NMR-based metabolomics studies of human prostate cancer tissue

Introduction

Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. Serum prostate-specific antigen (PSA) remains the most used biomarker in the detection and management of patients with PCa, in spite of the problems related with its low specificity, false positive rate and overdiagnosis. Furthermore, PSA is unable to discriminate indolent from aggressive PCa, which can lead to overtreatment. Early diagnosed and treated PCa can have a good prognosis and is potentially curable. Therefore, the discovery of new biomarkers able to detect clinically significant aggressive PCa is urgently needed.

Methods

This revision was based on an electronic literature search, using Pubmed, with Nuclear Magnetic Resonance (NMR), tissue and prostate cancer as keywords. All metabolomic studies performed in PCa tissues by NMR spectroscopy, from 2007 until March 2018, were included in this review.

Results

In the context of cancer, metabolomics allows the analysis of the entire metabolic profile of cancer cells. Several metabolic alterations occur in cancer cells to sustain their abnormal rates of proliferation. NMR proved to be a suitable methodology for the evaluation of these metabolic alterations in PCa tissues, allowing to unveil alterations in citrate, spermine, choline, choline-related compounds, lactate, alanine and glutamate.

Conclusion

The study of the metabolic alterations associated with PCa progression, accomplished by the analysis of PCa tissue by NMR, offers a promising approach for elucidating biochemical pathways affected by PCa and also for discovering new clinical biomarkers. The main metabolomic alterations associated with PCa development and promising biomarker metabolites for diagnosis of PCa were outlined.

     

The discovery of putative urine markers for the specific detection of prostate tumor by integrative mining of public genomic profiles

Urine has emerged as an attractive biofluid for the noninvasive detection of prostate cancer (PCa). There is a strong imperative to discover candidate urinary markers for the clinical diagnosis and prognosis of PCa. The rising flood of various omics profiles presents immense opportunities for the identification of prospective biomarkers. Here we present a simple and efficient strategy to derive candidate urine markers for prostate tumor by mining cancer genomic profiles from public databases. Prostate, bladder and kidney are three major tissues from which cellular matters could be released into urine. To identify urinary markers specific for PCa, upregulated entities that might be shed in exosomes of bladder cancer and kidney cancer are first excluded. Through the ontology-based filtering and further assessment, a reduced list of 19 entities encoding urinary proteins was derived as putative PCa markers. Among them, we have found 10 entities closely associated with the process of tumor cell growth and development by pathway enrichment analysis. Further, using the 10 entities as seeds, we have constructed a protein-protein interaction (PPI) subnetwork and suggested a few urine markers as preferred prognostic markers to monitor the invasion and progression of PCa. Our approach is amenable to discover and prioritize potential markers present in a variety of body fluids for a spectrum of human diseases.     

Biomarkers intersect with the exposome

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment.     

Biomarkers intersect with the exposome

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment.     

Proteomics of human prostate cancer biospecimens: the global,systems-wide perspective for Protein markers with potential clinical utility

Despite intense global efforts, no new clinical and/or viable biomarkers have been established to overcome the limitation of the prostate specific antigen in the early diagnosis and prognosis of prostate cancer (PCa). The current proteomic approaches to PCa biomarker discovery, each have distinct advantages and disadvantages, yet when combined hold real promise in the coming years. One key approach to this effort is the development of non-targeted, depletion-free and quantitative liquid chromatography–ultra high resolution tandem mass spectrometry (LC–MS) pipelines for the systems-wide interrogation of the diverse proteomes encompassed in whole tissue and blood serum or plasma. Derived quantitative proteomes can be decoded for their biomedical relevance with advanced bioinformatics and bibliographic mining to yield promising ‘molecular portraits’ that can gauge prostatic disease at the serological level. Their functional annotation, although potentially useful, is beyond our current level of biological understanding and should not be requisite for their effective use in the clinical monitoring of prostatic disease.     

miRNA Expression Analyses in Prostate Cancer Clinical Tissues

A critical challenge in prostate cancer (PCa) clinical management is posed by the inadequacy of currently used biomarkers for disease screening, diagnosis, prognosis and treatment. In recent years, microRNAs (miRNAs) have emerged as promising alternate biomarkers for prostate cancer diagnosis and prognosis. However, the development of miRNAs as effective biomarkers for prostate cancer heavily relies on their accurate detection in clinical tissues. miRNA analyses in prostate cancer clinical specimens is often challenging owing to tumor heterogeneity, sampling errors, stromal contamination etc. The goal of this article is to describe a simplified workflow for miRNA analyses in archived FFPE or fresh frozen prostate cancer clinical specimens using a combination of quantitative real-time PCR (RT-PCR) and in situ hybridization (ISH). Within this workflow, we optimize the existing methodologies for miRNA extraction from FFPE and frozen prostate tissues and expression analyses by Taqman-probe based miRNA RT-PCR. In addition, we describe an optimized method for ISH analyses formiRNA detection in prostate tissues using locked nucleic acid (LNA)- based probes. Our optimized miRNA ISH protocol can be applied to prostate cancer tissue slides or prostate cancer tissue microarrays (TMA).     

Molecular mechanisms in prostate cancer. A review

Genetic studies have provided remarkable clues to the causes of prostate cancer (PCa). For example, in addition to the expected role of androgens in facilitating the development of PCa, the possibility that infections might lead to prostate cancer has been raised with the identification of RNASEL and MSR1 as familial prostate cancer genes; that insight will profoundly affect future studies and may ultimately lead to new approaches to the prevention of prostate cancer. The identification of key molecular alterations in prostate cancer cells implicates carcinogen defenses, including GSTP1, growth factor signaling pathways (such as NKX3.1, PTEN and p27) and androgens as critical determinants of the phenotype of PCa cells and defines specific targets for detection, diagnosis and treatment of PCa.     

Untargeted metabolomics: an overview of its usefulness and future potential in prenatal diagnosis

ABSTRACT

Introduction: Metabolomics opens up new avenues for biomarker discovery in different branches of medicine, including perinatology. Chromosomal aberration, preterm delivery (PTD), congenital heart defects, spina bifida, chorioamnionitis, and low birth weight are the main perinatal pathologies. Investigations using untargeted metabolomics have found the candidate metabolites for diagnostic biomarkers.

Areas covered: This review describes areas of prenatal diagnosis in which untargeted metabolomics has been used. Data on the disease, type of sample, techniques used, number of samples used in the study, and metabolites obtained including the sign of their regulation are summarized.

Expert commentary: Untargeted metabolomics is a powerful tool which can shed a new light on prenatal diagnostics. It helps to discover affected metabolic pathways what may help to reveal disease pathogenesis and propose potential biomarkers. Among others, glycerol and 2- and 3-hydroxybutyrate were proposed as markers of chromosomal aberration. Serum metabolic signature of PTD was characterized by increased lipids and decreased levels of hypoxanthine, tryptophane, and pyroglutamic acid. Lower level lipids and vitamin D3 metabolites together with increased bilirubin level in maternal serum were associated with macrosomia. However, to give a real value to those assays and allow their clinical application multicenter, large cohort validation studies are necessary.     

Epidermal Growth Factor Receptor in Prostate Cancer Derived Exosomes

Exosomes proteins and microRNAs have gained much attention as diagnostic tools and biomarker potential in various malignancies including prostate cancer (PCa). However, the role of exosomes and membrane-associated receptors, particularly epidermal growth factor receptor (EGFR) as mediators of cell proliferation and invasion in PCa progression remains unexplored. EGFR is frequently overexpressed and has been associated with aggressive forms of PCa. While PCa cells and tissues express EGFR, it is unknown whether exosomes derived from PCa cells or PCa patient serum contains EGFR. The aim of this study was to detect and characterize EGFR in exosomes derived from PCa cells, LNCaP xenograft and PCa patient serum. Exosomes were isolated from conditioned media of different PCa cell lines; LNCaP xenograft serum as well as patient plasma/serum by differential centrifugation and ultracentrifugation on a sucrose density gradient. Exosomes were confirmed by electron microscopy, expression of exosomal markers and NanoSight^™ analysis. EGFR expression was determined by western blot analysis and ELISA. This study demonstrates that exosomes may easily be derived from PCa cell lines, serum obtained from PCa xenograft bearing mice and clinical samples derived from PCa patients. Presence of exosomal EGFR in PCa patient exosomes may present a novel approach for measuring of the disease state. Our work will allow to build on this finding for future understanding of PCa exosomes and their potential role in PCa progression and as minimal invasive biomarkers for PCa.     

Urine metabolomics analysis for biomarker discovery and detection of jaundice syndrome in patients with liver disease

Metabolomics is a powerful new technology that allows for the assessment of global metabolic profiles in easily accessible biofluids and biomarker discovery in order to distinguish between diseased and nondiseased status information. Deciphering the molecular networks that distinguish diseases may lead to the identification of critical biomarkers for disease aggressiveness. However, current diagnostic methods cannot predict typical Jaundice syndrome (JS) in patients with liver disease and little is known about the global metabolomic alterations that characterize JS progression. Emerging metabolomics provides a powerful platform for discovering novel biomarkers and biochemical pathways to improve diagnostic, prognostication, and therapy. Therefore, the aim of this study is to find the potential biomarkers from JS disease by using a nontarget metabolomics method, and test their usefulness in human JS diagnosis. Multivariate data analysis methods were utilized to identify the potential biomarkers. Interestingly, 44 marker metabolites contributing to the complete separation of JS from matched healthy controls were identified. Metabolic pathways (Impact-value≥0.10) including alanine, aspartate, and glutamate metabolism and synthesis and degradation of ketone bodies were found to be disturbed in JS patients. This study demonstrates the possibilities of metabolomics as a diagnostic tool in diseases and provides new insight into pathophysiologic mechanisms.     

Sarcosine Up-Regulates Expression of Genes Involved in Cell Cycle Progression of Metastatic Models of Prostate Cancer

The effects of sarcosine on the processes driving prostate cancer (PCa) development remain still unclear. Herein, we show that a supplementation of metastatic PCa cells (androgen independent PC-3 and androgen dependent LNCaP) with sarcosine stimulates cells proliferation in vitro. Similar stimulatory effects were observed also in PCa murine xenografts, in which sarcosine treatment induced a tumor growth and significantly reduced weight of treated mice (p < 0.05). Determination of sarcosine metabolism-related amino acids and enzymes within tumor mass revealed significantly increased glycine, serine and sarcosine concentrations after treatment accompanied with the increased amount of sarcosine dehydrogenase. In both tumor types, dimethylglycine and glycine-N-methyltransferase were affected slightly, only. To identify the effects of sarcosine treatment on the expression of genes involved in any aspect of cancer development, we further investigated expression profiles of excised tumors using cDNA electrochemical microarray followed by validation using the semi-quantitative PCR. We found 25 differentially expressed genes in PC-3, 32 in LNCaP tumors and 18 overlapping genes. Bioinformatical processing revealed strong sarcosine-related induction of genes involved particularly in a cell cycle progression. Our exploratory study demonstrates that sarcosine stimulates PCa metastatic cells irrespectively of androgen dependence. Overall, the obtained data provides valuable information towards understanding the role of sarcosine in PCa progression and adds another piece of puzzle into a picture of sarcosine oncometabolic potential.     

Magnetic resonance spectroscopy detectable metabolomic fingerprint of response to antineoplastic treatment

Targeted therapeutic approaches are increasingly being implemented in the clinic, but early detection of response frequently presents a challenge as many new therapies lead to inhibition of tumor growth rather than tumor shrinkage. Development of novel non-invasive methods to monitor response to treatment is therefore needed. Magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging are non-invasive imaging methods that can be employed to monitor metabolism, and previous studies indicate that these methods can be useful for monitoring the metabolic consequences of treatment that are associated with early drug target modulation. However, single-metabolite biomarkers are often not specific to a particular therapy. Here we used an unbiased 1H MRS-based metabolomics approach to investigate the overall metabolic consequences of treatment with the phosphoinositide 3-kinase inhibitor LY294002 and the heat shock protein 90 inhibitor 17AAG in prostate and breast cancer cell lines. LY294002 treatment resulted in decreased intracellular lactate, alanine fumarate, phosphocholine and glutathione. Following 17AAG treatment, decreased intracellular lactate, alanine, fumarate and glutamine were also observed but phosphocholine accumulated in every case. Furthermore, citrate, which is typically observed in normal prostate tissue but not in tumors, increased following 17AAG treatment in prostate cells. This approach is likely to provide further information about the complex interactions between signaling and metabolic pathways. It also highlights the potential of MRS-based metabolomics to identify metabolic signatures that can specifically inform on molecular drug action.     

Metabolomics for mitochondrial and cancer studies

Metabolomics, a high-throughput global metabolite analysis, is a burgeoning field, and in recent times has shown substantial evidence to support its emerging role in cancer diagnosis, cancer recurrence, and prognosis, as well as its impact in identifying novel cancer biomarkers and developing cancer therapeutics. Newly evolving advances in disease diagnostics and therapy will further facilitate future growth in the field of metabolomics, especially in cancer, where there is a dire need for sensitive and more affordable diagnostic tools and an urgency to develop effective therapies and identify reliable biomarkers to predict accurately the response to a therapy. Here, we review the application of metabolomics in cancer and mitochondrial studies and its role in enabling the understanding of altered metabolism and malignant transformation during cancer growth and metastasis. The recent developments in the area of metabolic flux analysis may help to close the gap between clinical metabolomics research and the development of cancer metabolome. In the era of personalized medicine with more and more patient specific targeted therapies being used, we need reliable, dynamic, faster, and yet sensitive biomarkers both to track the disease and to develop and evolve therapies during the course of treatment. Recent advances in metabolomics along with the novel strategies to analyze, understand, and construct the metabolic pathways opens this window of opportunity in a very cost-effective manner.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

Serum metabonomics study of pregnant women with gestational diabetes mellitus based on LC-MS

ObjectiveThrough metabolomics method, the objective of the paper is to differentially screen serum metabolites of GDM patients and healthy pregnant women, to explore potential biomarkers of GDM and analyze related pathways, and to explain the potential mechanism and biological significance of GDM.MethodsThe serum samples from 30 GDM patients and 30 healthy pregnant women were selected to conduct non-targeted metabolomics study by liquid chromatography-mass spectrometry. The differential metabolites between the two groups were searched and the metabolic pathway was analyzed by KEGG database.ResultsMultivariate statistical analysis found that serum metabolism in GDM patients was different significantly from healthy pregnant women, 36 differential metabolites and corresponding metabolic pathways were identified in serum, which involved several metabolic ways like, fatty acid metabolism, butyric acid metabolism, bile secretion, and amino acid metabolism.ConclusionThe discovery of these biomarkers provided a new theoretical basis and experimental basis for further study of the early diagnosis and pathogenesis of GDM. At the same time, LC-MS-based serum metabolomics methods also showed great application values in disease diagnosis and mechanism research.     

Biomarkers in renal cell carcinoma: a metabolomics approach

Since Otto Warburg, many studies have explored the unique metabolic phenotype of cancer cells highlighting the value and applicability of metabolomics in the oncology field, particularly in the development of cancer biomarkers. With respect to renal cell carcinoma (RCC), a metabolomics approach would own a great potential since urinary system is intimately connected with urine and, this biofluid, offers some advantages allowing the development of an assay suitable for use in clinical practice. Moreover, the assessment of metabolic derangements characteristics of RCC might provide a complete health assessment of this pathology, enabling the development of novel targeted therapies and even the stratification of responsive patients to specific therapeutic options improving the effectiveness of therapy. Metabolomic studies performed so far showed that the RCC metabolic signature is characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid catabolism, known to be crucial to cell proliferation. Despite some of those alterations are common to carcinogenesis, the potential role of acylcarnitines, gentisate, α-ketoglutarate and quinolinate in RCC pathophysiology has been proposed recently. The ability of metabolomics to discriminate between RCC and normal samples shows convincing evidence of its applicability in RCC management. Furthermore, the studies already carried out have not only tried to unveil the metabolic profile of RCC but also to evaluate the impact of some factors, namely technical, in RCC-metabolomics research. This type of study is pivotal in the design of metabolomics studies, helping to increase the reliability of the results. The present review updates the current knowledge on the metabolic alterations recognized in the RCC, and provides insight to the characteristics, strengths, limitations, and recent advances in RCC-metabolomics studies, always keeping in mind its potential application in clinical/health areas as a biomarker discovery tool.