-operating characteristic curve (AUC) of 0.9877 and 0.9869 in the training and test cohorts, respectively. In the validation cohort, the 11 lipid panel still achieved an accuracy of 0.9641 and an AUC of 0.9866.

Interpretation

The present study demonstrates the applicability and robustness of utilizing a machine learning algorithm to analyze lipidomic data for efficient and reliable biomarker screening. The 11 lipid biomarkers show great potential for the non-invasive diagnosis of MBGs with high throughput.

Funding

A full list of funding bodies that contributed to this study can be found in the Acknowledgments section.

Serum untargeted lipidomics by UHPLC-ESI-HRMS aids the biomarker discovery of colorectal adenoma

BACKGROUND

Colorectal adenoma (CA) is an important precancerous lesion and early screening target of colorectal cancer (CRC). Lipids with numerous physiological functions are proved to be involved in the development of CRC. However, there is no lipidomic study with large-scale serum samples on diagnostic biomarkers for CA.

METHODS

The serum lipidomics of CA patients (n = 50) and normal control (NR) (n = 50) was performed by ultra high performance liquid chromatography-high resolution mass spectrometry with electrospray ionization (UHPLC-ESI-HRMS). Univariate and multivariate statistical analyses were utilized to screen the differential lipids between groups, and combining the constituent ratio analysis and diagnostic efficiency evaluation by receiver operating characteristic (ROC) curve disclosed the potential mechanism and biomarkers for CA.

RESULTS

There were obvious differences in serum lipid profiles between CA and NR groups. Totally, 79 differential lipids were selected by criterion of P < 0.05 and fold change > 1.5 or < 0.67. Triacylglycerols (TAGs) and phosphatidylcholines (PCs) were the major differential lipids with ratio > 60%, indicating these two lipid metabolic pathways showed evident disequilibrium, which could contribute to CA formation. Of them, 12 differential lipids had good diagnostic ability as candidate biomarkers for CA (AUC ≥ 0.900) by ROC analysis.

CONCLUSIONS

To our knowledge, this is the first attempt to profile serum lipidomics and explore lipid biomarkers of CA to help early screening of CRC. 12 differential lipids are obtained to act as potential diagnostic markers of CA. PCs and fatty acids were the main dysregulated biomarkers for CA in serum.

The Application of Metabolomics in Recent Colorectal Cancer Studies: A State-of-the-Art Review

Simple Summary

Colorectal Cancer (CRC) is one of the leading causes of cancer-related death in the United States. Current diagnosis techniques are either highly invasive or lack sensitivity, suggesting the need for alternative techniques for biomarker detection. Metabolomics represents one such technique with great promise in identifying CRC biomarkers with high sensitivity and specificity, but thus far is rarely employed in a clinical setting. In order to provide a framework for future clinical usage, we characterized dysregulated metabolites across recent literature, identifying metabolites dysregulated across a variety of biospecimens. We additionally put special focus on the interplay of the gut microbiome and perturbed metabolites in CRC. We were able to identify many metabolites showing consistent dysregulation in CRC, demonstrating the value of metabolomics as a promising diagnostic technique.

Abstract

Colorectal cancer (CRC) is a highly prevalent disease with poor prognostic outcomes if not diagnosed in early stages. Current diagnosis techniques are either highly invasive or lack sufficient sensitivity. Thus, identifying diagnostic biomarkers of CRC with high sensitivity and specificity is desirable. Metabolomics represents an analytical profiling technique with great promise in identifying such biomarkers and typically represents a close tie with the phenotype of a specific disease. We thus conducted a systematic review of studies reported from January 2012 to July 2021 relating to the detection of CRC biomarkers through metabolomics to provide a collection of knowledge for future diagnostic development. We identified thirty-seven metabolomics studies characterizing CRC, many of which provided metabolites/metabolic profile-based diagnostic models with high sensitivity and specificity. These studies demonstrated that a great number of metabolites can be differentially regulated in CRC patients compared to healthy controls, adenomatous polyps, or across stages of CRC. Among these metabolite biomarkers, especially dysregulated were certain amino acids, fatty acids, and lysophosphatidylcholines. Additionally, we discussed the contribution of the gut bacterial population to pathogenesis of CRC through their modulation to fecal metabolite pools and summarized the established links in the literature between certain microbial genera and altered metabolite levels in CRC patients. Taken together, we conclude that metabolomics presents itself as a promising and effective method of CRC biomarker detection.

Changing Metabolic Patterns along the Colorectal Adenoma–Carcinoma Sequence

Colorectal cancer (CRC) is a major public health burden and one of the leading causes of cancer-related deaths worldwide. Screening programs facilitate early diagnosis and can help to reduce poor outcomes. Serum metabolomics can extract vital molecular information that may increase the sensitivity and specificity of colonoscopy in combination with histopathological examination. The present study identifies serum metabolite patterns of treatment-naïve patients, diagnosed with either advanced adenoma (AA) or CRC in colonoscopy screenings, in the framework of the SAKKOPI (Salzburg Colon Cancer Prevention Initiative) program. We used a targeted flow injection analysis and liquid chromatography-tandem mass spectrometry metabolomics approach (FIA- and LC-MS/MS) to characterise the serum metabolomes of an initial screening cohort and two validation cohorts (in total 66 CRC, 76 AA and 93 controls). The lipidome was significantly perturbed, with a proportion of lipid species being downregulated in CRC patients, as compared to AA and controls. The predominant alterations observed were in the levels of lyso-lipids, glycerophosphocholines and acylcarnitines, but additionally, variations in the quantity of hydroxylated sphingolipids could be detected. Changed amino acid metabolism was restricted mainly to metabolites of the arginine/dimethylarginine/NO synthase pathway. The identified metabolic divergences observed in CRC set the foundation for mechanistic studies to characterise biochemical pathways that become deregulated during progression through the adenoma to carcinoma sequence and highlight the key importance of lipid metabolites. Biomarkers related to these pathways could improve the sensitivity and specificity of diagnosis, as well as the monitoring of therapies.

OUP accepted manuscript

Circulating biomarkers have emerged as valuable surrogates for evaluating disease states in solid malignancies. Their relative ease of access and rapid turnover has bolstered clinical applications in monitoring treatment efficacy and cancer progression. In this review, the roles of various circulating biomarkers in monitoring treatment response are described. Non-specific markers of disease burden, tumor markers (eg CA 125, CEA, PSA, etc.), circulating tumor cells, nucleic acids, exosomes, and metabolomic arrays are highlighted. Specifically, the discovery of each of these markers is reviewed, with examples illustrating their use in influencing treatment decisions, and barriers to their application noted where these exist. Finally, opportunities for future work using these circulating biomarkers are discussed.