Metabolomic Profiling of Blood-Derived Microvesicles in Breast Cancer Patients

The Diagnostic Potential of Extracellular Vesicles Derived From the Blood Plasma of Glioblastoma Patients

BACKGROUND/AIM

Biomarkers for patients suffering from glioblastoma (GBM) are scarce. Extracellular vesicles (EV) are a promising candidate for a potential biomarker. Therefore, EV concentration could be a potential biomarker of tumor burden, volume, and prognosis.

PATIENTS AND METHODS

Large EV (lEV) and small EV (sEV) were isolated from 36 GBM patients' blood plasma by differential centrifugation. Nanoparticle tracking was used to measure EV concentration. Quantitative analysis of tumor volume was performed by evaluating T2/FLAIR relaxation times.

RESULTS

The mean size of lEV was 173.3 nm ± 18.2 nm, while sEV measured 148.3 ± 9.0 nm. Patients with higher lEV concentrations showed a trend towards longer overall survival (36.1 vs. 16.5 months, p=0.08). Regarding inflammatory markers, higher leukocyte count was positively correlated with higher sEV concentration (r2=0.3887, DF 21, p=0.0015). No significant relationship was found between lEV or sEV concentration and tumor volume.

CONCLUSION

Overall EV concentration in the peripheral blood is not a predictor of tumor volume. sEV concentration is associated with a potential pro-inflammatory metabolism.

Discovery of Plasma Lipids as Potential Biomarkers Distinguishing Breast Cancer Patients from Healthy Controls

The development of a sensitive and specific blood test for the early detection of breast cancer is crucial to improve screening and patient outcomes. Existing methods, such as mammography, have limitations, necessitating the exploration of alternative approaches, including circulating factors. Using 598 prospectively collected blood samples, a multivariate plasma-derived lipid biomarker signature was developed that can distinguish healthy control individuals from those with breast cancer. Liquid chromatography with high-resolution and tandem mass spectrometry (LC-MS/MS) was employed to identify lipids for both extracellular vesicle-derived and plasma-derived signatures. For each dataset, we identified a signature of 20 lipids using a robust, statistically rigorous feature selection algorithm based on random forest feature importance applied to cross-validated training samples. Using an ensemble of machine learning models, the plasma 20-lipid signature generated an area under the curve (AUC) of 0.95, sensitivity of 0.91, and specificity of 0.79. The results from this study indicate that lipids extracted from plasma can be used as target analytes in the development of assays to detect the presence of early-stage breast cancer.

Biochemical Pathways Delivering Distinct Glycosphingolipid Patterns in MDA-MB-231 and MCF-7 Breast Cancer Cells

The complex structure of glycosphingolipids (GSLs) supports their important role in cell function as modulators of growth factor receptors and glutamine transporters in plasma membranes. The aberrant composition of clustered GSLs within signaling platforms, so-called lipid rafts, inevitably leads to tumorigenesis due to disturbed growth factor signal transduction and excessive uptake of glutamine and other molecules needed for increased energy and structural molecule cell supply. GSLs are also involved in plasma membrane processes such as cell adhesion, and their transition converts cells from epithelial to mesenchymal with features required for cell migration and metastasis. Glutamine activates the mechanistic target of rapamycin complex 1 (mTORC1), resulting in nucleotide synthesis and proliferation. In addition, glutamine contributes to the cancer stem cell GD2 ganglioside-positive phenotype in the triple-negative breast cancer cell line MDA-MB-231. Thieno[2,3-b]pyridine derivative possesses higher cytotoxicity against MDA-MB-231 than against MCF-7 cells and induces a shift to aerobic metabolism and a decrease in S(6)nLc4Cer GSL-positive cancer stem cells in the MDA-MB-231 cell line. In this review, we discuss findings in MDA-MB-231, MCF-7, and other breast cancer cell lines concerning their differences in growth factor receptors and recent knowledge of the main biochemical pathways delivering distinct glycosphingolipid patterns during tumorigenesis and therapy.

Bioactive sphingolipids as emerging targets for signal transduction in cancer development

Sphingolipids, crucial components of cellular membranes, play a vital role in maintaining cellular structure and signaling integrity. Disruptions in sphingolipid metabolism are increasingly implicated in cancer development. Key bioactive sphingolipids, such as ceramides, sphingosine-1-phosphate (S1P), ceramide-1-phosphate (C1P), and glycosphingolipids, profoundly impact tumor biology. They influence the behavior of tumor cells, stromal cells, and immune cells, affecting tumor aggressiveness, angiogenesis, immune modulation, and extracellular matrix remodeling. Furthermore, abnormal expression of sphingolipids and their metabolizing enzymes modulates the secretion of tumor-derived extracellular vesicles (TDEs), which are key players in creating an immunosuppressive tumor microenvironment, remodeling the extracellular matrix, and facilitating oncogenic signaling within in situ tumors and distant pre-metastatic niches (PMNs). Understanding the role of sphingolipids in the biogenesis of tumor-derived extracellular vesicles (TDEs) and their bioactive contents can pave the way for new biomarkers in cancer diagnosis and prognosis, ultimately enhancing comprehensive tumor treatment strategies.

Metabolic features of tumor-derived extracellular vesicles: challenges and opportunities

Tumor-derived extracellular vesicles (TDEVs) play crucial roles in intercellular communication both in the local tumor microenvironment and systemically, facilitating tumor progression and metastatic spread. They carry a variety of molecules with bioactive properties, such as nucleic acids, proteins and metabolites, that trigger different signaling processes in receptor cells and induce, among other downstream effects, metabolic reprogramming. Interestingly, the cargo of TDEVs also reflects the metabolic status of the producing cells in a time- and context-dependent manner, providing information on the functionality and state of those cells. For these reasons, together with their ability to be detected in diverse biofluids, there is increasing interest in the study of TDEVs, particularly their metabolic cargo, as diagnostic and prognostic tools in cancer management. This review presents a compilation of metabolism-related molecules (enzymes and metabolites) described in cancer extracellular vesicles (EVs) with potential use as cancer biomarkers, and discusses the challenges arising in this rapidly evolving field.

Modulatory effects of cancer stem cell-derived extracellular vesicles on the tumor immune microenvironment

Cancer stem cells (CSCs), accounting for only a minor cell proportion (< 1%) within tumors, have profound implications in tumor initiation, metastasis, recurrence, and treatment resistance due to their inherent ability of self-renewal, multi-lineage differentiation, and tumor-initiating potential. In recent years, accumulating studies indicate that CSCs and tumor immune microenvironment act reciprocally in driving tumor progression and diminishing the efficacy of cancer therapies. Extracellular vesicles (EVs), pivotal mediators of intercellular communications, build indispensable biological connections between CSCs and immune cells. By transferring bioactive molecules, including proteins, nucleic acids, and lipids, EVs can exert mutual influence on both CSCs and immune cells. This interaction plays a significant role in reshaping the tumor immune microenvironment, creating conditions favorable for the sustenance and propagation of CSCs. Deciphering the intricate interplay between CSCs and immune cells would provide valuable insights into the mechanisms of CSCs being more susceptible to immune escape. This review will highlight the EV-mediated communications between CSCs and each immune cell lineage in the tumor microenvironment and explore potential therapeutic opportunities.

Prognostic potential of lipid profiling in cancer patients: a systematic review of mass spectrometry-based studies

Cancer prognosis remains a critical clinical challenge. Lipidomic analysis via mass spectrometry (MS) offers the potential for objective prognostic prediction, leveraging the distinct lipid profiles of cancer patient-derived specimens. This review aims to systematically summarize the application of MS-based lipidomic analysis in prognostic prediction for cancer patients. Our systematic review summarized 38 studies from the past decade that attempted prognostic prediction of cancer patients through lipidomics. Commonly analyzed cancers included colorectal, prostate, and breast cancers. Liquid (serum and urine) and tissue samples were equally used, with liquid chromatography-tandem MS being the most common analytical platform. The most frequently evaluated prognostic outcomes were overall survival, stage, and recurrence. Thirty-eight lipid markers (including phosphatidylcholine, ceramide, triglyceride, lysophosphatidylcholine, sphingomyelin, phosphatidylethanolamine, diacylglycerol, phosphatidic acid, phosphatidylserine, lysophosphatidylethanolamine, lysophosphatidic acid, dihydroceramide, prostaglandin, sphingosine-1-phosphate, phosphatidylinosito, fatty acid, glucosylceramide and lactosylceramide) were identified as prognostic factors, demonstrating potential for clinical application. In conclusion, the potential for developing lipidomics in cancer prognostic prediction was demonstrated. However, the field is still nascent, necessitating future studies for validating and establishing lipid markers as reliable prognostic tools in clinical practice.

Extracellular vesicle-mediated drug delivery in breast cancer theranostics

Breast cancer (BC) continues to be a significant global challenge due to drug resistance and severe side effects. The increasing prevalence is alarming, requiring new therapeutic approaches to address these challenges. At this point, Extracellular vesicles (EVs), specifically small endosome-released nanometer-sized EVs (SEVs) or exosomes, have been explored by literature as potential theranostics. Therefore, this review aims to highlight the therapeutic potential of exosomes in BC, focusing on their advantages in drug delivery and their ability to mitigate metastasis. Following the review, we identified exosomes' potential in combination therapies, serving as miRNA carriers and contributing to improved anti-tumor effects. This is evident in clinical trials investigating exosomes in BC, which have shown their ability to boost chemotherapy efficacy by delivering drugs like paclitaxel (PTX) and doxorubicin (DOX). However, the translation of EVs into BC therapy is hindered by various challenges. These challenges include the heterogeneity of EVs, the selection of the appropriate parent cell, the loading procedures, and determining the optimal administration routes. Despite the promising therapeutic potential of EVs, these obstacles must be addressed to realize their benefits in BC treatment.

Metabolic profiling in tissues and urine of patients with prostatic lesions and the diagnostic value of urine extracellular vesicles metabolites in prostate cancer

BACKGROUND

Prostate cancer (PCa) lacks convenient and highly specific diagnostic markers. Although the value of extracellular vesicles (EV) in oncology is widely recognized, the diagnostic value of EV metabolites requires further exploration. This study aimed to explore the diagnostic value of urine EV (u-EV) metabolomics in PCa.

METHODS

We first detected metabolites in paired tissues cells (cells), tissue EV (t-EVs), u-EVs, and urine samples in cohort 1 (8 PCa vs. 5 benign prostatic hypertrophy, BPH) to prob the feasibility of EV metabolites as diagnostic markers. We then analyzed the value of u-EVs as markers for PCa diagnosis and typing in the expanded sample cohort (60 PCa vs. 40 BPH).

RESULTS

U-EV metabolites were more consistent with those in tissue-derived samples (cells and t-EVs) than those in urine, and more differential metabolites between BPH and PCa were identified in u-EV. Subsequently, we used a random forest model to construct a panel of six metabolites for PCa, which showed an area under the curve (AUC) of 0.833 in training cohort and 0.844 in validation cohort. We also found significantly differentially expressed metabolites between PCa subtypes (Gleason ≤ 7 vs. Gleason > 7 and localized vs. metastasis), demonstrating the value of EV metabolites in PCa typing and prognostic assessment.

CONCLUSION

Metabolomic analysis of u-EVs is a promising source of noninvasive markers for PCa diagnosis.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

Vesiculation in irradiated and cation-leaky-stored red blood cells

BACKGROUND

Extracellular vesicles (EVs) are released by red blood cells (RBCs) throughout their life-span and also during hypothermic storage when they accumulate in the blood bag. We queried whether stored RBCs with increased cation permeability, either from donors with familial pseudohyperkalaemia (FP) or caused by irradiation, vesiculate more readily.

STUDY DESIGN AND METHODS

Recent technical advances have revealed at least two sub-populations of MVs in RBC storage units: macrovesicles (2-6 μm) and microvesicles (1-2 μm). Using nanoparticle tracking analysis, imaging flow cytometry, and protein quantification methods, we measured and characterized vesicles released by RBCs from control and FP individuals at three different storage time-points (day 4, day 17, and day 29). The RBCs had either been stored untreated or irradiated on either day 1 or day 14 of storage.

RESULTS

We found no difference in the number or size of vesicles released between cation-leaky FP RBCs and non-FP controls. Similarly, irradiated and non-irradiated RBCs showed very similar patterns of vesicle release to during cold-storage. The only significant difference in vesicle release was the increase in accumulated vesicles with length of storage time which has been reported previously.

DISCUSSION

EVs in stored blood are potential contributors to adverse transfusion reactions. The number of vesicles released during 35-day hypothermic storage varies between donors and increases with storage duration. However, increased cation permeability and irradiation do not appear to affect vesicle formation during RBC cold-storage.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

Extracellular vesicles in the treatment and diagnosis of breast cancer: a status update

Breast cancer is one of the leading causes of cancer-related death in women. Currently, the treatment of breast cancer is limited by the lack of effectively targeted therapy and patients often suffer from higher severity, metastasis, and resistance. Extracellular vesicles (EVs) consist of lipid bilayers that encapsulate a complex cargo, including proteins, nucleic acids, and metabolites. These bioactive cargoes have been found to play crucial roles in breast cancer initiation and progression. Moreover, EV cargoes play pivotal roles in converting mammary cells to carcinogenic cells and metastatic foci by extensively inducing proliferation, angiogenesis, pre-metastatic niche formation, migration, and chemoresistance. The present update review mainly discusses EVs cargoes released from breast cancer cells and tumor-derived EVs in the breast cancer microenvironment, focusing on proliferation, metastasis, chemoresistance, and their clinical potential as effective biomarkers.

Extracellular Vesicles in Liquid Biopsies as Biomarkers for Solid Tumors

Extracellular vesicles (EVs) are secreted by all living cells and are ubiquitous in every human body fluid. They are quite heterogeneous with regard to biogenesis, size, and composition, yet always reflect their parental cells with their cell-of-origin specific cargo loading. Since numerous studies have demonstrated that EV-associated proteins, nucleic acids, lipids, and metabolites can represent malignant phenotypes in cancer patients, EVs are increasingly being discussed as valuable carriers of cancer biomarkers in liquid biopsy samples. However, the lack of standardized and clinically feasible protocols for EV purification and characterization still limits the applicability of EV-based cancer biomarker analysis. This review first provides an overview of current EV isolation and characterization techniques that can be used to exploit patient-derived body fluids for biomarker quantification assays. Secondly, it outlines promising tumor-specific EV biomarkers relevant for cancer diagnosis, disease monitoring, and the prediction of cancer progression and therapy resistance. Finally, we summarize the advantages and current limitations of using EVs in liquid biopsy with a prospective view on strategies for the ongoing clinical implementation of EV-based biomarker screenings.

Comprehensive serum lipidomic analyses reveal potential biomarkers for malignant breast cancer: A case-control study

BACKGROUND

Breast cancer is the most worldwide commonly found malignancy among women. The evidence for lipidomic studies of breast cancer in the Chinese population is relatively limited.

OBJECTIVE

Our current study aimed to identify peripheral lipids capable of distinguishing adults with and without malignant breast cancer in a Chinese population and to explore the potential lipid metabolism pathways implicated in breast cancer.

METHODS

Lipidomics was performed with an Ultimate 3000 UHPLC system coupled with a Q-Exactive HF MS platform by using the serum of 71 female patients with malignant breast cancer and 92 age-matched (± 2 years) healthy women. The data were uploaded to and processed by the specialized online software Metaboanalyst 5.0. Both univariate and multivariate analyses were carried out for potential biomarker screening. Areas under the receiver-operating characteristic (ROC) curves (AUCs) of identified differential lipids were obtained for evaluating their classification capacity.

RESULTS

A total of 47 significantly different lipids were identified by applying the following criteria: false discovery rate-adjusted P < 0.05, variable importance in projection ⩾ 1.0, and fold change ⩾ 2.0 or ⩽ 0.5. Among them, 13 lipids were identified as diagnostic biomarkers with the area under curve (AUC) greater than 0.7. Multivariate ROC curves indicated that AUCs greater than 0.8 could be achieved with 2-47 lipids.

CONCLUSIONS

Using an untargeted LC-MS-based metabolic profiling approach, our study provides preliminary evidence that extensive dysregulations of OxPCs, PCs, SMs and TAGs were involved in the pathological processes of breast cancer. We provided clues for furtherly investigating the role of lipid alterations in the pathoetiology of breast cancer.

EASY-FIA: A Readably Usable Standalone Tool for High-Resolution Mass Spectrometry Metabolomics Data Pre-Processing

Flow injection analysis coupled with high-resolution mass spectrometry (FIA-HRMS) is a fair trade-off between resolution and speed. However, free software available for data pre-processing is few, web-based, and often requires advanced user specialization. These tools rarely embedded blank and noise evaluation strategies, and direct feature annotation. We developed EASY-FIA, a free standalone application that can be employed for FIA-HRMS metabolomic data pre-processing by users with no bioinformatics/programming skills. We validated the tool's performance and applicability in two clinical metabolomics case studies. The main functions of our application are blank subtraction, alignment of the metabolites, and direct feature annotation by means of the Human Metabolome Database (HMDB) using a minimum number of mass spectrometry parameters. In a scenario where FIA-HRMS is increasingly recognized as a reliable strategy for fast metabolomics analysis, EASY-FIA could become a standardized and feasible tool easily usable by all scientists dealing with MS-based metabolomics. EASY-FIA was implemented in MATLAB with the App Designer tool and it is freely available for download.

Metabolomics of Extracellular Vesicles: A Future Promise of Multiple Clinical Applications

Extracellular vesicles (EVs) can contain DNA, RNA, proteins and metabolic molecules from primary origins; they are coated with a phospholipid bilayer membrane and released by cells into the extracellular matrix. EVs can be obtained from various body liquids, including the blood, saliva, cerebrospinal fluid, and urine. As has been proved, EVs-mediated transfer of biologically active molecules is crucial for various physiological and pathological processes. Extensive investigations have already begun to explore the diagnosis and prognosis potentials for EVs. Furthermore, research has continued to recognize the critical role of nucleic acids and proteins in EVs. However, our understanding of the comprehensive effects of metabolites in these nanoparticles is currently limited and in its infancy. Therefore, we have attempted to summarize the recent research into the metabolomics of EVs in relation to potential clinical applications and discuss the problems and challenges that have occurred, to provide more guidance for the future development in this field.

Circulating Carnitine Levels and Breast Cancer: A Matched Retrospective Case-Control Study

Introduction

Epidemiological studies investigating the association between carnitine and breast cancer are scarce.

Materials and Methods

This 1:1 age-matched retrospective case-control study identified 991 female breast cancer cases and 991 female controls without breast cancer using pathological testing. We used targeted metabolomics technology to measure 16 types of whole blood carnitine compounds, such as free carnitine (C0) and octadecanoylcarnitine (C18).

Results

The average age for cases and controls was approximately 50 ± 8.7 years. After adjusting for covariates, each standard deviation (SD) increase in malonylcarnitine (C3DC; OR 0.91; 95% CI 0.83-1.00), decenoylcarnitine (C10:1; OR 0.87; 95% CI 0.79-0.96), and decadienoylcarnitine (C10:2; OR 0.90; 95% CI 0.82-0.99) level was associated with decreased odds of breast cancer. However, higher butyrylcarnitine (C4) levels were associated with increased odds of breast cancer (OR 1.12; 95% CI 1.02-1.23). No statistically significant relationship was noted between other carnitine compounds and breast cancer. The false discovery rates for C3DC, C4, C10:1 and C10:2 were 0.172, 0.120, 0.064 and 0.139, respectively.

Conclusions

Higher levels of C3DC, C10:1, and C10:2 were protective factors for breast cancer, whereas increased C4 levels were a risk factor for the disease.