Metabolomic characterization of human prostate cancer bone metastases reveals increased levels of cholesterol

Preoperative plasma fatty acid metabolites inform risk of prostate cancer progression and may be used for personalized patient stratification

Background

Little is known about the relationship between the metabolite profile of plasma from pre-operative prostate cancer (PCa) patients and the risk of PCa progression. In this study we investigated the association between pre-operative plasma metabolites and risk of biochemical-, local- and metastatic-recurrence, with the aim of improving patient stratification.

Methods

We conducted a case-control study within a cohort of PCa patients recruited between 1996 and 2015. The age-matched primary cases (n = 33) were stratified in low risk, high risk without progression and high risk with progression as defined by the National Comprehensive Cancer Network. These samples were compared to metastatic (n = 9) and healthy controls (n = 10). The pre-operative plasma from primary cases and the plasma from metastatic patients and controls were assessed with untargeted metabolomics by LC-MS. The association between risk of progression and metabolite abundance was calculated using multivariate Cox proportional-hazard regression and the relationship between metabolites and outcome was calculated using median cut-off normalized values of metabolite abundance by Log-Rank test using the Kaplan Meier method.

Results

Medium-chain acylcarnitines (C6-C12) were positively associated with the risk of PSA progression (p = 0.036, median cut-off) while long-chain acylcarnitines (C14-C16) were inversely associated with local (p = 0.034) and bone progression (p = 0.0033). In primary cases, medium-chain acylcarnitines were positively associated with suberic acid, which also correlated with the risk of PSA progression (p = 0.032, Log-Rank test). In the metastatic samples, this effect was consistent for hexanoylcarnitine, L.octanoylcarnitine and decanoylcarnitine. Medium-chain acylcarnitines and suberic acid displayed the same inverse association with tryptophan, while indoleacetic acid, a breakdown product of tryptophan metabolism was strongly associated with PSA (p = 0.0081, Log-Rank test) and lymph node progression (p = 0.025, Log-Rank test). These data were consistent with the increased expression of indoleamine 2,3 dioxygenase (IDO1) in metastatic versus primary samples (p = 0.014). Finally, functional experiments revealed a synergistic effect of long chain fatty acids in combination with dihydrotestosterone administration on the transcription of androgen responsive genes.

Conclusions

This study strengthens the emerging link between fatty acid metabolism and PCa progression and suggests that measuring levels of medium- and long-chain acylcarnitines in pre-operative patient plasma may provide a basis for improving patient stratification.

Improving diagnosis of genitourinary cancers: Biomarker discovery strategies through mass spectrometry-based metabolomics

The genitourinary oncology field needs integration of results from basic science, epidemiological studies, clinical and translational research to improve the current methods for diagnosis. MS-based metabolomics can be transformative for disease diagnosis and contribute to global health parity. Metabolite panels are promising to translate metabolomic findings into the clinics, changing the current diagnosis paradigm based on single biomarker analysis. This review article describes capabilities of the MS-based oncometabolomics field for improving kidney, prostate, and bladder cancer detection, early diagnosis, risk stratification, and outcome. Published works are critically discussed based on the study design; type and number of samples analyzed; data quality assessment through quality assurance and quality control practices; data analysis workflows; confidence levels reported for identified metabolites; validation attempts; the overlap of discriminant metabolites for the different genitourinary cancers; and the translation capability of findings into clinical settings. Ongoing challenges are discussed, and future directions are delineated.

Upregulation of Scavenger Receptor B1 Is Required for Steroidogenic and Nonsteroidogenic Cholesterol Metabolism in Prostate Cancer

Aberrant cholesterol metabolism is increasingly appreciated to be essential for prostate cancer initiation and progression. Transcript expression of the high-density lipoprotein-cholesterol receptor scavenger receptor B1 (SR-B1) is elevated in primary prostate cancer. Hypothesizing that SR-B1 expression may help facilitate malignant transformation, we document increased SR-B1 protein and transcript expression in prostate cancer relative to normal prostate epithelium that persists in lethal castration-resistant prostate cancer (CRPC) metastasis. As intratumoral steroid synthesis from the precursor cholesterol can drive androgen receptor (AR) pathway activity in CRPC, we screened androgenic benign and cancer cell lines for sensitivity to SR-B1 antagonism. Benign cells were insensitive to SR-B1 antagonism, and cancer line sensitivity inversely correlated with expression levels of full-length and splice variant AR. In androgen-responsive CRPC cell model C4-2, SR-B1 antagonism suppressed cholesterol uptake, de novo steroidogenesis, and AR activity. SR-B1 antagonism also suppressed growth and viability and induced endoplasmic reticulum stress and autophagy. The inability of exogenous steroids to reverse these effects indicates that AR pathway activation is insufficient to overcome cytotoxic stress caused by a decrease in the availability of cholesterol. Furthermore, SR-B1 antagonism decreased cholesterol uptake, growth, and viability of the AR-null CRPC cell model PC-3, and the small-molecule SR-B1 antagonist block lipid transport-1 decreased xenograft growth rate despite poor pharmacologic properties. Overall, our findings show that SR-B1 is upregulated in primary and castration-resistant disease and is essential for cholesterol uptake needed to drive both steroidogenic and nonsteroidogenic biogenic pathways, thus implicating SR-B1 as a novel and potentially actionable target in CRPC. SIGNIFICANCE: These findings highlight SR-B1 as a potential target in primary and castration-resistant prostate cancer that is essential for cholesterol uptake needed to drive steroidogenic and nonsteroidogenic biogenic pathways.

Metabolomic profiling for the identification of novel diagnostic markers and therapeutic targets in prostate cancer: an update

INTRODUCTION

An altered metabolic regulation is involved in the development and progression of different cancer types. As well as this, many genes associated with tumors are shown to have an important role in control of the metabolism. The incidence of prostate cancer (PCa) is increased in men with metabolic disorders. In particular, obesity is an established risk factor for PCa. An increased body mass index correlates with aggressive disease, and a higher risk of biochemical recurrence and prostate cancer-specific mortality. Increased lipogenesis is also one of the most significant events in PCa metabolism reprogramming. Areas covered: In this article, we provide an updated review of the current understanding of the PCa metabolome and evaluate the possibility of unveiling novel therapeutic targets. Expert opinion: Obesity is an established risk factor for PCa, and an increased BMI correlates with aggressive disease, and a higher risk of biochemical recurrence and prostate cancer-specific mortality. PCa metabolome is characterized by the accumulation of metabolic intermediates and an increased expression of genes in the tricarboxylic acid cycle, the induction of de novo lipogenesis and cholesterogenesis. PCa cells can induce different alterations in their microenvironment by modulating the crosstalk between cancer and stromal cells.

Metabolic Alterations, Aggressive Hormone-Naïve Prostate Cancer and Cardiovascular Disease: A Complex Relationship

Background: Epidemiological studies suggest a possible relationship between metabolic alterations, cardiovascular disease and aggressive prostate cancer, however, no clear consensus has been reached. Objective: The aim of the study was to analyze the recent literature and summarize our experience on the association between metabolic disorders, aggressive hormone-naïve prostate cancer and cardiovascular disease. Method: We identified relevant papers by searching in electronic databases such as Scopus, Life Science Journals, and Index Medicus/Medline. Moreover, we showed our experience on the reciprocal relationship between metabolic alterations and aggressive prostate cancer, without the influence of hormone therapy, as well the role of coronary and carotid vasculopathy in advanced prostate carcinoma. Results: Prostate cancer cells have an altered metabolic homeostatic control linked to an increased aggressivity and cancer mortality. The absence of discrimination of risk factors as obesity, systemic arterial hypertension, diabetes mellitus, dyslipidemia and inaccurate selection of vascular diseases as coronary and carotid damage at initial diagnosis of prostate cancer could explain the opposite results in the literature. Systemic inflammation and oxidative stress associated with metabolic alterations and cardiovascular disease can also contribute to prostate cancer progression and increased tumor aggressivity. Conclusions: Metabolic alterations and cardiovascular disease influence aggressive and metastatic prostate cancer. Therefore, a careful evaluation of obesity, diabetes mellitus, dyslipidemia, systemic arterial hypertension, together with a careful evaluation of cardiovascular status, in particular coronary and carotid vascular disease, should be carried out after an initial diagnosis of prostatic carcinoma.

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.

Metabolomics Profiling on Different Stages of Colorectal Cancer: A Systematic Review

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Early diagnosis and accurate staging of the disease is vital to improve the prognosis. Metabolomics has been used to identify changes in metabolite profiles in the different stages of cancer in order to introduce new non-invasive molecular tools for staging. In this systematic review, we aim to identify the common metabolite changes in human biological samples and the dominant metabolic pathways associated with CRC progression. A broad systematic search was carried out from selected databases. Four reviewers screened and reviewed the titles, abstracts, and full-text articles according to the inclusion and exclusion criteria. Quality assessment was conducted on the eight articles which met the criteria. Data showed that the metabolites involved with redox status, energy metabolism and intermediates of amino acids, choline and nucleotides metabolism were the most affected during CRC progression. However, there were differences in the levels of individual metabolites detected between the studies, and this might be due to the study population, sample preparation, analytical platforms used and statistical tools. In conclusion, this systematic review highlights the changes in metabolites from early to late stages of CRC. Moreover, biomarkers for prognosis are important to reduce CRC-related mortality.

LXRs, SHP, and FXR in Prostate Cancer: Enemies or Ménage à Quatre With AR?

Androgens and androgen receptor (AR, NR3C4) clearly play a crucial role in prostate cancer progression. Besides, the link between metabolic disorders and the risk of developing a prostate cancer has been emerging these last years. Interestingly, “lipid” nuclear receptors such as LXRα/NR1H3 and LXRβ/NR1H2 (as well as FXRα/NR1H4 and SHP/NR0B2) have been described to decrease the lipid metabolism, while AR increases it. Moreover, these former orphan nuclear receptors can regulate androgen levels and modulate AR activity. Thus, it is not surprising to find such receptors involved in the physiology of prostate. This review is focused on the roles of liver X receptors (LXRs), farnesoid X receptor (FXR), and small heterodimeric partner (SHP) in prostate physiology and their capabilities to interfere with the androgen-regulated pathways by modulating the levels of active androgen within the prostate. By the use of prostate cancer cell lines, mice deficient for these nuclear receptors and human tissue libraries, several authors have pointed out the putative possibility to pharmacologically target these receptors. These data open a new field of research for the development of new drugs that could overcome the castration resistance in prostate cancer, a usual phenomenon in patients.

Ser-486/491 phosphorylation and inhibition of AMPKα activity is positively associated with Gleason score, metastasis, and castration-resistance in prostate cancer: A retrospective clinical study

BACKGROUND

We previously demonstrated that adenosine monophosphate-activated protein kinase (AMPKα) activity is significantly inhibited by Ser-486/491 phosphorylation in cell culture and in vivo models of metastatic and castration-resistant prostate cancer, and hypothesized these findings may translate to clinical specimens.

METHODS

In this retrospective, single-institution pilot study, 45 metastatic prostate cancer cases were identified within the University Hospitals Cleveland Medical Center Pathology Archive with both metastasis and matched primary prostate tumor specimens in formalin-fixed, paraffin-embedded blocks, and complete electronic medical records. Thirty non-metastatic, hormone-dependent prostate cancer controls, who were progression-free as defined by undetectable prostate specific antigen for at least 79.6 months (range 79.6-136.0 months), and matched metastatic cases based on age, race, and year of diagnosis. All specimens were collected from 1991 to 2014; primary tumor specimens were obtained via diagnostic biopsy or prostatectomy, and metastasis specimens obtained via surgery or perimortem. 5-μ sequential slides were processed for phospho-Ser-486/491 AMPKα₁ /α₂ , phospho-Thr-172 AMPKα, AMPKα₁ /α₂ , phospho-Ser-792 Raptor, phospho-Ser-79 acetyl-CoA carboxylase, and phospho-Ser-872, 3-hydroxy-3-methylglutaryl-CoA reductase immunohistochemistry to determine expression, phosphorylation pattern, and activity of AMPKα.

RESULTS

Increased inhibitory Ser-486/491 AMPKα₁ /α₂ phosphorylation, increased AMPKα protein expression, decreased AMPKα activity, and loss of nuclear AMPKα and p-AMPKα are associated with prostate cancer progression to metastasis. Increased p-Ser-486/491 AMPKα₁ /α₂ was also positively correlated with higher Gleason grade and progression to castration-resistance.

CONCLUSIONS

p-Ser-486/491 AMPKα₁ /α₂ is a novel marker of prostate cancer metastasis and castration-resistance. Ser-486/491 phosphokinases should be pursued as targets for metastatic and castration-resistant prostate cancer chemotherapy.

Lipid metabolism and carcinogenesis, cancer development

The disorder of lipid metabolism is pathologically linked to hyperlipidemia, lipid storage disease, obesity and other related diseases. Intriguingly, recent studies have revealed that lipid metabolism disorders play an important role in carcinogenesis and development as well, since they cause abnormal expression of various genes, proteins, and dysregulation of cytokines and signaling pathways. More importantly, lipid-lowering drugs and anti-lipid per-oxidation treatment have been showing their advantages in clinic, in comparison with other anti-cancer drugs with high toxicity. Thus, further elucidation of molecular mechanism between lipid metabolism and cancer is essential in developing novel diagnostic biomarkers and therapeutic targets of human cancers.

Bone Cell Activity in Clinical Prostate Cancer Bone Metastasis and Its Inverse Relation to Tumor Cell Androgen Receptor Activity

Advanced prostate cancer frequently metastasizes to bone and induces a mixed osteoblastic/osteolytic bone response. Standard treatment for metastatic prostate cancer is androgen-deprivation therapy (ADT) that also affects bone biology. Treatment options for patients relapsing after ADT are limited, particularly in cases where castration-resistance does not depend on androgen receptor (AR) activity. Patients with non-AR driven metastases may, however, benefit from therapies targeting the tumor microenvironment. Therefore, the current study specifically investigated bone cell activity in clinical bone metastases in relation to tumor cell AR activity, in order to gain novel insight into biological heterogeneities of possible importance for patient stratification into bone-targeting therapies. Metastasis tissue obtained from treatment-naïve (n = 11) and castration-resistant (n = 28) patients was characterized using whole-genome expression analysis followed by multivariate modeling, functional enrichment analysis, and histological evaluation. Bone cell activity was analyzed by measuring expression levels of predefined marker genes representing osteoclasts (ACP5, CTSK, MMP9), osteoblasts (ALPL, BGLAP, RUNX2) and osteocytes (SOST). Principal component analysis indicated a positive correlation between osteoblast and osteoclast activity and a high variability in bone cell activity between different metastases. Immunohistochemistry verified a positive correlation between runt-related transcription factor 2 (RUNX2) positive osteoblasts and tartrate-resistant acid phosphatase (TRAP, encoded by ACP5) positive osteoclasts lining the metastatic bone surface. No difference in bone cell activity was seen between treatment-naïve and castration-resistant patients. Importantly, bone cell activity was inversely correlated to tumor cell AR activity (measured as AR, FOXA1, HOXB13, KLK2, KLK3, NKX3-1, STEAP2, and TMPRSS2 expression) and to patient serum prostate-specific antigen (PSA) levels. Functional enrichment analysis indicated high bone morphogenetic protein (BMP) signaling in metastases with high bone cell activity and low tumor cell AR activity. This was confirmed by BMP4 immunoreactivity in tumor cells of metastases with ongoing bone formation, as determined by histological evaluation of van Gieson-stained sections. In conclusion, the inverse relation observed between bone cell activity and tumor cell AR activity in prostate cancer bone metastasis may be of importance for patient response to AR and/or bone targeting therapies, but needs to be evaluated in clinical settings in relation to serum markers for bone remodeling, radiography and patient response to therapy. The importance of BMP signaling in the development of sclerotic metastasis lesions deserves further exploration.

GC-MS-Based Endometabolome Analysis Differentiates Prostate Cancer from Normal Prostate Cells

Prostate cancer (PCa) is an important health problem worldwide. Diagnosis and management of PCa is very complex because the detection of serum prostate specific antigen (PSA) has several drawbacks. Metabolomics brings promise for cancer biomarker discovery and for better understanding PCa biochemistry. In this study, a gas chromatography–mass spectrometry (GC-MS) based metabolomic profiling of PCa cell lines was performed. The cell lines include 22RV1 and LNCaP from PCa with androgen receptor (AR) expression, DU145 and PC3 (which lack AR expression), and one normal prostate cell line (PNT2). Regarding the metastatic potential, PC3 is from an adenocarcinoma grade IV with high metastatic potential, DU145 has a moderate metastatic potential, and LNCaP has a low metastatic potential. Using multivariate analysis, alterations in levels of several intracellular metabolites were detected, disclosing the capability of the endometabolome to discriminate all PCa cell lines from the normal prostate cell line. Discriminant metabolites included amino acids, fatty acids, steroids, and sugars. Six stood out for the separation of all the studied PCa cell lines from the normal prostate cell line: ethanolamine, lactic acid, β-Alanine, L-valine, L-leucine, and L-tyrosine.

Liver X receptors constrain tumor development and metastasis dissemination in PTEN-deficient prostate cancer

Advanced prostate cancer (PCa) is a clinical challenge as no curative therapeutic is available. In this context, a better understanding of metastasis and resistance mechanisms in PCa is an important issue. As phosphatase and tensin homolog (PTEN) loss is the most common genetic lesion in such cancer, we investigate human data sets for mechanisms that can constrain cancer evolution in this setting. Here we report a liver X receptor (LXR) signature, which tightly correlates with PTEN loss, in PCa. Accordingly, the LXR pathway is deregulated in prostate carcinomas in Pten-null mice. Genetic ablation of LXRs in Pten-null mice, exacerbates PCa invasiveness and metastatic dissemination, which involves mesenchymal transition and accumulation of matrix metalloproteinases. Mechanistically, PTEN deletion governed LXR transcriptional activity through deregulation of cholesterol de novo synthesis, resulting in accumulation of endogenous LXR ligands. Our study therefore reveals a functional circuit linking PTEN and LXR, and highlights LXRs as metabolic gatekeepers that are able to constrain PCa progression.

Treatment of prostate cancer, especially in its advanced stage, is still challenging; therefore, strategies to prevent metastatic dissemination are of great interest. Here the authors reveal a crucial role for liver X receptors in suppressing prostate carcinogenesis and metastatic progression in PTEN-null tumors.

Metabolomic Profiling of Extracellular Vesicles and Alternative Normalization Methods Reveal Enriched Metabolites and Strategies to Study Prostate Cancer-Related Changes

Body fluids are a rich source of extracellular vesicles (EVs), which carry cargo derived from the secreting cells. So far, biomarkers for pathological conditions have been mainly searched from their protein, (mi)RNA, DNA and lipid cargo. Here, we explored the small molecule metabolites from urinary and platelet EVs relative to their matched source samples. As a proof-of-concept study of intra-EV metabolites, we compared alternative normalization methods to profile urinary EVs from prostate cancer patients before and after prostatectomy and from healthy controls.

Methods: We employed targeted ultra-performance liquid chromatography-tandem mass spectrometry to profile over 100 metabolites in the isolated EVs, original urine samples and platelets. We determined the enrichment of the metabolites in the EVs and analyzed their subcellular origin, pathways and relevant enzymes or transporters through data base searches. EV- and urine-derived factors and ratios between metabolites were tested for normalization of the metabolomics data.

Results: Approximately 1 x 10¹⁰ EVs were sufficient for detection of metabolite profiles from EVs. The profiles of the urinary and platelet EVs overlapped with each other and with those of the source materials, but they also contained unique metabolites. The EVs enriched a selection of cytosolic metabolites including members from the nucleotide and spermidine pathways, which linked to a number of EV-resident enzymes or transporters. Analysis of the urinary EVs from the patients indicated that the levels of glucuronate, D-ribose 5-phosphate and isobutyryl-L-carnitine were 2-26-fold lower in all pre-prostatectomy samples compared to the healthy control and post-prostatectomy samples (p < 0.05). These changes were only detected from EVs by normalization to EV-derived factors or with metabolite ratios, and not from the original urine samples.

Conclusions: Our results suggest that metabolite analysis of EVs from different samples is feasible using a high-throughput platform and relatively small amount of sample material. With the knowledge about the specific enrichment of metabolites and normalization methods, EV metabolomics could be used to gain novel biomarker data not revealed by the analysis of the original EV source materials.

Modulating cancer cell survival by targeting intracellular cholesterol transport

Background:

Demand for cholesterol is high in certain cancers making them potentially sensitive to therapeutic strategies targeting cellular cholesterol homoeostasis. A potential approach involves disruption of intracellular cholesterol transport, which occurs in Niemann–Pick disease as a result of acid sphingomyelinase (ASM) deficiency. Hence, a class of lysosomotropic compounds that were identified as functional ASM inhibitors (FIASMAs) might exhibit chemotherapeutic activity by disrupting cancer cell cholesterol homoeostasis.

Methods:

Here, the chemotherapeutic utility of ASM inhibition was investigated. The effect of FIASMAs on intracellular cholesterol levels, cholesterol homoeostasis, cellular endocytosis and signalling cascades were investigated. The in vivo efficacy of ASM inhibition was demonstrated using melanoma xenografts and a nanoparticle formulation was developed to overcome dose-limiting CNS-associated side effects of certain FIASMAs.

Results:

Functional ASM inhibitors inhibited intracellular cholesterol transport leading to disruption of autophagic flux, cellular endocytosis and receptor tyrosine kinase signalling. Consequently, major oncogenic signalling cascades on which cancer cells were reliant for survival were inhibited. Two tested ASM inhibitors, perphenazine and fluphenazine that are also clinically used as antipsychotics, were effective in inhibiting xenografted tumour growth. Nanoliposomal encapsulation of the perphenazine enhanced its chemotherapeutic efficacy while decreasing CNS-associated side effects.

Conclusions:

This study suggests that disruption of intracellular cholesterol transport by targeting ASM could be utilised as a potential chemotherapeutic approach for treating cancer.

Preliminary evaluation of serum total cholesterol concentrations in dogs with osteosarcoma

OBJECTIVES

To determine if total serum cholesterol concentrations were altered in dogs with osteosarcoma. To evaluate association of total serum cholesterol concentration with clinical outcomes in dogs with appendicular osteosarcoma.

MATERIALS AND METHODS

Retrospective, multi-institutional study on 64 dogs with osteosarcoma. Control population consisted of dogs with traumatic bone fractures (n=30) and healthy patients of similar age and weight as those of the osteosarcoma cases (n=31). Survival analysis was done on 35 appendicular osteosarcoma patients that received the current standard of care. Statistical associations were assessed by univariable and multi-variable analysis. Information about age, sex, primary tumour location, total cholesterol concentration, monocytes and lymphocyte counts and alkaline phosphatase were also included.

RESULTS

Total cholesterol was elevated above the reference interval (3·89 to 7·12 mmol/L) (150 to 275 mg/dL) in 29 of 64 (45·3%) osteosarcoma-bearing dogs, whereas similar elevations were found in only 3 of 30 (10%) fracture controls (P<0·0001) and 2 of 31 (6·5%) similar age/weight controls (P=0·0002). Elevated total cholesterol was significantly associated with a reduced hazard ratio (0·27, P=0·008) for overall mortality in dogs with osteosarcoma.

CLINICAL SIGNIFICANCE

These results suggest that elevated total cholesterol is associated with canine osteosarcoma and may have prognostic significance.

Simvastatin and MBCD Inhibit Breast Cancer-Induced Osteoclast Activity by Targeting Osteoclastogenic Factors

Previous reports have documented that cholesterol-lowering simvastatin prevented osteolytic metastasis of breast cancer in animal model in which cancer cells were placed into blood circulation. Thus, simvastatin treatment might have a preventive effect in inhibiting osteoclast activity of metastatic bone microenvironment. This study documented that both simvastatin and MBCD (cholesterol depleting drug) blocked the breast cancer-induced TRAP and MMP activity, and expressions of various osteoclastogenic genes (TRAP, Cathepsin K, and NFATc1) in pre-osteoclast RAW264.7 cells, and osteoclastogenic CSF-1 and RANKL expressions in breast cancer MCF-7 cells. Thus, these findings unravel a molecular mechanism of simvastatin-/MBCD-mediated inhibition of breast cancer-driven osteoclast activity.

Assessing Heterogeneity of Osteolytic Lesions in Multiple Myeloma by ¹H HR-MAS NMR Metabolomics

Multiple myeloma (MM) is a malignancy of plasma cells characterized by multifocal osteolytic bone lesions. Macroscopic and genetic heterogeneity has been documented within MM lesions. Understanding the bases of such heterogeneity may unveil relevant features of MM pathobiology. To this aim, we deployed unbiased ¹H high-resolution magic-angle spinning (HR-MAS) nuclear magnetic resonance (NMR) metabolomics to analyze multiple biopsy specimens of osteolytic lesions from one case of pathological fracture caused by MM. Multivariate analyses on normalized metabolite peak integrals allowed clusterization of samples in accordance with a posteriori histological findings. We investigated the relationship between morphological and NMR features by merging morphological data and metabolite profiling into a single correlation matrix. Data-merging addressed tissue heterogeneity, and greatly facilitated the mapping of lesions and nearby healthy tissues. Our proof-of-principle study reveals integrated metabolomics and histomorphology as a promising approach for the targeted study of osteolytic lesions.

Targeting SR-BI for Cancer Diagnostics, Imaging and Therapy

Scavenger receptor class B type I (SR-BI) plays an important role in trafficking cholesteryl esters between the core of high density lipoprotein and the liver. Interestingly, this integral membrane protein receptor is also implicated in the metabolism of cholesterol by cancer cells, whereby overexpression of SR-BI has been observed in a number of tumors and cancer cell lines, including breast and prostate cancers. Consequently, SR-BI has recently gained attention as a cancer biomarker and exciting target for the direct cytosolic delivery of therapeutic agents. This brief review highlights these key developments in SR-BI-targeted cancer therapies and imaging probes. Special attention is given to the exploration of high density lipoprotein nanomimetic platforms that take advantage of upregulated SR-BI expression to facilitate targeted drug-delivery and cancer diagnostics, and promising future directions in the development of these agents.

Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

Abrogating cholesterol esterification suppresses growth and metastasis of pancreatic cancer

Cancer cells are known to execute reprogramed metabolism of glucose, amino acids and lipids. Here, we report a significant role of cholesterol metabolism in cancer metastasis. By using label-free Raman spectromicroscopy, we found an aberrant accumulation of cholesteryl ester in human pancreatic cancer specimens and cell lines, mediated by acyl-CoA cholesterol acyltransferase-1 (ACAT-1) enzyme. Expression of ACAT-1 showed a correlation with poor patient survival. Abrogation of cholesterol esterification, either by an ACAT-1 inhibitor or by shRNA knockdown, significantly suppressed tumor growth and metastasis in an orthotopic mouse model of pancreatic cancer. Mechanically, ACAT-1 inhibition increased intracellular free cholesterol level, which was associated with elevated endoplasmic reticulum stress and caused apoptosis. Collectively, our results demonstrate a new strategy for treating metastatic pancreatic cancer by inhibiting cholesterol esterification.

Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence

Metabolite profiling is being increasing employed in the study of prostate cancer as a means of identifying predictive, diagnostic, and prognostic biomarkers. This review provides a summary and critique of the current literature. Thirty-three human case-control studies of prostate cancer exploring disease prediction, diagnosis, progression, or treatment response were identified. All but one demonstrated the ability of metabolite profiling to distinguish cancer from benign, tumor aggressiveness, cases who recurred, and those who responded well to therapy. In the subset of studies where biomarker discriminatory ability was quantified, high AUCs were reported that would potentially outperform the current gold standards in diagnosis, prognosis, and disease recurrence, including PSA testing. There were substantial similarities between the metabolites and the associated pathways reported as significant by independent studies, and important roles for abnormal cell growth, intensive cell proliferation, and dysregulation of lipid metabolism were highlighted. The weight of the evidence therefore suggests metabolic alterations specific to prostate carcinogenesis and progression that may represent potential metabolic biomarkers. However, replication and validation of the most promising biomarkers is currently lacking and a number of outstanding methodologic issues remain to be addressed to maximize the utility of metabolomics in the study of prostate cancer. Cancer Epidemiol Biomarkers Prev; 25(6); 887-906. ©2016 AACR.

The Role of Cholesterol in Cancer

The roles played by cholesterol in cancer development and the potential of therapeutically targeting cholesterol homeostasis is a controversial area in the cancer community. Several epidemiologic studies report an association between cancer and serum cholesterol levels or statin use, while others suggest that there is not one. Furthermore, the Cancer Genome Atlas (TCGA) project using next-generation sequencing has profiled the mutational status and expression levels of all the genes in diverse cancers, including those involved in cholesterol metabolism, providing correlative support for a role of the cholesterol pathway in cancer development. Finally, preclinical studies tend to more consistently support the role of cholesterol in cancer, with several demonstrating that cholesterol homeostasis genes can modulate development. Because of space limitations, this review provides selected examples of the epidemiologic, TCGA, and preclinical data, focusing on alterations in cholesterol homeostasis and its consequent effect on patient survival. In melanoma, this focused analysis demonstrated that enhanced expression of cholesterol synthesis genes was associated with decreased patient survival. Collectively, the studies in melanoma and other cancer types suggested a potential role of disrupted cholesterol homeostasis in cancer development but additional studies are needed to link population-based epidemiological data, the TCGA database results, and preclinical mechanistic evidence to concretely resolve this controversy. Cancer Res; 76(8); 2063-70. ©2016 AACR.

Multi-platform mass spectrometry analysis of the CSF and plasma metabolomes of rigorously matched amyotrophic lateral sclerosis, Parkinson's disease and control subjects

Amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD) are protein-aggregation diseases that lack clear molecular etiologies. Biomarkers could aid in diagnosis, prognosis, planning of care, drug target identification and stratification of patients into clinical trials. We sought to characterize shared and unique metabolite perturbations between ALS and PD and matched controls selected from patients with other diagnoses, including differential diagnoses to ALS or PD that visited our clinic for a lumbar puncture. Cerebrospinal fluid (CSF) and plasma from rigorously age-, sex- and sampling-date matched patients were analyzed on multiple platforms using gas chromatography (GC) and liquid chromatography (LC)-mass spectrometry (MS). We applied constrained randomization of run orders and orthogonal partial least squares projection to latent structure-effect projections (OPLS-EP) to capitalize upon the study design. The combined platforms identified 144 CSF and 196 plasma metabolites with diverse molecular properties. Creatine was found to be increased and creatinine decreased in CSF of ALS patients compared to matched controls. Glucose was increased in CSF of ALS patients and α-hydroxybutyrate was increased in CSF and plasma of ALS patients compared to matched controls. Leucine, isoleucine and ketoleucine were increased in CSF of both ALS and PD. Together, these studies, in conjunction with earlier studies, suggest alterations in energy utilization pathways and have identified and further validated perturbed metabolites to be used in panels of biomarkers for the diagnosis of ALS and PD.

Cancer prevention and therapy through the modulation of the tumor microenvironment

Cancer arises in the context of an in vivo tumor microenvironment. This microenvironment is both a cause and consequence of tumorigenesis. Tumor and host cells co-evolve dynamically through indirect and direct cellular interactions, eliciting multiscale effects on many biological programs, including cellular proliferation, growth, and metabolism, as well as angiogenesis and hypoxia and innate and adaptive immunity. Here we highlight specific biological processes that could be exploited as targets for the prevention and therapy of cancer. Specifically, we describe how inhibition of targets such as cholesterol synthesis and metabolites, reactive oxygen species and hypoxia, macrophage activation and conversion, indoleamine 2,3-dioxygenase regulation of dendritic cells, vascular endothelial growth factor regulation of angiogenesis, fibrosis inhibition, endoglin, and Janus kinase signaling emerge as examples of important potential nexuses in the regulation of tumorigenesis and the tumor microenvironment that can be targeted. We have also identified therapeutic agents as approaches, in particular natural products such as berberine, resveratrol, onionin A, epigallocatechin gallate, genistein, curcumin, naringenin, desoxyrhapontigenin, piperine, and zerumbone, that may warrant further investigation to target the tumor microenvironment for the treatment and/or prevention of cancer.

Global Prioritization of Disease Candidate Metabolites Based on a Multi-omics Composite Network

The identification of disease-related metabolites is important for a better understanding of metabolite pathological processes in order to improve human medicine. Metabolites, which are the terminal products of cellular regulatory process, can be affected by multi-omic processes. In this work, we propose a powerful method, MetPriCNet, to predict and prioritize disease candidate metabolites based on integrated multi-omics information. MetPriCNet prioritized candidate metabolites based on their global distance similarity with seed nodes in a composite network, which integrated multi-omics information from the genome, phenome, metabolome and interactome. After performing cross-validation on 87 phenotypes with a total of 602 metabolites, MetPriCNet achieved a high AUC value of up to 0.918. We also assessed the performance of MetPriCNet on 18 disease classes and found that 4 disease classes achieved an AUC value over 0.95. Notably, MetPriCNet can also predict disease metabolites without known disease metabolite knowledge. Some new high-risk metabolites of breast cancer were predicted, although there is a lack of known disease metabolite information. A predicted disease metabolic landscape was constructed and analyzed based on the results of MetPriCNet for 87 phenotypes to help us understand the genetic and metabolic mechanism of disease from a global view.

The HDL receptor SR-BI is associated with human prostate cancer progression and plays a possible role in establishing androgen independence

BACKGROUND

Human prostate cancer represents one of the most frequently diagnosed cancers in men worldwide. Currently, diagnostic methods are insufficient to identify patients at risk for aggressive prostate cancer, which is essential for early treatment. Recent data indicate that elevated cholesterol levels in the plasma are a prerequisite for the progression of prostate cancer. Here, we analyzed clinical prostate cancer samples for the expression of receptors involved in cellular cholesterol uptake.

METHODS

We screened mRNA microarray files of prostate cancer samples for alterations in the expression levels of cholesterol transporters. Furthermore, we performed immunohistochemistry analysis on human primary prostate cancer tissue sections derived from patients to investigate the correlation of SR-BI with clinicopathological parameters and the mTOR target pS6.

RESULTS

In contrast to LDLR, we identified SR-BI mRNA and protein expression to be induced in high Gleason grade primary prostate cancers. Histologic analysis of prostate biopsies revealed that 53.6 % of all cancer samples and none of the non-cancer samples showed high SR-BI staining intensity. The disease-free survival time was reduced (P = 0.02) in patients expressing high intra-tumor levels of SR-BI. SR-BI mRNA correlated with HSD17B1 and HSD3B1 and SR-BI protein staining showed correlation with active ribosomal protein S6 (RS = 0.828, P < 0.00001).

CONCLUSIONS

We identified SR-BI to indicate human prostate cancer formation, suggesting that increased levels of SR-BI may be involved in the generation of a castration-resistant phenotype.

Changes in urinary metabolic profiles of colorectal cancer patients enrolled in a prospective cohort study (ColoCare)

INTRODUCTION

Metabolomics is a valuable tool for biomarker screening of colorectal cancer (CRC). In this study, we profiled the urinary metabolomes of patients enrolled in a prospective patient cohort (ColoCare). We aimed to describe changes in the metabolome in the longer clinical follow-up and describe initial predictors as candidate markers with possibly prognostic significance.

METHODS

In total, 199 urine samples from CRC patients pre-surgery (n=97), 1-8 days post-surgery (n=12) and then after 6 and 12 months (n=52 and 38, respectively) were analyzed using both GC-MS and ¹H-NMR. Both datasets were analyzed separately with built in uni- and multivariate analyses of Metaboanalyst 2.0. Furthermore, adjusted linear mixed effects regression models were constructed.

RESULTS

Many concentrations of the metabolites derived from the gut microbiome were affected by CRC surgery, presumably indicating a tumor-induced shift in bacterial species. Associations of the microbial metabolites with disease stage indicate an important role of the gut microbiome in CRC.We were able to differentiate the metabolite profiles of CRC patients prior to surgery from those at any post-surgery timepoint using a multivariate model containing 20 marker metabolites (AUCROC=0.89; 95% CI:0.84-0.95).

CONCLUSION

To the best of our knowledge, this is one of the first metabolomic studies to follow CRC patients in a prospective setting with repeated urine sampling over time. We were able to confirm markers initially identified in case-control studies and pin point metabolites which may serve as candidates for prognostic biomarkers of CRC.

Analytical protocols based on LC-MS, GC-MS and CE-MS for nontargeted metabolomics of biological tissues

Invasive, site-specific metabolite information could be better obtained from tissues. Hence, highly sensitive mass spectrometry-based metabolomics coupled with separation techniques are increasingly in demand in clinical research for tissue metabolomics application. Applying these techniques to nontargeted tissue metabolomics provides identification of distinct metabolites. These findings could help us to understand alterations at the molecular level, which can also be applied in clinical practice as screening markers for early disease diagnosis. However, tissues as solid and heterogeneous samples pose an additional analytical challenge that should be considered in obtaining broad, reproducible and representative analytical profiles. This manuscript summarizes the state of the art in tissue (human and animal) treatment (quenching, homogenization and extraction) for nontargeted metabolomics with mass spectrometry.

Metabolomics and its Application to the Development of Clinical Laboratory Tests for Prostate Cancer

INTRODUCTION

There is a critical need to develop clinical laboratory assays that provide risk assessment for men at elevated risk for prostate cancer, and once diagnosed, could further identify those men with clinically significant disease.

METHODS

Recent advancements in analytical instrumentation have enabled mass spectrometry-based metabolomics methodologies. Further advancements in chromatographic techniques have facilitated high throughput, quantitative assays for a broad spectrum of biochemicals.

RESULTS

Screening metabolomics techniques have been applied to biospecimens from large cohorts of men comparing those individuals with prostate cancer to those with no evidence of malignancy. Work beginning in tissues has identified biochemical profiles that correlate with disease and disease severity, including tumor grade and stage. Some of these metabolic abnormalities, such as dramatic elevations in sarcosine, have been found to translate into biological fluids, especially blood and urine, which can be sampled in a minimally invasive manner.

DISCUSSION

The differential abundances of these tumor-associated metabolites have been found to improve the performance of clinical prognostic/diagnostic tools.

CONCLUSION

The outlook is bright for metabolomic technology to address clinical diagnostic needs for prostate cancer patient management. Early validation of specific clinical tests provides a preview of further successes in this area. Metabolomics has shown its utility to complement and augment traditional clinical approaches as well as emerging genomic, transcriptomic and proteomic methodologies, and is expected to play a key role in the precision medicine-based management of the prostate cancer patient.

Metabolomics-derived prostate cancer biomarkers: fact or fiction?

Despite continuing research for precise probing and grading of prostate cancer (PC) biomarkers, the indexes lack sensitivity and specificity. To search for PC biomarkers, we used proton nuclear magnetic resonance ((1)H NMR)-derived serum metabolomics. The study comprises 102 serum samples obtained from low-grade (LG, n = 40) and high-grade (HG, n = 30) PC cases and healthy controls (HC, n = 32). (1)H NMR-derived serum data were examined using principal component analysis and orthogonal partial least-squares discriminant analysis. The strength of the model was verified by internal cross-validation using the same samples divided into 70% as training and 30% as test data sets. Receiver operating characteristic (ROC) curve examination was also achieved. Serum metabolomics reveals that four biomarkers (alanine, pyruvate, glycine, and sarcosine) were able to accurately (ROC 0.966) differentiate 90.2% of PC cases with 84.4% sensitivity and 92.9% specificity compared with HC. Similarly, three biomarkers, alanine, pyruvate, and glycine, were able to precisely (ROC 0.978) discriminate 92.9% of LG from HG PC with 92.5% sensitivity and 93.3% specificity. The robustness of these biomarkers was confirmed by prediction of the test data set with >99% diagnostic precision for PC determination. These findings demonstrate that (1)H NMR-based serum metabolomics is a promising approach for probing and grading PC.

Application of metabolomics in thyroid cancer research

Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput "omics" techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis.

High Cholesterol Deteriorates Bone Health: New Insights into Molecular Mechanisms

Many epidemiological studies show a positive connection between cardiovascular diseases and risk of osteoporosis, suggesting a role of hyperlipidemia and/or hypercholesterolemia in regulating osteoporosis. The majority of the studies indicated a correlation between high cholesterol and high LDL-cholesterol level with low bone mineral density, a strong predictor of osteoporosis. Similarly, bone metastasis is a serious complication of cancer for patients. Several epidemiological and basic studies have established that high cholesterol is associated with increased cancer risk. Moreover, osteoporotic bone environment predisposes the cancer cells for metastatic growth in the bone microenvironment. This review focuses on how cholesterol and cholesterol-lowering drugs (statins) regulate the functions of bone residential osteoblast and osteoclast cells to augment or to prevent bone deterioration. Moreover, this study provides an insight into molecular mechanisms of cholesterol-mediated bone deterioration. It also proposes a potential mechanism by which cellular cholesterol boosts cancer-induced bone metastasis.

Combination simvastatin and metformin induces G1-phase cell cycle arrest and Ripk1- and Ripk3-dependent necrosis in C4-2B osseous metastatic castration-resistant prostate cancer cells

Castration-resistant prostate cancer (CRPC) cells acquire resistance to chemotherapy and apoptosis, in part, due to enhanced aerobic glycolysis and biomass production, known as the Warburg effect. We previously demonstrated that combination simvastatin (SIM) and metformin (MET) ameliorates critical Warburg effect-related metabolic aberrations of C4-2B cells, synergistically and significantly decreases CRPC cell viability and metastatic properties, with minimal effect on normal prostate epithelial cells, and inhibits primary prostate tumor growth, metastasis, and biochemical failure in an orthotopic model of metastatic CRPC, more effectively than docetaxel chemotherapy. Several modes of cell death activated by individual treatment of SIM or MET have been reported; however, the cell death process induced by combination SIM and MET treatment in metastatic CRPC cells remains unknown. This must be determined prior to advancing combination SIM and MET to clinical trial for metastatic CRPC. Treatment of C4-2B cells with combination 4 μM SIM and 2 mM MET (SIM+MET) led to significant G1-phase cell cycle arrest and decrease in the percentage of DNA-replicating cells in the S-phase by 24 h; arrest was sustained throughout the 96-h treatment. SIM+MET treatment led to enhanced autophagic flux in C4-2B cells by 72–96 h, ascertained by increased LC3B-II (further enhanced with lysosomal inhibitor chloroquine) and reduced Sequestosome-1 protein expression, significantly increased percentage of acidic vesicular organelle-positive cells, and increased autophagic structure accumulation assessed by transmission electron microscopy. Chloroquine, however, could not rescue CRPC cell viability, eliminating autophagic cell death; rather, autophagy was upregulated by C4-2B cells in attempt to withstand chemotherapy. Instead, SIM+MET treatment led to Ripk1- and Ripk3-dependent necrosis by 48–96 h, determined by propidium iodide-Annexin V flow cytometry, increase in Ripk1 and Ripk3 protein expression, necrosome formation, HMGB-1 extracellular release, and necrotic induction and viability rescue with necrostatin-1 and Ripk3-targeting siRNA. The necrosis-inducing capacity of SIM+MET may make these drugs a highly-effective treatment for apoptosis- and chemotherapy-resistant metastatic CRPC cells.

1-stearoylglycerol is associated with risk of prostate cancer: results from serum metabolomic profiling

Although prostate cancer is the most commonly diagnosed cancer among men in developed populations, recent recommendations against routine prostate-specific antigen screening have cast doubt on its utility for early detection. We compared the metabolomic profiles of prospectively collected fasting serum from 74 prostate cancer cases and 74 controls selected from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort of male smokers. Circulating 1-stearoylglycerol (1-SG, or 1-monostearin) was statistically significantly inversely associated with risk of prostate cancer after Bonferroni correction for multiple comparisons (i.e., 420 identified metabolites) (OR=0.34, 95% CI=0.20 - 0.58, p=6.3 × 10-5). The magnitude of this association did not differ by disease aggressiveness and was observed for cases diagnosed up to 23 years after blood collection. Similar but somewhat weaker prostate cancer risk signals were also evident for glycerol and alpha-ketoglutarate. In this population, men with higher serum 1-SG were less likely to develop prostate cancer, supporting a role for dysregulation of lipid metabolism in this malignancy. Additional studies are needed to retest the association and to examine 1-SG for its potential as a prostate cancer early detection marker.

Synergistic simvastatin and metformin combination chemotherapy for osseous metastatic castration-resistant prostate cancer

Docetaxel chemotherapy remains a standard of care for metastatic castration-resistant prostate cancer (CRPC). Docetaxel modestly increases survival, yet results in frequent occurrence of side effects and resistant disease. An alternate chemotherapy with greater efficacy and minimal side effects is needed. Acquisition of metabolic aberrations promoting increased survival and metastasis in CRPC cells includes constitutive activation of Akt, loss of adenosine monophosphate-activated protein kinase (AMPK) activity due to Ser-485/491 phosphorylation, and overexpression of 3-hydroxy-3-methylglutaryl-Coenzyme A reductase (HMG-CoAR). We report that combination of simvastatin and metformin, within pharmacologic dose range (500 nmol/L to 4 μmol/L simvastatin and 250 μmol/L to 2 mmol/L metformin), significantly and synergistically reduces C4-2B3/B4 CRPC cell viability and metastatic properties, with minimal adverse effects on normal prostate epithelial cells. Combination of simvastatin and metformin decreased Akt Ser-473 and Thr-308 phosphorylation and AMPKα Ser-485/491 phosphorylation; increased Thr-172 phosphorylation and AMPKα activity, as assessed by increased Ser-79 and Ser-872 phosphorylation of acetyl-CoA carboxylase and HMG-CoAR, respectively; decreased HMG-CoAR activity; and reduced total cellular cholesterol and its synthesis in both cell lines. Studies of C4-2B4 orthotopic NCr-nu/nu mice further demonstrated that combination of simvastatin and metformin (3.5-7.0 μg/g body weight simvastatin and 175-350 μg/g body weight metformin) daily by oral gavage over a 9-week period significantly inhibited primary ventral prostate tumor formation, cachexia, bone metastasis, and biochemical failure more effectively than 24 μg/g body weight docetaxel intraperitoneally injected every 3 weeks, 7.0 μg/g/day simvastatin, or 350 μg/g/day metformin treatment alone, with significantly less toxicity and mortality than docetaxel, establishing combination of simvastatin and metformin as a promising chemotherapeutic alternative for metastatic CRPC.

MPINet: metabolite pathway identification via coupling of global metabolite network structure and metabolomic profile

High-throughput metabolomics technology, such as gas chromatography mass spectrometry, allows the analysis of hundreds of metabolites. Understanding that these metabolites dominate the study condition from biological pathway perspective is still a significant challenge. Pathway identification is an invaluable aid to address this issue and, thus, is urgently needed. In this study, we developed a network-based metabolite pathway identification method, MPINet, which considers the global importance of metabolites and the unique character of metabolomic profile. Through integrating the global metabolite functional network structure and the character of metabolomic profile, MPINet provides a more accurate metabolomic pathway analysis. This integrative strategy simultaneously captures the global nonequivalence of metabolites in a pathway and the bias from metabolomic experimental technology. We then applied MPINet to four different types of metabolite datasets. In the analysis of metastatic prostate cancer dataset, we demonstrated the effectiveness of MPINet. With the analysis of the two type 2 diabetes datasets, we show that MPINet has the potentiality for identifying novel pathways related with disease and is reliable for analyzing metabolomic data. Finally, we extensively applied MPINet to identify drug sensitivity related pathways. These results suggest MPINet's effectiveness and reliability for analyzing metabolomic data across multiple different application fields.

Feasibility of detecting prostate cancer by ultraperformance liquid chromatography-mass spectrometry serum metabolomics

Prostate cancer (PCa) is the second leading cause of cancer-related mortality in men. The prevalent diagnosis method is based on the serum prostate-specific antigen (PSA) screening test, which suffers from low specificity, overdiagnosis, and overtreatment. In this work, untargeted metabolomic profiling of age-matched serum samples from prostate cancer patients and healthy individuals was performed using ultraperformance liquid chromatography coupled to high-resolution tandem mass spectrometry (UPLC-MS/MS) and machine learning methods. A metabolite-based in vitro diagnostic multivariate index assay (IVDMIA) was developed to predict the presence of PCa in serum samples with high classification sensitivity, specificity, and accuracy. A panel of 40 metabolic spectral features was found to be differential with 92.1% sensitivity, 94.3% specificity, and 93.0% accuracy. The performance of the IVDMIA was higher than the prevalent PSA test. Within the discriminant panel, 31 metabolites were identified by MS and MS/MS, with 10 further confirmed chromatographically by standards. Numerous discriminant metabolites were mapped in the steroid hormone biosynthesis pathway. The identification of fatty acids, amino acids, lysophospholipids, and bile acids provided further insights into the metabolic alterations associated with the disease. With additional work, the results presented here show great potential toward implementation in clinical settings.

Cholesteryl ester accumulation induced by PTEN loss and PI3K/AKT activation underlies human prostate cancer aggressiveness

Altered lipid metabolism is increasingly recognized as a signature of cancer cells. Enabled by label-free Raman spectromicroscopy, we performed quantitative analysis of lipogenesis at single-cell level in human patient cancerous tissues. Our imaging data revealed an unexpected, aberrant accumulation of esterified cholesterol in lipid droplets of high-grade prostate cancer and metastases. Biochemical study showed that such cholesteryl ester accumulation was a consequence of loss of tumor suppressor PTEN and subsequent activation of PI3K/AKT pathway in prostate cancer cells. Furthermore, we found that such accumulation arose from significantly enhanced uptake of exogenous lipoproteins and required cholesterol esterification. Depletion of cholesteryl ester storage significantly reduced cancer proliferation, impaired cancer invasion capability, and suppressed tumor growth in mouse xenograft models with negligible toxicity. These findings open opportunities for diagnosing and treating prostate cancer by targeting the altered cholesterol metabolism.

Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS

Hepatocellular carcinoma (HCC) accounts for most cases of liver cancer worldwide; contraction of hepatitis C (HCV) is considered a major risk factor for liver cancer even when individuals have not developed formal cirrhosis. Global, untargeted metabolic profiling methods were applied to serum samples from patients with either HCV alone or HCC (with underlying HCV). The main objective of the study was to identify metabolite based biomarkers associated with cancer risk, with the long term goal of ultimately improving early detection and prognosis. Serum global metabolite profiles from patients with HCC (n=37) and HCV (n=21) were obtained using high performance liquid chromatography-mass spectrometry (HPLC-MS) methods. The selection of statistically significant metabolites for partial least-squares discriminant analysis (PLS-DA) model creation based on biological and statistical significance was contrasted to that of a traditional approach utilizing p-values alone. A PLS-DA model created using the former approach resulted in a model with 92% sensitivity, 95% specificity, and an AUROC of 0.93. A series of PLS-DA models iteratively utilizing three to seven metabolites that were altered significantly (p<0.05) and sufficiently (FC≤0.7 or FC≥1.3) showed good performance using p-values alone; the best of these PLS-DA models was capable of generating 73% sensitivity, 95% specificity, and an AUROC of 0.92. Metabolic profiles derived from LC-MS readily distinguish patients with HCC and HCV from those with HCV only. Differences in the metabolic profiles between high-risk individuals and HCC indicate the possibility of identifying the early development of liver cancer in at risk patients. The use of biological significance as a selection process prior to PLS-DA modeling may offer improved probabilities for translation of newly discovered biomarkers to clinical application.

Recent Advances in Metabolic Profiling And Imaging of Prostate Cancer

Cancer is a metabolic disease. Cancer cells, being highly proliferative, show significant alterations in metabolic pathways such as glycolysis, respiration, the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, lipid metabolism, and amino acid metabolism. Metabolites like peptides, nucleotides, products of glycolysis, the TCA cycle, fatty acids, and steroids can be an important read out of disease when characterized in biological samples such as tissues and body fluids like urine, serum, etc. The cancer metabolome has been studied since the 1960s by analytical techniques such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Current research is focused on the identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients and distinguish between benign and advanced metastatic forms of the disease. In this review, we discuss the current state of prostate cancer metabolomics, the biomarkers that show promise in distinguishing indolent from aggressive forms of the disease, the strengths and limitations of the analytical techniques being employed, and future applications of metabolomics in diagnostic imaging and personalized medicine of prostate cancer.

Inhibition of the insulin-like growth factor-1 receptor enhances effects of simvastatin on prostate cancer cells in co-culture with bone

Prostate cancer (PC) bone metastases show weak responses to conventional therapies. Bone matrix is rich in growth factors, with insulin-like growth factor-1 (IGF-1) being one of the most abundant. IGF-1 acts as a survival factor for tumor cells and we speculate that bone-derived IGF-1 counteracts effects of therapies aimed to target bone metastases and, consequently, that therapeutic effects could be enhanced if given in combination with IGF-1 receptor (IGF-1R) inhibitors. Simvastatin inhibits the mevalonate pathway and has been found to induce apoptosis of PC cells. The aims of this study were to confirm stimulating effects of bone-derived IGF-1 on PC cells and to test if IGF-1R inhibition enhances growth inhibitory effects of simvastatin on PC cells in a bone microenvironment. The PC-3 and 22Rv1 tumor cell lines showed significantly induced cell growth when co-cultured with neonatal mouse calvarial bones. The tumor cell IGF-1R was activated by calvariae-conditioned media and neutralization of bone-derived IGF-1 abolished the calvarium-induced PC-3 cell growth. Treatment of PC-3 and 22Rv1 cells with simvastatin, or the IGF-1R inhibitor NVP-AEW541, reduced tumor cell numbers and viability, and induced apoptosis. Combined simvastatin and NVP-AEW541 treatment resulted in enhanced growth inhibitory effects compared to either drug given alone. Effects of simvastatin involved down-regulation of IGF-1R in PC-3 and of constitutively active androgen receptor variants in 22Rv1 cells. In conclusion, we suggest that IGF-1 inhibition may be a way to strengthen effects of apoptosis-inducing therapies on PC bone metastases; a possibility that needs to be further tested in pre-clinical models.

Low- and high-grade bladder cancer determination via human serum-based metabolomics approach

To address the shortcomings of urine cytology and cystoscopy for probing and grading urinary bladder cancer (BC), we applied (1)H nuclear magnetic resonance (NMR) spectroscopy as a surrogate method for the identification of BC. This study includes 99 serum samples comprising low-grade (LG; n = 36) and high-grade (HG; n = 31) BC as well as healthy controls (HC; n = 32). (1)H NMR-derived serum data were analyzed using orthogonal partial least-squares discriminant analysis (OPLS-DA). OPLS-DA-derived model validity was confirmed using an internal and external cross-validation. Internal validation was performed using the initial samples (n = 99) data set. External validation was performed on a new batch of suspected BC patients (n = 106) through a double-blind study. Receiver operating characteristic (ROC) curve analysis was also performed. OPLS-DA-derived serum metabolomics (six biomarkers, ROC; 0.99) were able to discriminate 95% of BC cases with 96% sensitivity and 94% specificity when compared to HC. Likewise (three biomarkers, ROC; 0.99), 98% of cases of LG were able to differentiate from HG with 97% sensitivity and 99% specificity. External validation reveals comparable results to the internal validation. (1)H NMR-based serum metabolic screening appears to be a promising and less invasive approach for probing and grading BC in contrast to the highly invasive and painful cystoscopic approach for BC detection.

Review of mass spectrometry-based metabolomics in cancer research

Metabolomics, the systematic investigation of all metabolites present within a biologic system, is used in biomarker development for many human diseases, including cancer. In this review, we investigate the current role of mass spectrometry-based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase, and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case-control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification, or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including less than 100 patients. Standardization is required especially concerning sample preparation and data analysis. In the second part of this review, we reconstructed a metabolic network of patients with cancer by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane, and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed.