Seminal plasma enables selection and monitoring of active surveillance candidates using nuclear magnetic resonance-based metabolomics: A preliminary investigation

1H-NMR-based urine metabolomics of prostate cancer and benign prostatic hyperplasia

Background

Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) are prevalent conditions affecting a significant portion of the male population, particularly with advancing age. Traditional diagnostic methods, such as digital rectal examination (DRE) and prostate-specific antigen (PSA) tests, have limitations in specificity and sensitivity, leading to potential overdiagnosis and unnecessary biopsies.

Significance

This study explores the effectiveness of 1H NMR urine metabolomics in distinguishing PCa from BPH and in differentiating various PCa grades, presenting a non-invasive diagnostic alternative with the potential to enhance early detection and patient-specific treatment strategies.

Results

The study demonstrated the capability of 1H NMR urine metabolomics in detecting distinct metabolic profiles between PCa and BPH, as well as among different Gleason grade groups. Notably, this method surpassed the PSA test in distinguishing PCa from BPH. Untargeted metabolomics analysis also revealed several metabolites with varying relative concentrations between PCa and BPH cases, suggesting potential biomarkers for these conditions.

Prostate cancer in omics era

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer.

The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer

Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.

Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches

Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In this context, a deeper understanding of metabolic reprogramming, an emerging hallmark of cancer, could provide novel opportunities for cancer diagnosis, prognosis, and treatment. In this setting, multi-omics data integration approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, and metabolomics, could offer unprecedented opportunities for uncovering the molecular changes underlying metabolic rewiring in complex diseases, such as PCa. Recent studies, focused on the integrated analysis of multi-omics data derived from PCa patients, have in fact revealed new insights into specific metabolic reprogramming events and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients. This review aims to provide an up-to-date summary of multi-omics studies focused on the characterization of the metabolomic phenotype of PCa, as well as an in-depth analysis of the correlation between changes identified in the multi-omics studies and the metabolic profile of PCa tumors.

Potential of nuclear magnetic resonance metabolomics in the study of prostate cancer

Nuclear magnetic resonance (NMR) metabolomics is a powerful analytical technique and a tool which has unique characteristics and capabilities for the evaluation of a number of biochemicals/metabolites of cancer and other disease processes that are present in biofluids (urine and blood) and tissues. The potential of NMR metabolomics in prostate cancer (PCa) has been explored by researchers and its usefulness has been documented. A large number of metabolites such as citrate, choline, and sarcosine were detected by NMR metabolomics from biofluids and tissues related to PCa and their levels were compared with controls and benign prostatic hyperplasia. The changes in the levels of these metabolites aid in the diagnosis and help to understand the dysregulated metabolic pathways in PCa. We review recent studies on in vitro and ex vivo NMR spectroscopy-based PCa metabolomics and its possible role as a diagnostic tool.

Seminal plasma metabolomics reveals lysine and serine dysregulation as unique features distinguishing between prostate cancer tumors of Gleason grades 6 and 7

BACKGROUND

Prostate cancer (PCa) is a metabolic disease. Most men are diagnosed with low grade indolent disease and differentiating these men from those who have life threatening cancer is a challenging but important clinical dilemma. There are currently limited biomarkers that can distinguish between the indolent Gleason grade 6 and higher-grade disease. Moreover, some individuals initially diagnosed with low grade disease progress to higher grade disease. Currently prostate biopsies are the only reliable methods of stratifying risk, but biopsies can cause significant morbidity, sample only a small portion of the gland and are costly. Therefore, biomarkers distinguishing between indolent and aggressive patterns of PCa are urgently required to minimize biopsy-associated morbidity, prevent over-treatment of indolent PCa and to better stratify patients for appropriate treatment.

METHODS

Seminal fluid samples were collected from normal individuals (n = 13) Before infertility treatment and histologically confirmed PCa patients (n = 51). ¹ H Nuclear magnetic resonance spectroscopy and orthogonal partial least square discriminant analysis were used to compare the populations.

RESULTS

Alterations in amino acids levels, specifically lysine and serine and changes in glycolytic intermediates were the most significant metabolic features associated with differences between healthy controls and PCa and between Gleason grade 6 (GS6) and Gleason grade 7 (GS7) samples. Orthogonal partial least square plots discriminated healthy controls from PCa samples (R ²  = 0.54, Q ²  = 0.31; area under the receiver operating characteristics curve [AUC] = 0.96), and GS6 from GS7 samples (R ²  = 0.62, Q ²  = 0.49; AUC = 0.98) based on lysine and serine content.

CONCLUSION

This study suggests that seminal plasma metabolomics profiling of seminal fluid is a promising means of differentiating indolent from aggressive disease. Particularly, lysine and serine levels may be able to differentiate GS6 from GS7 disease.

Metabolism of prostate cancer by magnetic resonance spectroscopy (MRS)

Understanding the metabolism of prostate cancer (PCa) is important for developing better diagnostic approaches and also for exploring new therapeutic targets. Magnetic resonance spectroscopy (MRS) techniques have been shown to be useful in the detection and quantification of metabolites. PCa illustrates metabolic phenotype, showing lower levels of citrate (Cit), a key metabolite of oxidative phosphorylation and alteration in several metabolic pathways to sustain tumor growth. Recently, dynamic nuclear polarization (DNP) studies have documented high rates of glycolysis (Warburg phenomenon) in PCa. High-throughput metabolic profiling strategies using MRS on variety of samples including intact tissues, biofluids like prostatic fluid, seminal fluid, blood plasma/sera, and urine have also played a vital role in understanding the abnormal metabolic activity of PCa patients. The enhanced analytical potential of these techniques in the detection and quantification of a large number of metabolites provides an in-depth understanding of metabolic rewiring associated with the tumorigenesis. Metabolomics analysis offers dual advantages of identification of diagnostic and predictive biomarkers as well as in understanding the altered metabolic pathways which can be targeted for inhibiting the cancer progression. This review briefly describes the potential applications of in vivo ¹H MRS, high-resolution magic angle spinning spectroscopy (HRMAS) and in vitro MRS methods in understanding the metabolic changes of PCa and its usefulness in the management of PCa patients.

Challenges, applications and future directions of precision medicine in prostate cancer - the role of organoids and patient-derived xenografts

OBJECTIVE

To provide a clinically relevant outline of various current precision medicine principles and available evidence on the application and potential for a precision medicine approach in prostate cancer.

METHODS

Narrative review of the current literature in the field.

CONCLUSION

Precision medicine is the concept of individualising patient management based on specific tumour characteristics and biology, rather than traditional histological subtypes. The overall aim is to personalise management to individual patients, to provide the right cancer treatment, to the right patient, at the right time. While the approach aims to improve clinical outcomes, decrease morbidity and improve survival in men with advanced prostate cancer, its clinical application is in its infancy. It does however show great promise in this and other cancers, and will continue to be an area of active research and clinical investigation.

Metabolomics Contributions to the Discovery of Prostate Cancer Biomarkers

Prostate cancer (PCa) is one of the most frequently diagnosed cancers and a leading cause of death among men worldwide. Despite extensive efforts in biomarker discovery during the last years, currently used clinical biomarkers are still lacking enough specificity and sensitivity for PCa early detection, patient prognosis, and monitoring. Therefore, more precise biomarkers are required to improve the clinical management of PCa patients. In this context, metabolomics has shown to be a promising and powerful tool to identify novel PCa biomarkers in biofluids. Thus, changes in polyamines, tricarboxylic acid (TCA) cycle, amino acids, and fatty acids metabolism have been reported in different studies analyzing PCa patients' biofluids. The review provides an up-to-date summary of the main metabolic alterations that have been described in biofluid-based studies of PCa patients, as well as a discussion regarding their potential to improve clinical PCa diagnosis and prognosis. Furthermore, a summary of the most significant findings reported in these studies and the connections and interactions between the different metabolic changes described has also been included, aiming to better describe the specific metabolic signature associated to PCa.

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

Prostate cancer (PCa) diagnosis with current biomarkers is difficult and often results in unnecessary invasive procedures as well as over-diagnosis and over-treatment, highlighting the need for novel biomarkers. The aim of this review is to provide a summary of available metabolomics PCa biomarkers, particularly for clinically significant disease. A systematic search was conducted on PubMed for publications from July 2008 to July 2018 in accordance with PRISMA guidelines to report biomarkers with respect to their application in PCa diagnosis, progression, aggressiveness, recurrence, and treatment response. The vast majority of studies report biomarkers with the ability to distinguish malignant from benign prostate tissue with a few studies investigating biomarkers associated with disease progression, treatment response or tumour recurrence. In general, these studies report high dimensional datasets and the number of analysed metabolites often significantly exceeded the number of available samples. Hence, observed multivariate differences between case and control samples in the datasets might potentially also be associated with pre-analytical, technical, statistical and confounding factors. Giving the technical and methodological hurdles, there are nevertheless a number of metabolites and pathways repeatedly reported across various technical approaches, cohorts and sample types that appear to play a predominant role in PCa tumour biology, progression and recurrence.

Metabolite Profiling of Clinical Cancer Biofluid Samples by NMR Spectroscopy

Metabolomics is a comprehensive characterization of the small polar molecules (metabolites) in different biological systems. One of the analytical platforms commonly used to study metabolic alterations in biofluid samples is proton nuclear magnetic resonance (¹H NMR) spectroscopy. NMR spectroscopy is very specific, quantitative, and highly reproducible. Moreover, sample preparation for NMR experiments is very simple and straightforward, and this gives NMR spectroscopy a distinct advantage over other metabolic profiling methods. It has already been shown that ¹H NMR-based profiling of biological fluids can be effective in differentiating benign from malignant lesions and in investigating the efficacy of specific cancer treatments. Therefore, ¹H NMR spectroscopy may become a promising tool for early noninvasive diagnosis and rapid assessment of treatment effects in cancer patients. Here, we describe a detailed protocol for ¹H NMR metabolite profiling in serum, plasma, and urine samples, including sample collection procedures, sample preparation for ¹H NMR experiments, spectral acquisition and processing, and quantitative profiling of ¹H NMR spectra. We also discuss several aspects of appropriate study design and some multivariate statistical methods that are commonly used to analyze metabolomics datasets.

NMR-based metabolomics of biofluids in cancer

This review describes the current status of NMR-based metabolomics of biofluids with respect to cancer risk assessment, detection, disease characterization, prognosis, and treatment monitoring. While the metabolism of cancer cells is altered compared with that of non-proliferating cells, the metabolome of blood and urine reflects the entire organism. We conclude that many studies show impressive associations between biofluid metabolomics and cancer progression, but translation to clinical practice is currently hindered by lack of validation, difficulties in biological interpretation, and non-standardized analytical procedures.