Recent Advances in Metabolic Profiling And Imaging of Prostate Cancer

Common alterations in plasma free amino acid profiles and gut microbiota-derived tryptophan metabolites of five types of cancer patients

Amino acids not only play a vital role in the synthesis of biological molecules such as proteins in cancer malignant cells, they are also essential metabolites for immune cell activation and antitumor effects in the tumor microenvironment. The abnormal changes in amino acid metabolism are closely related to the occurrence and development of tumors and immunity. Intestinal microorganisms play an essential role in amino acid metabolism, and tryptophan and its intestinal microbial metabolites are typical representatives. However, it is known that the cyclic amino acid profile is affected by specific cancer types, so relevant studies mainly focus on one type of cancer and rarely study different cancer forms at the same time. The objective of this study was to examine the PFAA profile of five cancer patients and the characteristics of tryptophan intestinal microbial metabolites to determine whether there are general amino acid changes across tumors. Plasma samples were collected from esophageal (n = 53), lung (n = 73), colorectal (n = 94), gastric (n = 55), breast cancer (n = 25), and healthy control (HC) (n = 139) subjects. PFAA profile and tryptophan metabolites were measured, and their perioperative changes were examined using high-performance liquid chromatography. Univariate analysis revealed significant differences between cancer patients and HC. Furthermore, multivariate analysis discriminated cancer patients from HC. Regression diagnosis models were established for each cancer group using differential amino acids from univariate analysis. Receiver-operating characteristic analysis was applied to evaluate these diagnosis models. Finally, GABA, arginine, tryptophan, taurine, glutamic acid, and melatonin showed common alterations across all types of cancer patients. Metabolic pathway analysis shows that the most significant enrichment pathways were tryptophan, arginine, and proline metabolism. This study provides evidence that common alterations of the metabolites mentioned above suggest their role in the pathogenesis of each cancer patient. It was suggested that multivariate models based on PFAA profiles and tryptophan metabolites might be applicable in the screening of cancer patients.

Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling

Prostate cancer (PCa) remains one of the leading causes of cancer mortality in men worldwide, currently lacking specific, early detection and staging biomarkers. In this regard, modern research focuses efforts on the discovery of novel molecules that could represent potential future non-invasive biomarkers for the diagnosis of PCa, as well as therapeutic targets. Mounting evidence shows that cancer cells express an altered metabolism in their early stages, making metabolomics a promising tool for the discovery of altered pathways and potential biomarker molecules. In this study, we first performed untargeted metabolomic profiling on 48 PCa plasma samples and 23 healthy controls using ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-[ESI+]-MS) for the discovery of metabolites with altered profiles. Secondly, we selected five molecules (L-proline, L-tryptophan, acetylcarnitine, lysophosphatidylcholine C18:2 and spermine) for the downstream targeted metabolomics and found out that all the molecules, regardless of the PCa stage, were decreased in the PCa plasma samples when compared to the controls, making them potential biomarkers for PCa detection. Moreover, spermine, acetylcarnitine and L-tryptophan had very high diagnostic accuracy, with AUC values of 0.992, 0.923 and 0.981, respectively. Consistent with other literature findings, these altered metabolites could represent future specific and non-invasive candidate biomarkers for PCa detection, which opens novel horizons in the field of metabolomics.

Circulating metabolite biomarkers: a game changer in the human prostate cancer diagnosis

PURPOSE

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men in Western and Asian countries. Serum prostate-specific antigen (PSA) test has been the routine diagnostic method despite the tremendous research in diagnostic markers for early detection of PCa. A shift towards a promising and potential biomarker for PCa detection is through metabolomic profiling of biofluids, particularly the blood and urine samples. Finding reliable, routinely usable circulating metabolite biomarkers may not be a distant reality.

METHODS

We performed a PubMed-based literature search of metabolite biomarkers in blood and urine for the early detection of prostate cancer. The timeline of these searches was limited between 2007 and 2022 and the following keywords were used: 'metabolomics', 'liquid biopsy', 'circulating metabolites', 'serum metabolite', 'plasma metabolite', and 'urine metabolite' with respect to 'prostate cancer'. We focussed only on diagnosis-based studies with only the subject-relevant articles published in the English language and excluded all of the other irrelevant publications that included prostate tissue biomarkers and cell line biomarkers.

RESULTS

We have consolidated all the blood and urine-based potential metabolite candidates in individual as well as panels, including lipid classes, fatty acids, amino acids, and volatile organic compounds which may become useful for PCa diagnosis.

CONCLUSION

All these metabolome findings unveil the impact of different dimensions of PCa development, giving a promising strategy to diagnose the disease since suspected individuals can be subjected to repeated and largescale blood and urine testing.

Gene's expression underpinning the divergent predictive value of [18F]F-fluorodeoxyglucose and prostate-specific membrane antigen positron emission tomography in primary prostate cancer: a bioinformatic and experimental study

BACKGROUND

Positron Emission Tomography (PET) imaging with Prostate-Specific Membrane Antigen (PSMA) and Fluorodeoxyglucose (FDG) represent promising biomarkers for risk-stratification of Prostate Cancer (PCa). We verified whether the expression of genes encoding for PSMA and enzymes regulating FDG cellular uptake are independent and additive prognosticators in PCa.

METHODS

mRNA expression of genes involved in glucose metabolism and PSMA regulation obtained from primary PCa specimens were retrieved from open-source databases and analyzed using an integrative bioinformatics approach. Machine Learning (ML) techniques were used to create predictive Progression-Free Survival (PFS) models. Cellular models of primary PCa with different aggressiveness were used to compare [18F]F-PSMA-1007 and [18F]F-FDG uptake kinetics in vitro. Confocal microscopy, immunofluorescence staining, and quantification analyses were performed to assess the intracellular and cellular membrane PSMA expression.

RESULTS

ML analyses identified a predictive functional network involving four glucose metabolism-related genes: ALDOB, CTH, PARP2, and SLC2A4. By contrast, FOLH1 expression (encoding for PSMA) did not provide any additive predictive value to the model. At a cellular level, the increase in proliferation rate and migratory potential by primary PCa cells was associated with enhanced FDG uptake and decreased PSMA retention (paralleled by the preferential intracellular localization).

CONCLUSIONS

The overexpression of a functional network involving four glucose metabolism-related genes identifies a higher risk of disease progression since the earliest phases of PCa, in agreement with the acknowledged prognostic value of FDG PET imaging. By contrast, the prognostic value of PSMA PET imaging is independent of the expression of its encoding gene FOLH1. Instead, it is influenced by the protein docking to the cell membrane, regulating its accessibility to tracer binding.

Epigenetic Inheritance From Normal Origin Cells Can Determine the Aggressive Biology of Tumor-Initiating Cells and Tumor Heterogeneity

The acquisition of genetic- and epigenetic-abnormalities during transformation has been recognized as the two fundamental factors that lead to tumorigenesis and determine the aggressive biology of tumor cells. However, there is a regularity that tumors derived from less-differentiated normal origin cells (NOCs) usually have a higher risk of vascular involvement, lymphatic and distant metastasis, which can be observed in both lymphohematopoietic malignancies and somatic cancers. Obviously, the hypothesis of genetic- and epigenetic-abnormalities is not sufficient to explain how the linear relationship between the cellular origin and the biological behavior of tumors is formed, because the cell origin of tumor is an independent factor related to tumor biology. In a given system, tumors can originate from multiple cell types, and tumor-initiating cells (TICs) can be mapped to different differentiation hierarchies of normal stem cells, suggesting that the heterogeneity of the origin of TICs is not completely chaotic. TIC’s epigenome includes not only genetic- and epigenetic-abnormalities, but also established epigenetic status of genes inherited from NOCs. In reviewing previous studies, we found much evidence supporting that the status of many tumor-related “epigenetic abnormalities” in TICs is consistent with that of the corresponding NOC of the same differentiation hierarchy, suggesting that they may not be true epigenetic abnormalities. So, we speculate that the established statuses of genes that control NOC’s migration, adhesion and colonization capabilities, cell-cycle quiescence, expression of drug transporters, induction of mesenchymal formation, overexpression of telomerase, and preference for glycolysis can be inherited to TICs through epigenetic memory and be manifested as their aggressive biology. TICs of different origins can maintain different degrees of innate stemness from NOC, which may explain why malignancies with stem cell phenotypes are usually more aggressive.

Genetically Predicted Circulating Concentrations of Alanine and Alanine Aminotransferase Were Associated with Prostate Cancer Risk

Object

Prostate cancer is one of the leading malignancies in men worldwide. Previous observational studies have linked amino acids and transaminase with altered risk of prostate cancer. However, whether these associations were causal remained unclear. Therefore, we conducted a Mendelian randomization (MR) to assess their potential causal associations.

Methods

Summary-level data for prostate cancer were obtained from a meta-analysis of genome-wide association studies (GWAS) including 79,148 prostate cancer cases and 61,106 controls of European descent. Instrumental variables (IVs) of amino acids and alanine aminotransferase (ALT) were obtained from a GWAS of 86,507 European individuals and a GWAS of 312,572 participants from the UK Biobank, respectively. MR analyses were performed using inverse-variance-weighted (IVW), likelihood-based, MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test and MR-Egger regression.

Results

Genetically predicted circulating concentrations of alanine were associated with an increased risk of prostate cancer (odds ratio (OR): 1.16, 95% confidence interval (CI): 1.01-1.33, P=0.037 by IVW). Consistently, genetically predicted ALT was inversely associated with the risk of prostate cancer (OR: 0.43, 95% CI: 0.27-0.68, P=3.28×10^-4 by IVW). MR-Egger regression did not indicate evidence of directional pleiotropy and sensitivity analyses yielded consistent associations.

Conclusion

Our study revealed that genetically predicted circulating alanine and ALT levels were associated with an altered risk of prostate cancer, suggesting their potential roles in the development of prostate cancer. Whether targeting alanine, ALT or its downstream effectors are helpful in reducing prostate cancer incidence warrants further investigation.

Beyond liquid biopsy: Toward non-invasive assays for distanced cancer diagnostics in pandemics

Liquid biopsy technologies have seen a significant improvement in the last decade, offering the possibility of reliable analysis and diagnosis from several biological fluids. The use of these technologies can overcome the limits of standard clinical methods, related to invasiveness and poor patient compliance. Along with this there are now mature examples of lab-on-chips (LOC) which are available and could be an emerging and breakthrough technology for the present and near-future clinical demands that provide sample treatment, reagent addition and analysis in a sample-in/answer-out approach. The possibility of combining non-invasive liquid biopsy and LOC technologies could greatly assist in the current need for minimizing exposure and transmission risks. The recent and ongoing pandemic outbreak of SARS-CoV-2, indeed, has heavily influenced all aspects of life worldwide. Ordinary tasks have been forced to switch from “in presence” to “distanced”, limiting the possibilities for a large number of activities in all fields of life outside of the home. Unfortunately, one of the settings in which physical distancing has assumed noteworthy consequences is the screening, diagnosis and follow-up of diseases.

In this review, we analyse biological fluids that are easily collected without the intervention of specialized personnel and the possibility that they may be used -or not-for innovative diagnostic assays. We consider their advantages and limitations, mainly due to stability and storage and their integration into Point-of-Care diagnostics, demonstrating that technologies in some cases are mature enough to meet current clinical needs.

Simultaneous Measurement of Tricarboxylic Acid Cycle Intermediates in Different Biological Matrices Using Liquid Chromatography-Tandem Mass Spectrometry; Quantitation and Comparison of TCA Cycle Intermediates in Human Serum, Plasma, Kasumi-1 Cell and Murine Liver Tissue

The tricarboxylic acid (TCA) cycle is a central part of carbon and energy metabolism, also connecting to glycolysis, amino acid, and lipid metabolism. The quantitation of the TCA cycle intermediate within one method is lucrative due to the interest in central carbon metabolism profiling in cells and tissues. In addition, TCA cycle intermediates in serum have been discovered to correspond as biomarkers to various underlying pathological conditions. In this work, an Liquid Chromatography-Mass Spectrometry/Mass Spectrometry-based quantification method is developed and validated, which takes advantage of fast, specific, sensitive, and cost-efficient precipitation extraction. Chromatographic separation is achieved while using Atlantis dC18 2.1 mm × 100 mm, particle size 3-μm of Waters column with a gradient elution mobile phase while using formic acid in water (0.1% v/v) and acetonitrile. Linearity was clearly seen over a calibration range of: 6.25 to 6400 ng/mL (r² > 0.980) for malic acid; 11.72 to 12,000 ng/mL (r² > 0.980) for cis-aconitic acid and L-aspartic acid; 29.30 to 30,000 ng/mL (r² > 0.980) for isocitric acid, l-serine, and l-glutamic acid; 122.07 to 125,000 ng/mL (r² > 0.980) for citric acid, glycine, oxo-glutaric acid, l-alanine, and l-glutamine; 527.34 to 540,000 ng/mL (r² > 0.980) for l-lactic acid; 976.56 to 1,000,000 ng/mL (r² > 0.980) for d-glucose; 23.44 to 24,000 ng/mL (r² > 0.980) for fumaric acid and succinic acid; and, 244.14 to 250,000 ng/mL (r² > 0.980) for pyruvic acid. Validation was carried out, as per European Medicines Agency (EMA) “guidelines on bioanalytical method validation”, for linearity, precision, accuracy, limit of detection (LOD), limit of quantification (LLOQ), recovery, matrix effect, and stability. The recoveries from serum and tissue were 79–119% and 77–223%, respectively. Using this method, we measured TCA intermediates in serum, plasma (NIST 1950 SRM), and in mouse liver samples. The concentration found in NIST SRM 1950 (n = 6) of glycine (246.4 µmol/L), l-alanine (302.4 µmol/L), and serine (92.9 µmol/L).

Nuclear magnetic resonance spectroscopy of human body fluids and in vivo magnetic resonance spectroscopy: Potential role in the diagnosis and management of prostate cancer

Prostate cancer is the most common solid organ cancer in men, and the second most common cause of male cancer-related mortality. It has few effective therapies, and is difficult to diagnose accurately. Prostate-specific antigen (PSA), which is currently the most effective diagnostic tool available, cannot reliably discriminate between different pathologies, and in fact only around 30% of patients found to have elevated levels of PSA are subsequently confirmed to actually have prostate cancer. As such, there is a desperate need for more reliable diagnostic tools that will allow the early detection of prostate cancer so that the appropriate interventions can be applied. Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopy (MRS) are 2 high throughput, noninvasive analytical procedures that have the potential to enable differentiation of prostate cancer from other pathologies using metabolomics, by focusing specifically on certain metabolites which are associated with the development of prostate cancer cells and its progression. The value that this type of approach has for the early detection, diagnosis, prognosis, and personalized treatment of prostate cancer is becoming increasingly apparent. Recent years have seen many promising developments in the fields of NMR spectroscopy and MRS, with improvements having been made to hardware as well as to techniques associated with the acquisition, processing, and analysis of related data. This review focuses firstly on proton NMR spectroscopy of blood serum, urine, and expressed prostatic secretions in vitro, and then on 1- and 2-dimensional proton MRS of the prostate in vivo. Major advances in these fields and methodological principles of data collection, acquisition, processing, and analysis are described along with some discussion of related challenges, before prospects that proton MRS has for future improvements to the clinical management of prostate cancer are considered.

The Multiple Roles and Therapeutic Potential of Molecular Chaperones in Prostate Cancer

Prostate cancer (PCa) is one of the most common cancer types in men worldwide. Heat shock proteins (HSPs) are molecular chaperones that are widely implicated in the pathogenesis, diagnosis, prognosis, and treatment of many cancers. The role of HSPs in PCa is complex and their expression has been linked to the progression and aggressiveness of the tumor. Prominent chaperones, including HSP90 and HSP70, are involved in the folding and trafficking of critical cancer-related proteins. Other members of HSPs, including HSP27 and HSP60, have been considered as promising biomarkers, similar to prostate-specific membrane antigen (PSMA), for PCa screening in order to evaluate and monitor the progression or recurrence of the disease. Moreover, expression level of chaperones like clusterin has been shown to correlate directly with the prostate tumor grade. Hence, targeting HSPs in PCa has been suggested as a promising strategy for cancer therapy. In the current review, we discuss the functions as well as the role of HSPs in PCa progression and further evaluate the approach of inhibiting HSPs as a cancer treatment strategy.

1H nuclear magnetic resonance-based metabolic profiling of cerebrospinal fluid to identify metabolic features and markers for tuberculosis meningitis

BACKGROUND

Tuberculosis meningitis (TBM) is the most severe form of tuberculosis, and currently lacks efficient diagnostic approaches. Metabolomics has the potential to differentiate patients with TBM from those with other forms of meningitis and meningitis-negative individuals. However, no systemic metabolomics research has compared the cerebrospinal fluid (CSF) of these patients.

METHODS

¹H nuclear magnetic resonance (NMR) was used for CSF metabolic profiling. Principal component analysis and orthogonal signal correction-partial least squares-discriminant analysis (OPLS-DA) were used to screen for important variables. The Human Metabolome Database was used to identify metabolites, and MetaboAnalyst 4.0 was used for pathway analysis and over-representation analysis.

RESULTS

OPLS-DA modeling could distinguish TBM from other forms of meningitis, and several significantly changed metabolites were identified. Additionally, 23, 6, and 21 metabolites were able to differentiate TBM from viral meningitis, bacterial meningitis, and meningitis-negative groups, respectively. Pathway analysis indicated that these metabolites were mainly involved in carbohydrate and amino acid metabolism, and over-representation analysis indicated that some of these pathways were over-represented.

CONCLUSIONS

The metabolites identified have the potential to serve as biomarkers for TBM diagnosis, and carbohydrate and amino acid metabolism are perturbed in the CSF of patents with TBM. Metabolomics is a valuable approach for screening TBM biomarkers. With further investigation, the metabolites identified in this study could aid in TBM diagnosis.

Prostate Cancer Energetics and Biosynthesis

Cancers must alter their metabolism to satisfy the increased demand for energy and to produce building blocks that are required to create a rapidly growing tumor. Further, for cancer cells to thrive, they must also adapt to an often changing tumor microenvironment, which can present new metabolic challenges (ex. hypoxia) that are unfavorable for most other cells. As such, altered metabolism is now considered an emerging hallmark of cancer. Like many other malignancies, the metabolism of prostate cancer is considerably different compared to matched benign tissue. However, prostate cancers exhibit distinct metabolic characteristics that set them apart from many other tumor types. In this chapter, we will describe the known alterations in prostate cancer metabolism that occur during initial tumorigenesis and throughout disease progression. In addition, we will highlight upstream regulators that control these metabolic changes. Finally, we will discuss how this new knowledge is being leveraged to improve patient care through the development of novel biomarkers and metabolically targeted therapies.

Differences in Urinary Amino Acid Patterns in Individuals with Different Types of Urological Tumor Urinary Amino Acid Patterns as Markers of Urological Tumors

BACKGROUND

Insufficient specificity and invasiveness of currently used diagnostic methods raises the need for new markers of urological tumors. The aim of this study was to find a link between the urinary excretion of amino acids and the presence of urological tumors.

MATERIALS AND METHODS

Using ion-exchange chromatography, we tested urine samples of patients with prostate cancer (n=30), urinary bladder cancer (n=28), renal cell carcinoma (n=16) and healthy volunteers (control group; n=21).

RESULTS

In each category, we found a group of amino acids which differed in concentration compared to the control group. These differences were most significant in sarcosine in patients with prostate cancer; leucine, phenylalanine and arginine in those with bladder cancer; and sarcosine, glutamic acid, glycine, tyrosine and arginine in the those with renal cell carcinoma.

CONCLUSION

Results of our research imply a possible connection between the occurrence of specific types of amino acids in the urine and the presence of urological tumors.

Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer

Prostate cancer (PCa) is the second most common male cancer worldwide and the fifth leading cause of death from cancer in men. Early detection and risk stratification is the most effective way to improve the survival of PCa patients. Current PCa biomarkers lack sufficient sensitivity and specificity to cancer. Metabolite biomarkers are evolving as a new diagnostic tool. This review is aimed to evaluate the potential of metabolite biomarkers for early detection, risk assessment, and monitoring of PCa. Of the 154 identified publications, 27 and 38 were original papers on urine and serum metabolomics, respectively. Nuclear magnetic resonance (NMR) is a promising method for measuring concentrations of metabolites in complex samples with good reproducibility, high sensitivity, and simple sample processing. Especially urine-based NMR metabolomics has the potential to be a cost-efficient method for the early detection of PCa, risk stratification, and monitoring treatment efficacy.

Metabolomics Applications in Precision Medicine: An Oncological Perspective

Nowadays, cancer therapy remains limited by the conventional one-size-fits-all approach. In this context, treatment decisions are based on the clinical stage of disease but fail to ascertain the individual´s underlying biology and its role in driving malignancy. The identification of better therapies for cancer treatment is thus limited by the lack of sufficient data regarding the characterization of specific biochemical signatures associated with each particular cancer patient or group of patients. Metabolomics approaches promise a better understanding of cancer, a disease characterized by significant alterations in bioenergetic metabolism, by identifying changes in the pattern of metabolite expression in addition to changes in the concentration of individual metabolites as well as alterations in biochemical pathways. These approaches hold the potential of identifying novel biomarkers with different clinical applications, including the development of more specific diagnostic methods based on the characterization of metabolic subtypes, the monitoring of currently used cancer therapeutics to evaluate the response and the prognostic outcome with a given therapy, and the evaluation of the mechanisms involved in disease relapse and drug resistance. This review discusses metabolomics applications in different oncological processes underlining the potential of this omics approach to further advance the implementation of precision medicine in the oncology area.

HIF-1α inhibition by diethylstilbestrol and its polyacetal conjugate in hypoxic prostate tumour cells: insights from NMR metabolomics

In this study, we have employed ¹H NMR metabolomics to assess the metabolic responses of PC3 prostate tumour cells to hypoxia and to pharmacological HIF-1α inhibition by DES or its polyacetal conjugate tert-DES. Oxygen deprivation prompted a number of changes in intracellular composition and metabolic activity, mainly reflecting upregulated glycolysis, amino acid catabolism and other compensatory mechanisms used by hypoxic cells to deal with oxidative imbalance and energy deficit. Cell treatment with a non-cytotoxic concentration of DES, under hypoxia, triggered significant changes in 17 metabolites. Among these, lactate, phosphocreatine and reduced glutathione, whose levels showed opposite variations in hypoxic and drug-treated cells, emerged as possible markers of DES-induced HIF-1α inhibition. Furthermore, the free drug had a much higher impact on the cellular metabolome than tert-DES, particularly concerning polyamine and pyrimidine biosynthetic pathways, known to be tightly involved in cell proliferation and growth. This is likely due to the different cell pharmacokinetics observed between free and conjugated DES. Overall, this study has revealed a number of unanticipated metabolic changes that inform on DES and tert-DES direct cellular effects, providing further insight into their mode of action at the biochemical level.

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia

INTRODUCTION

Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.

OBJECTIVES

In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.

METHODS

Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1H nuclear magnetic resonance (1H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.

RESULTS

The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.

CONCLUSION

PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

Cerebrospinal fluid metabolomic profiling in tuberculous and viral meningitis: Screening potential markers for differential diagnosis

BACKGROUND

Tuberculous meningitis (TBM) is the most severe and frequent form of central nervous system tuberculosis. The current lack of efficient diagnostic tests makes it difficult to differentiate TBM from other common types of meningitis, especially viral meningitis (VM). Metabolomics is an important tool to identify disease-specific biomarkers. However, little metabolomic information is available on adult TBM.

METHODS

We used ¹H nuclear magnetic resonance-based metabolomics to investigate the metabolic features of the CSF from 18 TBM and 20 VM patients. Principal component analysis and orthogonal signal correction-partial least squares-discriminant analysis (OSC-PLS-DA) were applied to analyze profiling data. Metabolites were identified using the Human Metabolome Database and pathway analysis was performed with MetaboAnalyst 3.0.

RESULTS

The OSC-PLS-DA model could distinguish TBM from VM with high reliability. A total of 25 key metabolites that contributed to their discrimination were identified, including some, such as betaine and cyclohexane, rarely reported before in TBM. Pathway analysis indicated that amino acid and energy metabolism was significantly different in the CSF of TBM compared with VM.

CONCLUSIONS

Twenty-five key metabolites identified in our study may be potential biomarkers for TBM differential diagnosis and are worthy of further investigation.

Metabonomic analysis of metastatic lung tissue in breast cancer mice by an integrated NMR-based metabonomics approach

This study identified the common potential biomarkers for early lung metastasis of breast cancer in two models.

Amino Acid Profiles of Serum and Urine in Search for Prostate Cancer Biomarkers: a Pilot Study

There is a great interest in searching for diagnostic biomarkers in prostate cancer patients. The aim of the pilot study was to evaluate free amino acid profiles in their serum and urine. The presented paper shows the first comprehensive analysis of a wide panel of amino acids in two different physiological fluids obtained from the same groups of prostate cancer patients (n = 49) and healthy men (n = 40). The potential of free amino acids, both proteinogenic and non-proteinogenic, as prostate cancer biomarkers and their utility in classification of study participants have been assessed. Several metabolites, which deserve special attention in the further metabolomic investigations on searching for prostate cancer markers, were indicated. Moreover, free amino acid profiles enabled to classify samples to one of the studied groups with high sensitivity and specificity. The presented research provides a strong evidence that ethanolamine, arginine and branched-chain amino acids metabolic pathways can be a valuable source of markers for prostate cancer. The altered concentrations of the above-mentioned metabolites suggest their role in pathogenesis of prostate cancer and they should be further evaluated as clinically useful markers of prostate cancer.

Biomarkers for prostate cancer: present challenges and future opportunities

Prostate cancer (PCa) has variable biological potential with multiple treatment options. A more personalized approach, therefore, is needed to better define men at higher risk of developing PCa, discriminate indolent from aggressive disease and improve risk stratification after treatment by predicting the likelihood of progression. This may improve clinical decision-making regarding management, improve selection for active surveillance protocols and minimize morbidity from treatment. Discovery of new biomarkers associated with prostate carcinogenesis present an opportunity to provide patients with novel genetic signatures to better understand their risk of developing PCa and help forecast their clinical course. In this review, we examine the current literature evaluating biomarkers in PCa. We also address current limitations and present several ideas for future studies.

Non-Coding RNAs in Castration-Resistant Prostate Cancer: Regulation of Androgen Receptor Signaling and Cancer Metabolism

Hormone-refractory prostate cancer frequently relapses from therapy and inevitably progresses to a bone-metastatic status with no cure. Understanding of the molecular mechanisms conferring resistance to androgen deprivation therapy has the potential to lead to the discovery of novel therapeutic targets for type of prostate cancer with poor prognosis. Progression to castration-resistant prostate cancer (CRPC) is characterized by aberrant androgen receptor (AR) expression and persistent AR signaling activity. Alterations in metabolic activity regulated by oncogenic pathways, such as c-Myc, were found to promote prostate cancer growth during the development of CRPC. Non-coding RNAs represent a diverse family of regulatory transcripts that drive tumorigenesis of prostate cancer and various other cancers by their hyperactivity or diminished function. A number of studies have examined differentially expressed non-coding RNAs in each stage of prostate cancer. Herein, we highlight the emerging impacts of microRNAs and long non-coding RNAs linked to reactivation of the AR signaling axis and reprogramming of the cellular metabolism in prostate cancer. The translational implications of non-coding RNA research for developing new biomarkers and therapeutic strategies for CRPC are also discussed.