To treat or not to treat: metabolomics reveals biomarkers for treatment indication in chronic lymphocytic leukaemia patients

Targeting sphingolipid metabolism in chronic lymphocytic leukemia

Elevated levels of circulating C16:0 glucosylceramides (GluCer) and increased mRNA expression of UDP-glucose ceramide glycosyltransferase (UGCG), the enzyme responsible for converting ceramides (Cer) to GluCer, represent unfavorable prognostic markers in chronic lymphocytic leukemia (CLL) patients. To evaluate the therapeutic potential of inhibiting GluCer synthesis, we genetically repressed the UGCG pathway using in vitro models of leukemic B cells, in addition to UGCG pharmacological inhibition with approved drugs such as eliglustat and ibiglustat, both individually and in combination with ibrutinib, assessed in cell models and primary CLL patient cells. Cell viability, apoptosis, and proliferation were evaluated in vitro, and survival and apoptosis were examined ex vivo. UGCG inhibition efficacy was confirmed by quantifying intracellular sphingolipid levels through targeted lipidomics using mass spectrometry. Other inhibitors of sphingolipid biosynthesis pathways were similarly assessed. Blocking UGCG significantly decreased cell viability and proliferation, highlighting the oncogenic role of UGCG in CLL. The efficient inhibition of UGCG was confirmed by a significant reduction in GluCer intracellular levels. The combination of UGCG inhibitors with ibrutinib demonstrated synergistic effect. Inhibitors that target alternative pathways within sphingolipid metabolism, like sphingosine kinases inhibitor SKI-II, also demonstrated promising therapeutic effects both alone and when used in combination with ibrutinib, reinforcing the oncogenic impact of sphingolipids in CLL cells. Targeting sphingolipid metabolism, especially the UGCG pathway, represents a promising therapeutic strategy and as a combination therapy for potential treatment of CLL patients, warranting further investigation.

Multiple omics levels of chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a lymphoproliferative malignancy characterized by the proliferation of functionally mature but incompetent B cells. It is the most prevalent type of leukemia in Western populations, accounting for approximately 25% of new leukemia cases. While recent advances, such as ibrutinib and venetoclax treatment have improved patient outlook, aggressive forms of CLL such as Richter transformation still pose a significant challenge. This discrepancy may be due to the heterogeneity of factors contributing to CLL development at multiple -omics levels. However, information on the omics of CLL is fragmented, hindering multi-omics-based research into potential treatment options. To address this, we aggregated and presented a selection of important aspects of various omics levels of the disease in this review. The purpose of the present literature analysis is to portray examples of CLL studies from different omics levels, including genomics, epigenomics, transcriptomics, epitranscriptomics, proteomics, epiproteomics, metabolomics, glycomics and lipidomics, as well as those identified by multi-omics approaches. The review includes the list of 102 CLL-associated genes with relevant genomics information. While single-omics studies yield substantial and useful data, they omit a significant level of complex biological interplay present in the disease. As multi-omics studies integrate several different layers of data, they may be better suited for complex diseases such as CLL and have thus far yielded promising results. Future multi-omics studies may assist clinicians in improved treatment choices based on CLL subtypes as well as allow the identification of novel biomarkers and targets for treatments.

ACOX1-mediated peroxisomal fatty acid oxidation contributes to metabolic reprogramming and survival in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is still an incurable disease, with many patients developing resistance to conventional and targeted therapies. To better understand the physiology of CLL and facilitate the development of innovative treatment options, we examined specific metabolic features in the tumor CLL B-lymphocytes. We observed metabolic reprogramming, characterized by a high level of mitochondrial oxidative phosphorylation activity, a low glycolytic rate, and the presence of C2- to C6-carnitine end-products revealing an unexpected, essential role for peroxisomal fatty acid beta-oxidation (pFAO). Accordingly, downmodulation of ACOX1 (a rate-limiting pFAO enzyme overexpressed in CLL cells) was enough to shift the CLL cells' metabolism from lipids to a carbon- and amino-acid-based phenotype. Complete blockade of ACOX1 resulted in lipid droplet accumulation and caspase-dependent death in CLL cells, including those from individuals with poor cytogenetic and clinical prognostic factors. In a therapeutic translational approach, ACOX1 inhibition spared non-tumor blood cells from CLL patients but led to the death of circulating, BCR-stimulated CLL B-lymphocytes and CLL B-cells receiving pro-survival stromal signals. Furthermore, a combination of ACOX1 and BTK inhibitors had a synergistic killing effect. Overall, our results highlight a less-studied but essential metabolic pathway in CLL and pave the way towards the development of new, metabolism-based treatment options.

Untargeted metabolomics identifies metabolic dysregulation of sphingolipids associated with aggressive chronic lymphocytic leukaemia and poor survival

BACKGROUND

Metabolic dependencies of chronic lymphocytic leukaemia (CLL) cells may represent new personalized treatment approaches in patients harbouring unfavourable features.

METHODS

Here, we used untargeted metabolomics and lipidomics analyses to isolate metabolomic features associated with aggressive CLL and poor survival outcomes. We initially focused on profiles associated with overexpression of the adverse metabolic marker glycosyltransferase (UGT2B17) associated with poor survival and drug resistance.

RESULTS

Leukaemic B-cell metabolomes indicated a significant perturbation in lipids, predominantly bio-active sphingolipids. Expression of numerous enzyme-encoding genes of sphingolipid biosynthesis pathways was significantly associated with shorter patient survival. Targeted metabolomics further exposed higher circulating levels of glucosylceramides (C16:0 GluCer) in CLL patients relative to healthy donors and an aggressive cancer biology. In multivariate analyses, C16:0 GluCer and sphinganine were independent prognostic markers and were inversely linked to treatment-free survival. These two sphingolipid species function as antagonistic mediators, with sphinganine being pro-apoptotic and GluCer being pro-proliferative, tested in leukemic B-CLL cell models. Blocking GluCer synthesis using ceramide glucosyltransferase inhibitors induced cell death and reduced the proliferative phenotype, which further sensitized a leukaemic B-cell model to the anti-leukaemics fludarabine and ibrutinib in vitro.

CONCLUSIONS

Specific sphingolipids may serve as prognostic markers in CLL, and inhibiting enzymatic pathways involved in their biosynthesis has potential as a therapaeutic approach.

Metabolomics Reveals Differences in Aqueous Humor Composition in Patients With and Without Pseudoexfoliation Syndrome

Pseudoexfoliation syndrome (XFS) is stress- or inflammation-induced elastosis accompanied by excessive production of microfibrils and their deposition in the anterior segment of the eye. Approximately 60–70 million people are affected by XFS worldwide. It is a component of a systemic disorder, considered a major risk factor for accelerated cataract formation, cataract surgery complications and development of glaucoma, which untreated or inadequately treated may lead to blindness. Moreover, XFS has been associated with cardiovascular and cerebrovascular morbidity, dementia, sensorineural hearing loss and pelvic organ prolapse. The pathogenesis of XFS has not been fully elucidated yet. Aqueous humor (AH) is a transparent fluid filling the anterior and posterior chambers of the eye. Determination of AH metabolites that are characteristic for XFS may provide valuable information about the molecular background of this ocular disorder. The aim of this study was to compare the composition of AH in XFS and non-XFS patients undergoing cataract surgery. The AH samples from 34 patients (15 with XFS and 19 without) were analyzed using liquid chromatography coupled to a Quadrupole Time-of-Flight mass spectrometer (LC-QTOF-MS). The obtained metabolic fingerprints were analyzed using multivariate statistics. Eleven statistically significant metabolites were identified. Compared with the non-XFS group, the AH of patients with XFS contained significantly lower levels of amino acids and their derivatives, for example, arginine (−31%, VIP = 2.38) and homo-arginine (−19%, VIP = 1.38). Also, a decrease in the levels of two acylcarnitines, hydroxybutyrylcarnitine (−29%, VIP = 1.24) and decatrienoylcarnitine (−46%, VIP = 1.89), was observed. However, the level of indoleacetaldehyde in XFS patients was significantly higher (+96%, VIP = 2.64). Other significant metabolites were two well-recognized antioxidants, ascorbic acid (−33%, VIP = 2.11) and hydroxyanthranilic acid (−33%, VIP = 2.25), as well as S-adenosylmethionine, a compound with anti-inflammatory properties (−29%, VIP = 1.93). Metabolic pathway analysis demonstrated that the identified metabolites belonged to eight metabolic pathways, with cysteine and methionine metabolism as well as arginine and proline metabolism being the most frequently represented. XFS can be associated with enhanced oxidative stress and inflammation, as well as with the disturbances of cellular respiration and mitochondrial energy production. Implementation of non-targeted metabolomics provided a better insight into the still not fully understood pathogenesis of XFS.

Applications of Metabolomics in Forensic Toxicology and Forensic Medicine

Forensic toxicology and forensic medicine are unique among all other medical fields because of their essential legal impact, especially in civil and criminal cases. New high-throughput technologies, borrowed from chemistry and physics, have proven that metabolomics, the youngest of the “omics sciences”, could be one of the most powerful tools for monitoring changes in forensic disciplines. Metabolomics is a particular method that allows for the measurement of metabolic changes in a multicellular system using two different approaches: targeted and untargeted. Targeted studies are focused on a known number of defined metabolites. Untargeted metabolomics aims to capture all metabolites present in a sample. Different statistical approaches (e.g., uni- or multivariate statistics, machine learning) can be applied to extract useful and important information in both cases. This review aims to describe the role of metabolomics in forensic toxicology and in forensic medicine.

Mass spectrometry based proteomics and metabolomics in personalized oncology

Precision medicine (PM) means the customization of healthcare with decisions and practices adjusted to the individual patient. It includes personalized diagnostics, patients' sub-classification, individual treatment selection and the monitoring of its effectiveness. Currently, in oncology, PM is based on the molecular and cellular features of a tumor, its microenvironment and the patient's genetics and lifestyle. Surprisingly, the available targeted therapies were found effective only in a subset of patients. An in-depth understanding of tumor biology is crucial to improve their effectiveness and develop new therapeutic targets. Completion of genetic information with proteomics and metabolomics can give broader knowledge about tumor biology which consequently provides novel biomarkers and indicates new therapeutic targets. Recently, metabolomics and proteomics have extensively been applied in the field of oncology. In the context of PM, human studies, with the use of mass spectrometry (MS) which allows the detection of thousands of molecules in a large number of samples, are the most valuable. Such studies, focused on cancer biomarkers discovery or patients' stratification, are presented in this review. Moreover, the technical aspects of MS-based clinical proteomics and metabolomics are described.

Lipids as Biomarkers of Cancer and Bacterial Infections

Lipids are ubiquitous molecules, known to play important roles in various cellular processes. Alterations to the lipidome can therefore be used as a read-out of the signs of disease, highlighting the importance to consider lipids as biomarkers in addition of nucleic acid and proteins. Lipids are among the primary structural and functional constituents of biological tissues, especially cell membranes. Along with membrane formation, lipids play also a crucial role in cell signalling, inflammation and energy storage. It was shown recently that lipid metabolism disorders play an important role in carcinogenesis and development. As well, the role of lipids in disease is particularly relevant for bacterial infections, during which several lipid bacterial virulence factors are recognized by the human innate immune response, such as lipopolysaccharide in Gram-negative bacteria, lipoteichoic acid in Gram-positive bacteria, and lipoglycans in mycobacteria. Compared to nucleic acids and proteins, a complete analysis of the lipidome, which is the comprehensive characterization of different lipid families, is usually very challenging due to the heterogeneity of lipid classes and their intrinsic physicoproperties caused by variations in the constituents of each class. Understanding the chemical diversity of lipids is therefore crucial to understanding their biological relevance and, as a consequence, their use as potential biomarkers for non-infectious and infectious diseases. This mini-review exposes the current knowledge and limitations of the use of lipids as biomarkers of the top global killers which are cancer and bacterial infections.

Comparative metabolite profiling of a metastatic and primary melanoma cell line using untargeted metabolomics: A case study

Melanoma accounts for more than 60% of deaths associated with skin cancer, making its early detection through dermatological screening essential for improved treatment outcomes. Early detection and successful treatment of melanoma can dramatically increase the 5-year survival rate from 14 to 98%. To support such efforts, comprehensive identification of metabolite patterns capable of describing cancer progression will help support the foundational knowledge necessary to build early detection platforms for intervention prior to metastasis. Using an UPLC-MS, as part of a cell-based, untargeted metabolomics approach, we profiled the metabolomes of WM-226-4 and WM-115 cells. Derived from the metastatic and the primary sites of the same individual, these two cell lines represent a paired melanoma cancer cell line. Progenesis and MetaboAnalyst, platforms dedicated to metabolomics data analysis, were used to establish a panel of differentially expressed metabolites across these two stages of melanoma. In addition, mummichog was used to identify the affected pathways. A total of 12 differentially expressed metabolites including amino acids, carnitine, acylcarnitine, and a limited set of lipids were identified. The significantly differing metabolites are components of a diverse set of metabolic pathways (e.g., glycerophospholipid metabolism, carnitine shuttle, tryptophan metabolism), that have biological implications for the survival and dissemination of metastatic melanoma cells.

LC-MS-based serum fingerprinting reveals significant dysregulation of phospholipids in chronic heart failure

Cardiac and extracardiac lipid metabolism is known to be significantly altered in the course of the heart failure with reduced ejection fraction (HF-REF), however the precise mechanisms are not fully elucidated. The aim of the study was to use of untargeted metabolomics to identify and validate changes in the blood metabolites profile, occurring as a result of HF-REF development. The analyses were performed first in the derivation set (36 chronic HF-REF patients and 19 controls without the disease) and repeated in validation cohort (31 chronic HF-REF patients and 20 controls). Independent analyses of both sets revealed statistically significant decline in intensities of phosphatidylcholine (PC): 34:4 and 36:5, lysophosphatidylcholine (lyso-PC): 14:0, 15:0, 18:0, 18:2, 20:3, lysophosphatidylethanolamine (lyso-PE): 18:1 and 18:2 in chronic HF-REF patients. More symptomatic patients and those with ischaemic etiology of HF-REF presented greater deficit in phospholipids (PLs) intensities. The decrease of identified PLs intensities (as compared to controls) correlated with decreased serum cholesterol level, impaired renal function, reduced exercise capacity, enhanced ventilatory response and metabolic parameters associated with altered fatty acids oxidation. In multiple regression analysis PLs deficit was significantly associated with age, carnitines serum intensity, renal function, uric acid, cholesterol level. In conclusion, HF-REF is associated with significant disturbances in phospholipids metabolism. Greater reduction in serum intensities of particular identified PLs is associated with older age, worse clinical condition, impaired oxidative muscle metabolism and enhanced catabolic status.

Identification of the lipid biomarkers from plasma in idiopathic pulmonary fibrosis by Lipidomics

Background

Idiopathic pulmonary fibrosis (IPF) is an irreversible interstitial pulmonary disease featured by high mortality, chronic and progressive course, and poor prognosis with unclear etiology. Currently, more studies have been focusing on identifying biomarkers to predict the progression of IPF, such as genes, proteins, and lipids. Lipids comprise diverse classes of molecules and play a critical role in cellular energy storage, structure, and signaling. The role of lipids in respiratory diseases, including cystic fibrosis, asthma and chronic obstructive pulmonary disease (COPD) has been investigated intensely in the recent years. The human serum lipid profiles in IPF patients however, have not been thoroughly understood and it will be very helpful if there are available molecular biomarkers, which can be used to monitor the disease progression or provide prognostic information for IPF disease.

Methods

In this study, we performed the ultraperformance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UPLC-QTOF/MS) to detect the lipid variation and identify biomarker in plasma of IPF patients. The plasma were from 22 IPF patients before received treatment and 18 controls.

Results

A total of 507 individual blood lipid species were determined with lipidomics from the 40 plasma samples including 20 types of fatty acid, 159 types of glycerolipids, 221 types of glycerophospholipids, 47 types of sphingolipids, 46 types of sterol lipids, 7 types of prenol lipids, 3 types of saccharolipids, and 4 types of polyketides. By comparing the variations in the lipid metabolite levels in IPF patients, a total of 62 unique lipids were identified by statistical analysis including 24 kinds of glycerophoslipids, 30 kinds of glycerolipids, 3 kinds of sterol lipids, 4 kinds of sphingolipids and 1 kind of fatty acids. Finally, 6 out of 62 discriminating lipids were selected as the potential biomarkers, which are able to differentiate between IPF disease and controls with ROC analysis.

Conclusions

Our results provided vital information regarding lipid metabolism in IPF patients and more importantly, a few potentially promising biomarkers were firstly identified which may have a predictive role in monitoring and diagnosing IPF disease.

Electronic supplementary material

The online version of this article (10.1186/s12890-017-0513-4) contains supplementary material, which is available to authorized users.

Applications of Metabolomics in Cancer Studies

Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.

Systematic biobanking, novel imaging techniques, and advanced molecular analysis for precise tumor diagnosis and therapy: The Polish MOBIT project

Personalized and precision medicine is gaining recognition due to the limitations by standard diagnosis and treatment; many areas of medicine, from cancer to psychiatry, are moving towards tailored and individualized treatment for patients based on their clinical characteristics and genetic signatures as well as novel imaging techniques. Advances in whole genome sequencing have led to identification of genes involved in a variety of diseases. Moreover, biomarkers indicating severity of disease or susceptibility to treatment are increasingly being characterized. The continued identification of new genes and biomarkers specific to disease subtypes and individual patients is essential and inevitable for translation into personalized medicine, in estimating both, disease risk and response to therapy. Taking into consideration the mostly unsolved necessity of tailored therapy in oncology the innovative project MOBIT (molecular biomarkers for individualized therapy) was designed. The aims of the project are: (i) establishing integrative management of precise tumor diagnosis and therapy including systematic biobanking, novel imaging techniques, and advanced molecular analysis by collecting comprehensive tumor tissues, liquid biopsies (whole blood, serum, plasma), and urine specimens (supernatant; sediment) as well as (ii) developing personalized lung cancer diagnostics based on tumor heterogeneity and integrated genomics, transcriptomics, metabolomics, and radiomics PET/MRI analysis. It will consist of 5 work packages. In this paper the rationale of the Polish MOBIT project as well as its design is presented. (iii) The project is to draw interest in and to invite national and international, private and public, preclinical and clinical initiatives to establish individualized and precise procedures for integrating novel targeted therapies and advanced imaging techniques.

Development of LC-QTOF-MS method for human lung tissue fingerprinting. A preliminary application to nonsmall cell lung cancer

The major histologic subtypes of non-small cell lung cancer (NSCLC) include adenocarcinoma (ADC), squamous cell lung carcinoma (SCC), and large-cell carcinoma (LCC). Clinical trials of targeted agents and newer chemotherapy agents yielded differences in outcomes according to histologic subgroups providing a rationale for histology-based treatment in NSCLC. Currently, NSCLC subtyping is performed based on histopathological examinations and immunohistochemistry. However available methods leave about 10% of NSCLC cases as not otherwise specified. The purpose of this study was development of an LC-QTOF-MS method for human lung tissue metabolic fingerprinting that could discriminate NSCLC histological subtypes and propose biomarkers candidates that could support proper NSCLC diagnosis. Metabolites were extracted with acetonitrile or methanol/ethanol and different chromatographic conditions were tested. In the final method 10 mg of lung tissue was homogenized with 50% methanol and metabolites were extracted with acetonitrile. Metabolites were separated on C8-RP and HILIC columns. About 3500 and 2000 of metabolic features (in both ion modes) were detected with good repeatability (CV < 20%) by RP and HILIC methods, respectively. Lung tumor and control tissue samples obtained from NSCLC patients were analyzed with developed methodology. Acylcarnitines, fatty acids, phospholipids, and amino acids were found more abundant in tumor as compared to control tissue. Acylcarnitines, lysophospholipids, creatinine, creatine, and alanine were identified as potential targets enabling classification of NSCLC subtypes.

LC-MS-Based Metabolic Fingerprinting of Aqueous Humor

Aqueous humor (AH) is a transparent fluid which fills the anterior and posterior chambers of the eye. It supplies nutrients and removes metabolic waste from avascular tissues in the eye. Proper homeostasis of AH is required to maintain adequate intraocular pressure as well as optical and refractive properties of the eye. Application of metabolomics to study human AH may improve knowledge about the molecular mechanisms of eye diseases. Until now, global analysis of metabolites in AH has been mainly performed using NMR. Among the analytical platforms used in metabolomics, LC-MS allows for the highest metabolome coverage. The aim of this study was to develop a method for extraction and analysis of AH metabolites by LC-QTOF-MS. Different protocols for AH preparation were tested. The best results were obtained when one volume of AH was mixed with one volume of methanol : ethanol (1 : 1). In the final method, 2 µL of extracted sample was analyzed by LC-QTOF-MS. The method allowed for reproducible measurement of over 1000 metabolic features. Almost 250 metabolites were identified in AH and assigned to 47 metabolic pathways. This method is suitable to study the potential role of amino acids, lipids, oxidative stress, or microbial metabolites in development of ocular diseases.

Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics

INTRODUCTION

Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.

OBJECTIVES

Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case-control, prognostic and longitudinal study designs.

METHODS

A literature search of the current relevant primary research was performed.

RESULTS

Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case-control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance.

CONCLUSION

Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies.