Response of Degarelix treatment in human prostate cancer monitored by HR-MAS 1H NMR spectroscopy

Metabolic analysis using HR-MAS in prostate tissue for prostate cancer diagnosis

INTRODUCTION

In this study we used nuclear magnetic resonance spectroscopy in prostate tissue to provide new data on potential biomarkers of prostate cancer in patients eligible for prostate biopsy.

MATERIAL AND METHODS

Core needle prostate tissue samples were obtained. After acquiring all the spectra using a Bruker Avance III DRX 600 spectrometer, tissue samples were subjected to routine histology to confirm presence or absence of prostate cancer. Univariate and multivariate analyses with metabolic and clinical variables were performed to predict the occurrence of prostate cancer.

RESULTS

A total of 201 patients, were included in the study. Of all cores subjected to high-resolution magic angle spinning (HR-MAS) followed by standard histological study, 56 (27.8%) tested positive for carcinoma. According to HR-MAS probe analysis, metabolic pathways such as glycolysis, the Krebs cycle, and the metabolism of different amino acids were associated with presence of prostate cancer. Metabolites detected in tissue such as citrate or glycerol-3-phosphocholine, together with prostate volume and suspicious rectal examination, formed a predictive model for prostate cancer in tissue with an area under the curve of 0.87, a specificity of 94%, a positive predictive value of 80% and a negative predictive value of 84%.

CONCLUSIONS

Metabolomics using HR-MAS analysis can uncover a specific metabolic fingerprint of prostate cancer in prostate tissue, using a tissue core obtained by transrectal biopsy. This specific fingerprint is based on levels of citrate, glycerol-3-phosphocholine, glycine, carnitine, and 0-phosphocholine. Several clinical variables, such as suspicious digital rectal examination and prostate volume, combined with these metabolites, form a predictive model to diagnose prostate cancer that has shown encouraging results.

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.

Metabolomic profiles of intact tissues reflect clinically relevant prostate cancer subtypes

BACKGROUND

Prostate cancer (PC) is a heterogenous multifocal disease ranging from indolent to lethal states. For improved treatment-stratification, reliable approaches are needed to faithfully differentiate between high- and low-risk tumors and to predict therapy response at diagnosis.

METHODS

A metabolomic approach based on high resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) analysis was applied on intact biopsies samples (n = 111) obtained from patients (n = 31) treated by prostatectomy, and combined with advanced multi- and univariate statistical analysis methods to identify metabolomic profiles reflecting tumor differentiation (Gleason scores and the International Society of Urological Pathology (ISUP) grade) and subtypes based on tumor immunoreactivity for Ki67 (cell proliferation) and prostate specific antigen (PSA, marker for androgen receptor activity).

RESULTS

Validated metabolic profiles were obtained that clearly distinguished cancer tissues from benign prostate tissues. Subsequently, metabolic signatures were identified that further divided cancer tissues into two clinically relevant groups, namely ISUP Grade 2 (n = 29) and ISUP Grade 3 (n = 17) tumors. Furthermore, metabolic profiles associated with different tumor subtypes were identified. Tumors with low Ki67 and high PSA (subtype A, n = 21) displayed metabolite patterns significantly different from tumors with high Ki67 and low PSA (subtype B, n = 28). In total, seven metabolites; choline, peak for combined phosphocholine/glycerophosphocholine metabolites (PC + GPC), glycine, creatine, combined signal of glutamate/glutamine (Glx), taurine and lactate, showed significant alterations between PC subtypes A and B.

CONCLUSIONS

The metabolic profiles of intact biopsies obtained by our non-invasive HR MAS NMR approach together with advanced chemometric tools reliably identified PC and specifically differentiated highly aggressive tumors from less aggressive ones. Thus, this approach has proven the potential of exploiting cancer-specific metabolites in clinical settings for obtaining personalized treatment strategies in PC.

Prediction of recurrence from metabolites and expression of TOP2A and EZH2 in prostate cancer patients treated with radiotherapy

BACKGROUND

The dual upregulation of TOP2A and EZH2 gene expression has been proposed as a biomarker for recurrence in prostate cancer patients to be treated with radical prostatectomy. A low tissue level of the metabolite citrate has additionally been connected to aggressive disease and recurrence in this patient group. However, for radiotherapy prostate cancer patients, few prognostic biomarkers have been suggested. The main aim of this study was to use an integrated tissue analysis to evaluate metabolites and expression of TOP2A and EZH2 as predictors for recurrence among radiotherapy patients.

METHODS

From 90 prostate cancer patients (56 received neoadjuvant hormonal treatment), 172 transrectal ultrasound-guided (TRUS) biopsies were collected prior to radiotherapy. Metabolic profiles were acquired from fresh frozen TRUS biopsies using high resolution-magic angle spinning MRS. Histopathology and immunohistochemistry staining for TOP2A and EZH2 were performed on TRUS biopsies containing cancer cells (n = 65) from 46 patients, where 24 of these patients (n = 31 samples) received hormonal treatment. Eleven radical prostatectomy cohorts of a total of 2059 patients were used for validation in a meta-analysis.

RESULTS

Among radiotherapy patients with up to 11 years of follow-up, a low level of citrate was found to predict recurrence, p = 0.001 (C-index = 0.74). Citrate had a higher predictive ability compared with individual clinical variables, highlighting its strength as a potential biomarker for recurrence. The dual upregulation of TOP2A and EZH2 was suggested as a biomarker for recurrence, particularly for patients not receiving neoadjuvant hormonal treatment, p = 0.001 (C-index = 0.84). While citrate was a statistically significant biomarker independent of hormonal treatment status, the current study indicated a potential of glutamine, glutamate and choline as biomarkers for recurrence among patients receiving neoadjuvant hormonal treatment, and glucose among patients not receiving neoadjuvant hormonal treatment.

CONCLUSION

Using an integrated approach, our study shows the potential of citrate and the dual upregulation of TOP2A and EZH2 as biomarkers for recurrence among radiotherapy patients.

Cancer insights from magnetic resonance spectroscopy of cells and excised tumors

Multinuclear ex vivo magnetic resonance spectroscopy (MRS) of cancer cells, xenografts, human cancer tissue, and biofluids is a rapidly expanding field that is providing unique insights into cancer. Starting from the 1970s, the field has continued to evolve as a stand-alone technology or as a complement to in vivo MRS to characterize the metabolome of cancer cells, cancer-associated stromal cells, immune cells, tumors, biofluids and, more recently, changes in the metabolome of organs induced by cancers. Here, we review some of the insights into cancer obtained with ex vivo MRS and provide a perspective of future directions. Ex vivo MRS of cells and tumors provides opportunities to understand the role of metabolism in cancer immune surveillance and immunotherapy. With advances in computational capabilities, the integration of artificial intelligence to identify differences in multinuclear spectral patterns, especially in easily accessible biofluids, is providing exciting advances in detection and monitoring response to treatment. Metabolotheranostics to target cancers and to normalize metabolic changes in organs induced by cancers to prevent cancer-induced morbidity are other areas of future development.

Role of asparagine biosynthesis pathway in Siniperca chuatsi rhabdovirus proliferation

Viruses are non-living organisms that rely on host cellular metabolism to complete their life cycle. Siniperca chuatsi rhabdovirus (SCRV) has caused huge economic losses to the Chinese perch (Siniperca chuatsi) industry worldwide. SCRV replication is dependent on the cellular glutamine metabolism, while aspartate metabolism plays an important role in viral proliferation in glutamine deficiency. Herein, we investigated roles of asparagine metabolism in SCRV proliferation. Results showed that SCRV infection upregulated the expression of key enzymes in the aspartate metabolic pathway in CPB cells. And the key enzymes of malate-aspartic acid shuttle pathway upregulated during the virus invasion phase, and key enzymes of the asparagine biosynthesis pathway upregulated during the viral replication and release phase. When asparagine was added to the depleted medium, the SCRV copy number restored to 90% of those in replete medium, showing that asparagine and glutamine completely rescue the replication of SCRV. Moreover, inhibition of the aspartate- malate shuttle pathway and knockdown of the expression of key enzymes in the asparagine biosynthesis pathway significantly reduced SCRV production, indicating that the aspartic acid metabolic pathway was required to the replication and proliferation of SCRV. Above results provided references for elucidating pathogenic mechanism of SCRV by regulation of aspartate metabolism.

Targeting lactate-related cell cycle activities for cancer therapy

Lactate has long been considered as a metabolic by-product of aerobic glycolysis for cancer. However, more and more studies have shown that lactate can regulate cancer progression via multiple mechanisms such as cell cycle regulation, immune suppression, energy metabolism and so on. A recent discovery of lactylation attracted a lot of attention and is already a hot topic in the cancer field. In this review, we summarized the latest functions of lactate and its underlying mechanisms in cancer. We also included our analysis of protein lactylation in different rat organs and compared them with other published lactylation data. The unresolved challenges in this field were discussed, and the potential application of these new discoveries of lactate-related cell cycle activities for cancer target therapy was speculated.

High resolution magic angle spinning MRS in prostate cancer

INTRODUCTION

Prostate cancer (PCa) is one of the leading causes of death among men worldwide. The current methods utilized to screen for prostate cancer may not have sufficient sensitivity in distinguishing aggressive from indolent diseases, which affect the quality of life of patients in the short and long term. The overdiagnosis of cases and overtreatment are prevalent due to the heterogeneity of the disease in terms of latent and progressive variants, as well as in the tissue types present in biopsy samples.

METHODS

The purpose of this review is to discuss the potential clinical benefits of incorporating high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) modalities to overcome the current challenges in the diagnosis, prognostication, and monitoring of PCa.

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.

Pharmacometabolomics Applied to Personalized Medicine in Urological Cancers

Prostate cancer (PCa), bladder cancer (BCa), and renal cell carcinoma (RCC) are the most common urological cancers, and their incidence has been rising over time. Surgery is the standard treatment for these cancers, but this procedure is only effective when the disease is localized. For metastatic disease, PCa is typically treated with androgen deprivation therapy, while BCa is treated with chemotherapy, and RCC is managed primarily with targeted therapies. However, response rates to these therapeutic options remain unsatisfactory due to the development of resistance and treatment-related toxicity. Thus, the discovery of biomarkers with prognostic and predictive value is needed to stratify patients into different risk groups, minimizing overtreatment and the risk of drug resistance development. Pharmacometabolomics, a branch of metabolomics, is an attractive tool to predict drug response in an individual based on its own metabolic signature, which can be collected before, during, and after drug exposure. Hence, this review focuses on the application of pharmacometabolomic approaches to identify the metabolic responses to hormone therapy, targeted therapy, immunotherapy, and chemotherapy for the most prevalent urological cancers.

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.

Pharmacometabolomics by NMR in Oncology: A Systematic Review

Pharmacometabolomics (PMx) studies aim to predict individual differences in treatment response and in the development of adverse effects associated with specific drug treatments. Overall, these studies inform us about how individuals will respond to a drug treatment based on their metabolic profiles obtained before, during, or after the therapeutic intervention. In the era of precision medicine, metabolic profiles hold great potential to guide patient selection and stratification in clinical trials, with a focus on improving drug efficacy and safety. Metabolomics is closely related to the phenotype as alterations in metabolism reflect changes in the preceding cascade of genomics, transcriptomics, and proteomics changes, thus providing a significant advance over other omics approaches. Nuclear Magnetic Resonance (NMR) is one of the most widely used analytical platforms in metabolomics studies. In fact, since the introduction of PMx studies in 2006, the number of NMR-based PMx studies has been continuously growing and has provided novel insights into the specific metabolic changes associated with different mechanisms of action and/or toxic effects. This review presents an up-to-date summary of NMR-based PMx studies performed over the last 10 years. Our main objective is to discuss the experimental approaches used for the characterization of the metabolic changes associated with specific therapeutic interventions, the most relevant results obtained so far, and some of the remaining challenges in this area.

Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics

Prostate cancer (PCa) is the second most diagnosed cancer in men worldwide. For its screening, serum prostate specific antigen (PSA) test has been largely performed over the past decade, despite its lack of accuracy and inability to distinguish indolent from aggressive disease. Metabolomics has been widely applied in cancer biomarker discovery due to the well-known metabolic reprogramming characteristic of cancer cells. Most of the metabolomic studies have reported alterations in urine of PCa patients due its noninvasive collection, but the analysis of prostate tissue metabolome is an ideal approach to disclose specific modifications in PCa development. This review aims to summarize and discuss the most recent findings from tissue and urine metabolomic studies applied to PCa biomarker discovery. Eighteen metabolites were found consistently altered in PCa tissue among different studies, including alanine, arginine, uracil, glutamate, fumarate, and citrate. Urine metabolomic studies also showed consistency in the dysregulation of 15 metabolites and, interestingly, alterations in the levels of valine, taurine, leucine and citrate were found in common between urine and tissue studies. These findings unveil that the impact of PCa development in human metabolome may offer a promising strategy to find novel biomarkers for PCa diagnosis.

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.

ApcMin/+ tumours and normal mouse small intestines show linear metabolite concentration and DNA cytosine hydroxymethylation gradients from pylorus to colon

Topographical variations of metabolite concentrations have been reported in the duodenum, jejunum and ileum of the small intestine, and in human intestinal tumours from those regions, but there are no published metabolite concentrations measurements correlated with linear position in the mouse small intestine or intestinal tumours. Since DNA methylation dynamics are influenced by metabolite concentrations, they too could show linear anatomical variation. We measured metabolites by HR-MAS ¹H NMR spectroscopy and DNA cytosine modifications by LC/MS, in normal small intestines of C57BL/6J wild-type mice, and in normal and tumour samples from Apc^Min/+ mice. Wild-type mouse intestines showed approximately linear, negative concentration gradations from the pylorus (i.e. the junction with the stomach) of alanine, choline compounds, creatine, leucine and valine. Apc^Min/+ mouse tumours showed negative choline and valine gradients, but a positive glycine gradient. 5-Hydroxymethylcytosine showed a positive gradient in the tumours. The linear gradients we found along the length of the mouse small intestine and in tumours contrast with previous reports of discrete concentration changes in the duodenum, jejunum and ileum. To our knowledge, this is also the first report of a systematic measurement of global levels of DNA cytosine modification in wild-type and Apc^Min/+ mouse small intestine.

Cancer metabolism in a snapshot: MRS(I)

The contribution of MRS(I) to the in vivo evaluation of cancer-metabolism-derived metrics, mostly since 2016, is reviewed here. Increased carbon consumption by tumour cells, which are highly glycolytic, is now being sampled by ¹³ C magnetic resonance spectroscopic imaging (MRSI) following the injection of hyperpolarized [1-¹³ C] pyruvate (Pyr). Hot-spots of, mostly, increased lactate dehydrogenase activity or flow between Pyr and lactate (Lac) have been seen with cancer progression in prostate (preclinical and in humans), brain and pancreas (both preclinical) tumours. Therapy response is usually signalled by decreased Lac/Pyr ¹³ C-labelled ratio with respect to untreated or non-responding tumour. For therapeutic agents inducing tumour hypoxia, the ¹³ C-labelled Lac/bicarbonate ratio may be a better metric than the Lac/Pyr ratio. ³¹ P MRSI may sample intracellular pH changes from brain tumours (acidification upon antiangiogenic treatment, basification at fast proliferation and relapse). The steady state tumour metabolome pattern is still in use for cancer evaluation. Metrics used for this range from quantification of single oncometabolites (such as 2-hydroxyglutarate in mutant IDH1 glial brain tumours) to selected metabolite ratios (such as total choline to N-acetylaspartate (plain ratio or CNI index)) or the whole ¹ H MRSI(I) pattern through pattern recognition analysis. These approaches have been applied to address different questions such as tumour subtype definition, following/predicting the response to therapy or defining better resection or radiosurgery limits.

Metabolomic prostate cancer fields in HRMAS MRS-profiled histologically benign tissue vary with cancer status and distance from cancer

In this article, we review the state of the field of high resolution magic angle spinning MRS (HRMAS MRS)-based cancer metabolomics since its beginning in 2004; discuss the concept of cancer metabolomic fields, where metabolomic profiles measured from histologically benign tissues reflect patient cancer status; and report our HRMAS MRS metabolomic results, which characterize metabolomic fields in prostatectomy-removed cancerous prostates. Three-dimensional mapping of cancer lesions throughout each prostate enabled multiple benign tissue samples per organ to be classified based on distance from and extent of the closest cancer lesion as well as the Gleason score (GS) of the entire prostate. Cross-validated partial least squares-discriminant analysis separations were achieved between cancer and benign tissue, and between cancer tissue from prostates with high (≥4 + 3) and low (≤3 + 4) GS. Metabolomic field effects enabled histologically benign tissue adjacent to cancer to distinguish the GS and extent of the cancer lesion itself. Benign samples close to either low GS cancer or extensive cancer lesions could be distinguished from those far from cancer. Furthermore, a successfully cross-validated multivariate model for three benign tissue groups with varying distances from cancer lesions within one prostate indicates the scale of prostate cancer metabolomic fields. While these findings could, at present, be potentially useful in the prostate cancer clinic for analysis of biopsy or surgical specimens to complement current diagnostics, the confirmation of metabolomic fields should encourage further examination of cancer fields and can also enhance understanding of the metabolomic characteristics of cancer in myriad organ systems. Our results together with the success of HRMAS MRS-based cancer metabolomics presented in our literature review demonstrate the potential of cancer metabolomics to provide supplementary information for cancer diagnosis, staging, and patient prognostication.

Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer

Activated choline metabolism is a hallmark of carcinogenesis and tumor progression, which leads to elevated levels of phosphocholine and glycerophosphocholine in all types of cancer tested so far. Magnetic resonance spectroscopy applications have played a key role in detecting these elevated choline phospholipid metabolites. To date, the majority of cancer-related studies have focused on phosphocholine and the Kennedy pathway, which constitutes the biosynthesis pathway for membrane phosphatidylcholine. Fewer and more recent studies have reported on the importance of glycerophosphocholine in cancer. In this review article, we summarize the recent literature on glycerophosphocholine metabolism with respect to its cancer biology and its detection by magnetic resonance spectroscopy applications.

NMR Spectroscopy for Metabolomics Research

Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

Prostate cancer-specific hallmarks of amino acids metabolism: Towards a paradigm of precision medicine

So far multiple differences in prostate cancer-specific amino acids metabolism have been discovered. Moreover, attempts to utilize these alterations for prostate cancer diagnosis and treatment have been made. The prostate cancer metabolism and biosynthesis of amino acids are particularly focused on anaplerosis more than on energy production. Other crucial requirements on amino acids pool come from the serine, one‑carbon cycle, glycine synthesis pathway and folate metabolism forming major sources of interproducts for synthesis of nucleobases necessary for rapidly proliferating cells. Considering the lack of some amino acids biosynthetic pathways and/or their extraordinary importance for prostate cancer cells, there is a widespread potential for targeted therapeutic applications with no effect on non-malignant cells. This review summarizes the up-to-date knowledge of the importance of amino acids for prostate cancer pathogenesis with a special emphasis on potential applications of metabolic variabilities in the new oncologic paradigm of precision medicine.

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.

Discrimination between the human prostate normal and cancer cell exometabolome by GC-MS

Serum prostate-specific antigen (PSA) is currently the most used biomarker in clinical practice for prostate cancer (PCa) detection. However, this biomarker has several drawbacks. In this work, an untargeted gas chromatography-mass spectrometry (GC-MS)-based metabolomic profiling of PCa cells was performed to prove the concept that metabolic alterations might differentiate PCa cell lines from normal prostate cell line. For that, we assessed the differences in volatile organic compounds (VOCs) profile in the extracellular medium (exometabolome) of four PCa cell lines and one normal prostate cell line at two pH values (pH 2 and 7) by GC-MS. Multivariate analysis revealed a panel of volatile metabolites that discriminated cancerous from normal prostate cells. The most altered metabolites included ketones, aldehydes and organic acids. Among these, we highlight pentadecane-2-one and decanoic acid, which were significantly increased in PCa compared to normal cells, and cyclohexanone, 4-methylheptan-2-one, 2-methylpentane-1,3-diol, 4-methylbenzaldehyde, 1-(3,5-dimethylfuran-2-yl)ethanone, methyl benzoate and nonanoic acid, which were significantly decreased in PCa cells. The PCa volatilome was markedly influenced by the VOCs extraction pH, though the discriminant capability was similar. Overall, our data suggest that VOCs monitoring has the potential to be used as a PCa screening methodology.

Translating in vivo metabolomic analysis of succinate dehydrogenase deficient tumours into clinical utility

PURPOSE

Mutations in the mitochondrial enzyme succinate dehydrogenase (SDH) subunit genes are associated with a wide spectrum of tumours including phaeochromocytoma and paraganglioma (PPGL) 1, 2, gastrointestinal stromal tumours (GIST) 3, renal cell carcinoma (RCC) 4 and pituitary adenomas5. SDH-related tumorigenesis is believed to be secondary to accumulation of the oncometabolite succinate. Our aim was to investigate the potential clinical applications of MRI spectroscopy (1H-MRS) in a range of suspected SDH-related tumours.

PATIENTS AND METHODS

Fifteen patients were recruited to this study. Respiratory-gated single-voxel 1H-MRS was performed at 3T to quantify the content of succinate at 2.4 ppm and choline at 3.22 ppm.

RESULTS

A succinate peak was seen in six patients, all of whom had a germline SDHx mutation or loss of SDHB by immunohistochemistry. A succinate peak was also detected in two patients with a metastatic wild-type GIST (wtGIST) and no detectable germline SDHx mutation but a somatic epimutation in SDHC. Three patients without a tumour succinate peak retained SDHB expression, consistent with SDH functionality. In six cases with a borderline or absent peak, technical difficulties such as motion artefact rendered 1H-MRS difficult to interpret. Sequential imaging in a patient with a metastatic abdominal paraganglioma demonstrated loss of the succinate peak after four cycles of [177Lu]-DOTATATE, with a corresponding biochemical response in normetanephrine.

CONCLUSIONS

This study has demonstrated the translation into clinical practice of in vivo metabolomic analysis using 1H-MRS in patients with SDH-deficient tumours. Potential applications include non-invasive diagnosis and disease stratification, as well as monitoring of tumour response to targeted treatments.

Profiling Prostate Cancer Therapeutic Resistance

The major challenge in the treatment of patients with advanced lethal prostate cancer is therapeutic resistance to androgen-deprivation therapy (ADT) and chemotherapy. Overriding this resistance requires understanding of the driving mechanisms of the tumor microenvironment, not just the androgen receptor (AR)-signaling cascade, that facilitate therapeutic resistance in order to identify new drug targets. The tumor microenvironment enables key signaling pathways promoting cancer cell survival and invasion via resistance to anoikis. In particular, the process of epithelial-mesenchymal-transition (EMT), directed by transforming growth factor-β (TGF-β), confers stem cell properties and acquisition of a migratory and invasive phenotype via resistance to anoikis. Our lead agent DZ-50 may have a potentially high efficacy in advanced metastatic castration resistant prostate cancer (mCRPC) by eliciting an anoikis-driven therapeutic response. The plasticity of differentiated prostate tumor gland epithelium allows cells to de-differentiate into mesenchymal cells via EMT and re-differentiate via reversal to mesenchymal epithelial transition (MET) during tumor progression. A characteristic feature of EMT landscape is loss of E-cadherin, causing adherens junction breakdown, which circumvents anoikis, promoting metastasis and chemoresistance. The targetable interactions between androgens/AR and TGF-β signaling are being pursued towards optimized therapeutic regimens for the treatment of mCRPC. In this review, we discuss the recent evidence on targeting the EMT-MET dynamic interconversions to overcome therapeutic resistance in patients with recurrent therapeutically resistant prostate cancer. Exploitation of the phenotypic landscape and metabolic changes that characterize the prostate tumor microenvironment in advanced prostate cancer and consequential impact in conferring treatment resistance are also considered in the context of biomarker discovery.

The crucial role of multiomic approach in cancer research and clinically relevant outcomes

Cancer with heavily economic and social burden is the hot point in the field of medical research. Some remarkable achievements have been made; however, the exact mechanisms of tumor initiation and development remain unclear. Cancer is a complex, whole-body disease that involves multiple abnormalities in the levels of DNA, RNA, protein, metabolite and medical imaging. Biological omics including genomics, transcriptomics, proteomics, metabolomics and radiomics aims to systematically understand carcinogenesis in different biological levels, which is driving the shift of cancer research paradigm from single parameter model to multi-parameter systematical model. The rapid development of various omics technologies is driving one to conveniently get multi-omics data, which accelerates predictive, preventive and personalized medicine (PPPM) practice allowing prediction of response with substantially increased accuracy, stratification of particular patients and eventual personalization of medicine. This review article describes the methodology, advances, and clinically relevant outcomes of different "omics" technologies in cancer research, and especially emphasizes the importance and scientific merit of integrating multi-omics in cancer research and clinically relevant outcomes.

Applications of high-resolution magic angle spinning MRS in biomedical studies II-Human diseases

High-resolution magic angle spinning (HRMAS) MRS is a powerful method for gaining insight into the physiological and pathological processes of cellular metabolism. Given its ability to obtain high-resolution spectra of non-liquid biological samples, while preserving tissue architecture for subsequent histopathological analysis, the technique has become invaluable for biochemical and biomedical studies. Using HRMAS MRS, alterations in measured metabolites, metabolic ratios, and metabolomic profiles present the possibility to improve identification and prognostication of various diseases and decipher the metabolomic impact of drug therapies. In this review, we evaluate HRMAS MRS results on human tissue specimens from malignancies and non-localized diseases reported in the literature since the inception of the technique in 1996. We present the diverse applications of the technique in understanding pathological processes of different anatomical origins, correlations with in vivo imaging, effectiveness of therapies, and progress in the HRMAS methodology.

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

Background

Diagnosis and monitoring of localized prostate cancer requires discovery and validation of noninvasive biomarkers. Nuclear magnetic resonance (NMR)-based metabolomics of seminal plasma reportedly improves diagnostic accuracy, but requires validation in a high-risk clinical cohort.

Materials and methods

Seminal plasma samples of 151 men being investigated for prostate cancer were analyzed with ¹H-NMR spectroscopy. After adjustment for buffer (add-to-subtract) and endogenous enzyme influence on metabolites, metabolite profiling was performed with multivariate statistical analysis (principal components analysis, partial least squares) and targeted quantitation.

Results

Seminal plasma metabolites best predicted low- and intermediate-risk prostate cancer with differences observed between these groups and benign samples. Lipids/lipoproteins dominated spectra of high grade samples with less metabolite contributions. Overall prostate cancer prediction using previously described metabolites was not validated.

Conclusion

Metabolomics of seminal plasma in vitro may assist urologists with diagnosis and monitoring of either low or intermediate grade prostate cancer. Less clinical benefit may be observed for high-risk patients. Further investigation in active surveillance cohorts, and/or in combination with in vivo magnetic resonance spectroscopic imaging may further optimize localized prostate cancer outcomes.