Univariate statistical analyses of the results obtained in urine amino acid profiling were performed analogously to those regarding Rubber craft material samples and also allowed to indicate which variables had different levels in samples obtained from prostate cancer patients compared to healthy men. Biomed Chromatogr. Several methods for amino acid determination have been applied, including cation-exchange liquid chromatography followed by post-column derivatization with ninhydrin and UV detection, reversed-phase high performance liquid chromatography Prostatee UV or fluorescence detection following pre-column derivatization 2223high performance liquid chromatography-electrospray Oswald wife spectrometry 24Prostate supplements amino acid performance liquid chromatography-electrospray ionization-tandem mass spectrometry 25 - 27gas chromatography-electron impact ionization-mass spectrometry 28 and capillary electrophoresis-electrospray ionization-tandem mass spectrometry Forward stepwise discriminant function analysis for urine was performed using the training and test sets of the same size as for serum. Side effects are mild and reversible and may include stomach upset, headache, fatigue, and decreased libido. This article sulplements been cited by other Prostafe in PMC. Cruciferous vegetables are legendary for their health benefits and their reputation for health building rests largely on acod therapeutic powers of DIM.
Adult massage noida. Background information, citation, abstract and about the author
Share your thoughts Prostate supplements amino acid comments about this topic in the space below. The capsules do not contain starch, sodium, gluten, sugar, artificial colors, or preservatives. The supplsments has been rated as a top prostate supplement and only contains clinically tested ingredients that are sourced from nature. The models were validated on Prostage remaining one third of the samples. Saini S. You can also read plenty of customer testimonials on the Prostarelief website to help you aminl more insight into how this product works. Other ingredients in Prostara are selenium, Saw palmetto, lycopene, pumpkin seed powder, soy isoflavones, and more. The results of discriminant function analysis for amino acid concentrations in urine samples showed the effectiveness of amino acids in predicting group membership. Biomed Chromatogr. Ann Intern Med. MetaboAnalyst 3.
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- There is a great interest in searching for diagnostic biomarkers in prostate cancer patients.
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Researchers at the Centenary Institute in Sydney have discovered a potential future treatment for prostate cancer—through starving the tumour cells of an essential nutrient they need to grow rapidly. Their work, with human cells grown in the lab, reveals targets for drugs that could slow the progress of early and late stage prostate cancer. Each year about Australian men die of prostate cancer.
Current therapies for prostate cancer include surgical removal of the prostate, radiation, freezing the tumour or cutting off the supply of the hormone testosterone—but there are often side-effects including incontinence and impotence.
Growing cells need an essential nutrient, the amino acid called leucine, which is pumped into the cell by specialised proteins. This allows the cancer cells to take in more leucine and outgrow normal cells. We found that we could disrupt the uptake of leucine firstly by reducing the amount of the protein pumps, and secondly by introducing a drug that competes with leucine.
First author Dr Qian Wang says by targeting different sets of pumps, the researchers were able to slow tumour growth in both the early and late stages of prostate cancer. Our hope is that we could develop a treatment that slows the growth of the cancer so that it would not require surgical removal.
Jeff says one of the other spin-offs of the discovery is a better understanding of the links between prostate cancer and eating foods high in leucine. We have already begun examining whether these pumps can explain the links between diet and prostate cancer. We strongly support innovative targeted research that leads to significantly improved clinical tests and treatments to reduce the burden of prostate cancer. PCFA and Movember have been working together since to reduce the impact of prostate cancer on Australian men and their loved ones.
Prostate cancer is the most common cancer in Australian men and is the second most common cause of cancer deaths in men after lung cancer. Generally at the early and potentially curable stage, prostate cancer does not have obvious symptoms. This makes it different from other benign prostate disorders, which may result in urinary symptoms. Men aged 50 and over should talk to their doctor about prostate cancer and if they decide to be tested, to do so annually.
If there is a family history of prostate cancer; men should talk to their doctor from the age of These responses are intact in primary prostate cancer, as indicated by high levels of LAT3 in primary disease, and an increase in LAT1 following hormone ablation and in metastatic lesions.
These data show that prostate cancer cells respond to the demand for increased amino acids through an integrated pathway, leading to increased amino acid transporter expression and cell growth. The Prostate Cancer Foundation of Australia PCFA have been partners of Movember since and together are working towards a shared goal of reducing the impact of prostate cancer on Australian men and their loved ones.
Together, Movember and the PCFA are dedicated to funding Australian research into the cause, diagnosis, prevention and treatment of prostate cancer; providing information, support and advocacy to those affected by prostate cancer and raising community awareness about prostate cancer.
PCFA receives limited government funding, instead relying on the generosity of the Movember community, and partners like Movember to provide and grow its vital services across Australia. Credit: Centenary Institute".
Late stage prostate cancer cells showing the nucleus in blue, and the nutrient pump on the surface of the cells in green. Credit: Centenary Institute. WP Admin. Prostate cancers are hungry, growing cells. Now we know how to cut off their food supply thanks to research to be published later this month in Cancer Research— work funded by Movember and the Prostate Cancer Foundation of Australia Researchers at the Centenary Institute in Sydney have discovered a potential future treatment for prostate cancer—through starving the tumour cells of an essential nutrient they need to grow rapidly.
Background information Citation and link to paper Images Each year about Australian men die of prostate cancer.
Starving cancer and other stories. Heart cells growing in a test tube.
Since the number of samples analyzed in our study is limited 49 prostate cancer patients and 40 controls , it should be considered as a pilot study. The product is very affordable, especially when compared to some of the other prostate supplements that are currently available on the market. Clin Cancer Res. Other than the essential ingredients found in almost every prostate supplement, Prostalieve also contains Maitake mushroom, Reishi mushroom, and shitake mushroom extracts which studies show contain anti-inflammatory and immunomodulation compounds . The whole procedure was repeated multiple times. These two ingredients include organic saw palmetto berries and organic pumpkin seed oil. It can be suggested that while searching for serum prostate cancer biomarkers special attention should be paid to the following compounds: methionine, ethanolamine, glutamine, isoleucine, arginine and leucine, among which ethanolamine is a non-proteinogenic compound.
Prostate supplements amino acid. We Have The Answers You're Looking For
The model obtained was validated with permutation tests. In order to do it, the whole analysis was repeated times but with random group labels. Then the results were compared with those for proper labels.
VIP scores for 15 amino acids with the highest contribution of to the separation of the studied groups are presented. The boxes on the right refer to the relative concentrations of the appropriate amino acid in the studied groups.
The performed forward stepwise discriminant function analysis involved step-by-step building of a discrimination model. Only part of the samples were used to build the model, randomly chosen from the studied groups. Those samples constituted a training set, which consisted of 30 samples of the prostate cancer group and 25 samples of the control group, representing The remaining samples 19 samples of the prostate cancer group and 15 samples of the control group constituted a test set, used for the external validation of the model.
The results of discriminant function analysis for amino acid concentrations in serum samples demonstrated that the set of predictors was effective in predicting group membership. The sensitivity and specificity values for the model were calculated based on the post-hoc classification matrix. The model correctly predicted the presence of prostate cancer in the case of 13 of 19 patients with diagnosed tumor in the test set sensitivity of Overall, the health status was correctly predicted in the case of 28 of 34 participants in the test set total group membership classification value of The utility of free amino acid profiles in the classification of the study participants was also analyzed using multivariate ROC curve analyses.
For each model, two thirds of the samples were used to assess the importance of the features amino acids. Then, the most important features were used to generate classification models. In the case of serum, 2, 3, 5, 10, 20 and 32 features were used, resulting in six models for that physiological fluid.
The models were validated on the remaining one third of the samples. The whole procedure was repeated multiple times. The results indicated that the frequency with which the variables appeared in the models corresponded to the VIP scores for these variables obtained in PLS-DA. A clear trend can be observed that ROC curves built using higher number of variables lie closer to the 0,1 point of the coordinate system, which is also reflected in the increasing AUC: from 0. Thus, the more variables in the model, the better the classification model was.
The results correspond to those obtained by comparing the AUC and ROC curve shapes: predictive accuracy increased with the higher number of variables: from Predictive accuracies obtained for serum and urine for models built using various number of variables in multivariate ROC curve analyses. According to additional PLS-DA of amino acid levels in serum, there were no significant differences in amino acid profiles between patients representing various Gleason scores.
Free amino acid profiles in urine samples were obtained for the same study participants and using the same method as free amino acid profiles in serum samples.
In the case of urine samples, 39 amino acids were quantified in all samples and their concentrations were subjected to consecutive statistical analyses. Univariate statistical analyses of the results obtained in urine amino acid profiling were performed analogously to those regarding serum samples and also allowed to indicate which variables had different levels in samples obtained from prostate cancer patients compared to healthy men. Statistically significant differences in the concentrations of urinary sarcosine between the group of prostate cancer patients and the control group were not observed.
The results of univariate ROC curve analyses indicated that in the case of urine, 9 amino acids with high AUC above 0. Forward stepwise discriminant function analysis for urine was performed using the training and test sets of the same size as for serum.
The results of discriminant function analysis for amino acid concentrations in urine samples showed the effectiveness of amino acids in predicting group membership.
The sensitivity and specificity in the test set were Multivariate ROC curve analyses for amino acid profiles in urine were also performed, analogously as in the case of serum. In the case of urine, 2, 3, 5, 10, 20 and 39 most important features were used to generate classification models, resulting in six models for that biofluid. Predictive accuracy increased with the higher number of variables: from Additional PLS-DA of amino acid levels in urine was performed in order to see whether there were differences in amino acid profiles between patients representing various Gleason scores.
Similarly, as in the case of serum, no significant differences were observed. The performed pilot study confirmed that amino acids represent a group of metabolites which has a high potential of use as prostate cancer biomarkers and can improve prostate cancer screening.
The article is the first which presents the comprehensive analysis of a wide panel of amino acids in two different body fluids obtained from the same groups of prostate cancer patients and healthy men. Till now, only results on determination of selected amino acids in a given body fluid of prostate cancer patients have been published. In the earlier studies, the maximum number of quantified amino acids in the selected biofluid taken from prostate cancer group was 19 and those studies were usually focused on proteinogenic amino acids 16 - 18 , However, the example of sarcosine indicated that non-proteinogenic amino acids can also play a role in prostate cancer pathogenesis and may contribute to improvement of its detection.
The above-mentioned studies are examples of targeted analyses. Prostate cancer has been also studied using metabolomic profiling in order to have an insight into the entire measurable metabolome 10 , 14 , 21 , 32 - Multiple metabolites were identified in such untargeted approach, including many amino acids. We decided to focus on targeted analysis of amino acids in order to collect information on concentrations of metabolites of that group in prostate cancer.
Since the number of samples analyzed in our study is limited 49 prostate cancer patients and 40 controls , it should be considered as a pilot study. However, in the case of 1- and 3-methylhistidine we cannot exclude the possibility that levels of those two metabolites are related to differences in meat consumption between the prostate cancer group and the control group, even though both groups were sharing a similar lifestyle.
Urinary excretion of 1- and 3-methylhistidine was found elevated with increasing meat intake by Cross et al. The obtained results proved that prostate cancer causes noticeable changes in free amino acid profiles in serum and urine.
In addition, more compounds were present at significantly altered levels in urine comparing to serum. Amino acid concentrations in serum were correlated with concentrations of the appropriate compounds in urine to a high extent: in the case of 24 of 32 amino acids quantified in both body fluids the increase or decrease of level of the given metabolite in serum of prostate cancer patients compared with the control group was associated with the same change of level of that metabolite in urine.
The results obtained allow to propose future directions of research. It can be suggested that while searching for serum prostate cancer biomarkers special attention should be paid to the following compounds: methionine, ethanolamine, glutamine, isoleucine, arginine and leucine, among which ethanolamine is a non-proteinogenic compound. It should be considered that biomarker does not have to be a single compound.
It is hoped that a multi-compound panel of markers can improve diagnosis of prostate cancer. It is based on a panel of four amino acids: sarcosine, alanine, glycine and glutamic acid quantified using liquid chromatography-mass spectrometry and its aim is to increase confidence in deciding whether to perform the prostate biopsy. Based on the performed multivariate statistical analyses it was demonstrated that abnormalities in amino acids profiles caused by the presence of prostate cancer are useful in classification of prostate cancer patients and healthy men with high sensitivity and specificity, both in serum and urine.
Results of discriminant function analyses indicated that higher sensitivity was achieved for the model built using amino acid concentrations in urine samples However, the total group membership classification values for serum and urine samples were the same However, in the case of higher number of variables in the models, predictive accuracies of urine amino acid profiles were higher than of serum amino acid profiles. In conclusion, it is hard to say which of the body fluids would benefit more in terms of classification parameters in screening for prostate cancer.
In addition, the obtained results of AUC demonstrated that the achieved classification was better than in the case of research of Miyagi et al. They discovered significant differences in the plasma amino acid profiles between prostate cancer patients and healthy controls which allowed to discriminate the two groups using multivariate ROC curve analysis with AUC of 0.
In our study AUC value obtained for 2 variables was 0. Based on the results of the presented studies the role of the non-proteinogenic amino acid sarcosine as a potential prostate cancer biomarker has been rejected. This may suggest its utility as the marker of prostate cancer. Multiple other amino acids had higher ability to discriminate samples and thus are better candidates for prostate cancer biomarkers.
Still, the results obtained for sarcosine in serum samples suggest its role in etiology of prostate cancer. It means that sarcosine has to be rejected as urinary biomarker of prostate cancer.
Although it was shown in by Sreekumar et al. Leucine, isoleucine and valine constitute a group of branched-chain amino acids BCAA. Our findings on lower concentrations of BCAA in biofluids of the prostate cancer group are consistent with results of Miyagi et al. The results of our study suggest that BCAA metabolic pathways can be a valuable source of diagnostic and prognostic markers for prostate cancer.
The difference in the level of ethanolamine was one of the most statistically significant among all measured metabolites, both in serum and urine. In fact, ethanolamine is not an amino acid, but a primary amine and a primary alcohol. That compound is one of the main precursors and degradation products of the phospholipid membrane.
Swanson et al. They analyzed prostate tissues and observed that in the case of prostate cancer the concentration of ethanolamine was significantly lower. Since ethanolamine, ethanolamine-containing metabolites and other phospholipid membrane precursors contain the information about various processes occurring in the organism cellular proliferation, apoptosis, activity of enzymes , there is an interest in correlating them with the presence and aggressiveness of cancer, as well as with the response to treatment Together with ethanolamine, arginine was another compound, for which in both serum and urine the levels differed the most significantly among other metabolites.
Arginine is used not only in protein synthesis, but is also involved in urea cycle, biosyntheses of creatine, polyamine, and serves as a crucial substrate for enzymes such as the nitric oxide NO synthases 42 , As the nitrogen donor in NO synthesis, arginine is linked to inflammation processes, neurotransmission and vasodilation.
For that reasons, NO is known to play a role in cancer Significant decrease in arginine concentration in body fluids of patients with prostate cancer may result from both decrease in arginine synthesis and increase in its degradation. The first process is probably due to down-regulation of ornithine carbamoyl transferase in cancer tissue On the other hand, increase in arginine degradation leads to NO production and may contribute to NO-dependent vasculature of prostate cancer tissue, growth of tumor, metastasis and poor prognosis of the disease The change of arginine levels in biofluids suggests its role in pathogenesis of prostate cancer and it is also in concordance with results of Miyagi et al.
Depletion of arginine is a promising anti-cancer treatment strategy and recombinant human arginase has been tested for arginine deprivation therapy in cancer.
It was demonstrated by Hsueh et al. The presented pilot study is the first comprehensive analysis of a wide panel of 42 proteinogenic and non-proteinogenic amino acids in two different physiological fluids obtained from the same groups of prostate cancer patients and healthy men. While sarcosine was rejected as a marker of prostate cancer, other metabolites were indicated which deserve special attention in searching for new prostate cancer biomarkers, many of which belong to non-proteinogenic amino acids.
The presented research provides a strong evidence that ethanolamine, arginine and BCAA metabolic pathways can be a valuable source of markers for prostate cancer. The altered concentrations of the above-mentioned metabolites suggest its role in pathogenesis of prostate cancer and should be further evaluated as clinically useful markers of prostate cancer.
National Center for Biotechnology Information , U. Int J Med Sci. Published online Jan 1. Find articles by Agnieszka Klupczynska. Find articles by Wojciech Sawicki. Jerzy A. Find articles by Jerzy A.
Zenon J. Find articles by Zenon J. Author information Article notes Copyright and License information Disclaimer. Kokot, Ph. Competing Interests: The authors have declared that no competing interest exists. Received Apr 8; Accepted Oct This article has been cited by other articles in PMC. Associated Data Supplementary Materials Supplementary table. Abstract There is a great interest in searching for diagnostic biomarkers in prostate cancer patients. Keywords: prostate cancer, amino acids, metabolomics, serum, urine.
Introduction Prostate cancer is one of the most frequently diagnosed cancers and one of the main causes of death due to tumors in men 1 - 3. Table 1 Characteristics of the prostate cancer group and the control group. Prostate cancer Controls No. Open in a separate window.
Data processing and statistical analyses Statistical analyses were performed using Statistica Univariate statistical analyses The performed univariate statistical analyses allowed to indicate which variables amino acids had different levels in samples obtained from prostate cancer patients compared to the control group.
Figure 1. Multivariate statistical analyses The results of univariate statistical analyses suggest that patients with prostate cancer and healthy men can be discriminated using multivariate statistical analyses, which involve set of variables at least two simultaneously and aim to search for patterns and relationships between variables in order to create the best classification and discrimination models.
Figure 2. Figure 3. Table 4 Predictive accuracies obtained for serum and urine for models built using various number of variables in multivariate ROC curve analyses. Univariate statistical analyses Univariate statistical analyses of the results obtained in urine amino acid profiling were performed analogously to those regarding serum samples and also allowed to indicate which variables had different levels in samples obtained from prostate cancer patients compared to healthy men.
Discussion The performed pilot study confirmed that amino acids represent a group of metabolites which has a high potential of use as prostate cancer biomarkers and can improve prostate cancer screening. Conclusions The presented pilot study is the first comprehensive analysis of a wide panel of 42 proteinogenic and non-proteinogenic amino acids in two different physiological fluids obtained from the same groups of prostate cancer patients and healthy men.
Supplementary Material Supplementary table. Click here for additional data file. References 1. Prostate cancer - a biomarker perspective. Front Endocrinol Lausanne ; 3 Global cancer statistics. CA Cancer J Clin. Prostate cancer genomics, biology, and risk assessment through genome-wide association studies.
Cancer Sci. Postma R, Schroder FH. Screening for prostate cancer. Eur J Cancer. Pavlou M, Diamandis EP. Question: I take warfarin Coumadin , an anticoagulant drug.
Are there supplements I should avoid, or be taking, due to this drug? Answer: Yes, the effectiveness of warfarin Coumadin , anisindione Miradon and other anticoagulant drugs prescribed to help prevent blood clots can be impacted by taking supplements. This is discussed in detail in the Warfarin article, which is part of the extensive Drug Interactions section of our website where you can look up interactions for other drugs you may be taking.
CoQ10 is chemically similar to vitamin K 2 and may also decrease the effects of warfarin, although the evidence for this is mixed. Because it can be affected by a large number of herbs, supplements and foods, it's important to consult your physician before taking any supplement with warfarin. The coumadin is adusted to my diet and the way to accomplish this is to be consistant with what I eat.
I have to take a larger does of counadin to offset my green leaf salads and vitimin K intake then someone else who dies not take vit K and eat greens. I wish this was standard practice. Of course no medication should be stopped cold turkey due to possible 'rebound' effects, and for this reason should only be done gradually, under a physician's supervision. No problem, also eat broccoli, kale, and spinach. Share your thoughts and comments about this topic in the space below. Please abide by the following rules: If you make a statement of fact, such as whether a type of treatment does or does not work, state your basis -- such as personal experience or a published study.
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Proteins that deliver leucine to prostate cancer cells are therapeutic targets -- ScienceDaily
Controlled amino acid therapy CAAT is a protocol developed for patients with cancer that includes strict dietary guidelines and nutritional supplements that focus on controlling amino acid and carbohydrate intake. The protocol was developed by the A. John Institute for Cancer Research and is touted to be based on extensive clinical research, but studies in humans or animal models of the entire CAAT protocol have not been published, nor have results — case studies or observational studies — from the institute been published.
The exact protocol is not reported and the website for the institute is no longer functioning. Components of the protocol, such as selective amino acid restriction, and supplements such as vitamin D and antioxidants, have been studied separately in vitro and in some animal models. This fact sheet focuses on the amino acid deprivation component. A major component of CAAT is selective amino acid restriction therapy SAART , which is based on the hypothesis that many cancer cells develop mutations that prevent the synthesis of some amino acids that are required for protein synthesis and thus continued cell survival.
When these cancer cells are deprived of an exogenous source of these amino acids, the cell cannot perform protein synthesis and thus is unable to survive. It has sbeen proposed that temporary selective deprivation of amino acids may result in the death of cancer cells without affecting normal cells or causing muscle proteolysis.
This hypothesis has not, however, been fully tested in vivo, but is based on observations from studies of single amino acid deprivation and overall protein restriction in vitro and in vivo.
Findings from one study suggest that a substantial decrease in overall protein intake inhibits cell proliferation in castration-resistant prostate cancer cells and amino acid starvation culture conditions ie, amino acids not present in culture medium combined with gefitinib resulted in cytotoxicity of EGFR -expressing cancer cell lines.
Decreased protein intake also inhibited tumor growth, but did not affect body weight, in a xenograft mouse model of human breast cancer.
Many internet sites claim that CAAT has been studied in clinical trials. These trials, however, evaluated only the amino acid deprivation portion of the protocol and only in very small, single-arm studies. One study conducted in the s, for example, evaluated 5 patients with metastatic melanoma who consumed a diet restricted in phenylalanine and tyrosine. Four of the patients experienced slowed tumor growth, which also correlated with lower levels of serum phenylalanine and tyrosine.
The authors concluded that the diet appeared to inhibit tumor growth, but was difficult for patients to follow. Login Register. Popular Emailed Recent Loading Please login or register first to view this content.
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