Trace elements analysis of ascitic fluid in benign and malignant diseases

Copper content in ascitic fluid is associated with angiogenesis and progression in ovarian cancer

BACKGROUND

Ascites is associated with the poor prognosis of malignant tumors. The biological importance of the changes in the content of trace elements in the ascitic fluid is unknown. Herein, we analyzed trace elements in the ascitic fluid of patients with ovarian tumors and used cultured cells to determine the copper (Cu)-induced changes in gene expression in ovarian cancer.

METHODS

Inductively coupled plasma mass spectrometry (ICP-MS) was used to compare ascitic fluid trace element levels in patients with benign ovarian tumors (n = 22) and borderline/malignant tumors (n = 5) for primary screening. Cu levels were validated using atomic absorption spectrometry (AAS) in 88 benign, 11 borderline, and 25 malignant ovarian tumor patients. To confirm Cu-induced gene expression changes, microarray analysis was performed for Cu-treated OVCAR3, A2780, and Met5A cells. The vascular endothelial growth factor (VEGF) concentration in the cell supernatant or ascitic fluid (ovarian cancer samples) was measured using ELISA.

RESULTS

ICP-MS showed that Co, Ni, Cu, Zn, As, Se, and Mo levels significantly increased in patients with malignant/borderline ovarian tumors compared to those in patients with benign ovarian tumors. AAS showed that malignant ovarian tumors were independently associated with elevated levels of Cu in ascites adjusted for age, body mass index, alcohol, smoking, and supplement use (p < 0.001). Microarray analysis of both Cu-treated ovarian cancer cell lines OVCAR3 and A2780 and the mesothelial cell line Met-5A revealed the upregulation of the angiogenesis biological process. Real-time polymerase chain reaction and ELISA demonstrated that an increased Cu content significantly enhanced VEGF mRNA expression and protein secretion in OVCAR3, A2780, and Met-5A cells. VEGF levels and clinical stages of the tumors correlated with the ascitic fluid Cu content in patients with malignant ovarian tumors (correlation coefficient 0.445, 95 % confidence interval [CI]: 0.069-0.710, p = 0.023 and correlation coefficient 0.406, 95 % CI: 0.022-0.686, p = 0.040, respectively).

CONCLUSION

Cu levels significantly increased in patients with malignant ovarian cancer. Cu induced angiogenic effects in ovarian cancer and mesothelial cells, which affected ascites fluid production. This study clarifies the link between elevated Cu in ascites and malignant ovarian tumor progression. Strategies to decrease Cu levels in the ascitic fluid may help downregulate VEGF expression, thereby improving the prognosis of ovarian malignancies.

The effect of zinc and phytoestrogen supplementation on the changes in mineral content of the femur of rats with chemically induced mammary carcinogenesis

The aim of this study was to assess skeletal effects of zinc or zinc with phytoestrogen (resveratrol or genistein) supplementation in an animal model of rats with DMBA-induced mammary carcinogenesis. The changes in bone parameters such as the length and mass were examined, as well as the changes in concentrations of selected minerals: calcium, magnesium, zinc, iron and phosphorus. Moreover, the investigations focused on finding the differences between the levels of iron and zinc in other tissues: the liver, spleen and serum of the examined rats. Fifty-six female Sprague-Dawley rats, 40 days old, were divided into four groups, regardless of the diets: standard (77mg Zn kg/food), zinc (4.6mg/mL via gavage), zinc (4.6mg/mL) plus resveratrol (0.2mg/kgbw), and zinc (4.6mg/mL) plus genistein (0.2mg/kgbw) for a period from 40 days until 20 weeks of age. The study rats were also treated with 7,12-dimethyl-1,2-benz[a]anthracene (DMBA) to induce mammary carcinogenesis. The applied diet and the advanced mammary cancer did not affect macrometric parameters of the rats' bones, but they strongly affected their mineral content. It was found that mammary cancer, irrespectively of the applied diet, significantly modified the iron level in the femur, liver, spleen and serum of the examined rats. In addition, zinc supplementation significantly lowered the levels of calcium, magnesium and phosphorus in the femur of rats with mammary cancer as compared with respective levels in the control group. So, it was found that additional supplementation with zinc, which is generally considered to be an antioxidant, with the co-existing mammary carcinoma, increased the unfavorable changes as concerns the stability of bone tissue. The appropriate combination of zinc and phytoestrogens (resveratrol or genistein) could help prevent or slow bone loss associated with a range of skeletal disorders in breast cancer.

Design of an expert system for mitigating trace element toxicity in cancer risk management

Cancer risk management involves obliterating excess concentration of cancer causing trace elements by the natural immune system and hence intake of nutritious diet is of paramount importance. Human diet should consist of essential macronutrients that have to be consumed in large quantities and trace elements are to be consumed in very little amount. As some of these trace elements are causative factors for various types of cancer and build up at the expense of macronutrients, cancer risk management of these trace elements should be based on their initial concentration in the blood of each individual and not on their tolerable upper intake level. We propose an information theory based Expert System (ES) for estimating the lowest limit of toxicity association between the trace elements and the macronutrients. Such an estimate would enable the physician to prescribe required medication containing the macronutrients to annul the toxicity of cancer risk trace elements. The lowest limit of toxicity association is achieved by minimizing the correlated information of the concentration correlation matrix using the concept of Mutual Information (MI) and an algorithm based on a Technique of Determinant Inequalities (TDI) developed by the authors. The novelty of our ES is that it provides the lowest limit of toxicity profile for all trace elements in the blood not restricted to a group of compounds having similar structure. We demonstrate the superiority our algorithm over Principal Component Analysis in mitigating trace element toxicity in blood samples.

Prediction of type-2 diabetes based on several element levels in blood and chemometrics

The present study was designed to evaluate the levels of eight elements including lithium, zinc, chromium, copper, iron, manganese, nickel and vanadium in whole blood of type-2 diabetes patients, to compare them with age-matched healthy controls and to investigate the feasibility of combining them with an ensemble model for diagnosing purpose. A dataset involving 158 samples, among which 105 were taken from healthy adults and the remaining 53 from patients with type-2 diabetes, was collected. All samples were split into the training set and the test set with the equal size. Based on a simple variable selection, two elements, i.e., chromium and iron, are also picked out as the most important elements. Three kinds of algorithms, i.e., fisher linear discriminate analysis (FLDA), support vector machine (SVM) and decision tree (DT), were used for constructing member models. The best ensemble classifiers constructed on the training set were validated on the independent test set, and the prediction results were compared with those from clinical diagnostics on the same subjects. The results reveal that almost all ensemble classifiers exhibit similar performance, implying that these elements coupled with an appropriate ensemble classifier can serve as a valuable tool of diagnosing diabetes type-2.

Determination of trace elements in anti-influenza virus mushrooms

We have determined the trace element composition of anti-influenza virus mushrooms using atomic absorption spectrophotometer. The elements present in greater concentration in Ganoderma lucidum samples are selenium, iron, and zinc, with selenium being the element with the highest concentration of all, at 416 ± 38.5 mg/kg; in Cordyceps militaris samples are iron, selenium, and zinc, with iron being the element with the highest concentration of all, at 291 ± 20.9 mg/kg; in Kuehneromyces mutabilis samples are selenium, iron, and manganese, with selenium being the element with the highest concentration of all, at 203 ± 9.8 mg/kg; in Inonotus hispidus samples are zinc, selenium, and iron, with zinc being the element with the highest concentration of all, at 194 ± 16.9mg/kg; in the Collybia maculata samples are iron, selenium, and zinc, with iron being the element with the highest concentration of all, at 274 ± 22.2 mg/kg, respectively. The average metal concentrations in mushrooms decreases in the order: selenium > iron > zinc > chromium > manganese > copper > magnesium > lead. After the mice were administered (orally) with mushroom extracts for 8 weeks and inoculated intranasally with viral suspension, element levels in serum were also measured. Highly significantly increased values of Se, Zn, and Mg in the serum of mice supplemented with anti-influenza virus mushrooms were a characteristic finding. Se, Zn, and Mg present in mushrooms may play a direct or indirect role in their anti-influenza virus nature. They may provide prophylactic protection against influenza infection via stimulation of host innate immune response.

Screening of prostate cancer by analyzing trace elements in hair and chemometrics

Prostate cancer is the most common non-cutaneous malignancy and second leading cause of cancer mortality in men. The principle goal of this study was explore the feasibility of applying boosting coupled with trace element analysis of hair, for accurately distinguishing prostate cancer from healthy person. A total of 113 subjects containing 55 healthy men and 58 prostate cancers were collected. Based on a special index of variable importance and a forward selection scheme, only nine elements (i.e., Zn, Cr, Mg, Ca, Al, P, Cd, Fe, and Mo) were picked out from 20 candidate elements for modeling the relationship. As a result, an ensemble classifier consisting of only eight decision stumps achieved an overall accuracy of 98.2%, a sensitivity of 100%, and a specificity of 96.4% on the independent test set while all subjects on the training set are classified correctly. It seems that integrating boosting and element analysis of hair can serve as a valuable tool of diagnosing prostate cancer in practice.

Serum trace element levels in tuberculous pleurisy

In this study, copper, zinc, magnesium, manganese, selenium, and iron were measured by inductively coupled plasma atomic emission spectrophotometry in patients with tuberculous (TB) pleurisy (n = 24) and in the control group (n = 20). Selenium, magnesium, and zinc were found to be significantly lower in TB pleurisy cases than those in the control group (p < 0.01, p < 0.001, and p < 0.001, respectively). There was no significant difference in the value of manganese and iron between TB pleurisy and the control group (p > 0.05). Copper levels were significantly increased in the serum of the patients (p < 0.0001). These results may provide an additional disease correlate for assessing TB pleurisy risk.

Value of combined detection of AFU and TCH in differential diagnosis between malignant and non-tuberculous benign ascites

The purpose of this study was to accurately evaluate the diagnostic efficacy of combined detection of ascitic fluid alpha-L-fucosidase (AFU) and cholesterol (TCH) compared with that of their individual detection. We assayed ascitic AFU activity by colorimetry and TCH level by CHOD-PAP method simultaneously in all 213 cases. Then, we assessed the value of combined detection of AFU and TCH activities with receiver operating characteristic curve (ROC curve), including diagnostic sensitivity, specificity, diagnostic accuracy, positive predict value(PV+), negative predict value(PV-) to see whether these two ascitic fluid biochemical examinations might help in differential diagnosis between malignant and non-tuberculous benign ascites. The mean values of AFU and TCH in malignant group [(164.96 ± 87.72) μmol/lh and (1.65 ± 1.00) mmol/l, respectively] were significantly higher than those in non-tuberculous benign group [(104.02 ± 62.08) μmol/lh and (0.69 ± 0.58) mmol/l, respectively] (P < 0.01). The optimal cutoff value of 101.95 μmol/lh for ascitic AFU and 1.04 mmol/l for ascitic TCH resulted in a diagnostic sensitivity of 82.3% and 70.8%, specificity of 63.2 and 83.8%, accuracy of 72.8 and 77.9%, PV+ of 65.3 and 78.2%, PV- of 83.1 and 77.8%, respectively. Combined detection of the two markers, the sensitivity, specificity, accuracy, PV+ and PV- were 86.5, 85.5, 85.9, 83.0, and 88.5%, respectively. Through comparison by Pearson Chi-square, the combined detection of AFU and TCH produced better diagnostic accuracy (85.9%) compared with the individual detection (P < 0.05). The combined detection of AFU and TCH produced better diagnostic accuracy in comparison with their individual detection, which is helpful to differential diagnosis between malignant and non-tuberculous benign ascites that may be relatively ideal markers to fit for clinical application in local hospitals.

The prediction of cardiovascular disease based on trace element contents in hair and a classifier of boosting decision stumps

The early discovery of cardiovascular disease (CVD) is crucial for performing successful treatments. This study aims at exploring the feasibility of Adaboost (ensemble from machining learning) using decision stumps as weak classifier, combined with trace element analysis of hair, for accurately predicting early CVD. A total of 124 hair samples composed of two groups of samples (one is healthy group from 100 healthy persons aged 24-72 while the other is patient group from 24 cardiovascular disease patients aged 36-81) were used. Nine kinds of trace elements, i.e., chromium (Cr), manganese (Mn), cadmium (Cd), copper (Cu), zinc (Zn), selenium (Se), iron (Fe), aluminum (Al), and nickel (Ni), were selected. In a preliminary analysis, no obvious linear correlations between elements can be observed and the concentration of Cr, Fe, Al, Cd, Ni, or Se for healthy group is higher than that for patient group while the opposite is true for Mn, Cu, or Zn, indicating that both low Se/Fe and high Mn/Cu can be identified as major risk factors. Based on the proposed approach, the final ensemble classifier, constructed on the training set and contained only four decision stumps, achieved an overall identification accuracy of 95.2%, a sensitivity of 100% and a specificity of 94% on the independent test set. The results suggested that integrating Adaboost and trace element analysis of hair sample can serve as a useful tool of diagnosing CVD in clinical practice.

Early prediction of lung cancer based on the combination of trace element analysis in urine and an Adaboost algorithm

Early detection of cancer is the key to effective treatment and long-term survival. Lung cancer is one of the most frequently occurring cancers and its early detection is particularly of interest. This work investigates the feasibility of a combination of Adaboost (ensemble from machining learning) using decision stumps as weak classifier and trace element analysis for predicting early lung cancer. A dataset involving the determination of 9 trace elements of 122 urine samples is used for illustration. Kennard and Stone (KS) algorithm coupled with an alternate re-sampling was used to realize sample set partitioning. The whole dataset was split into equally sized training and test set, which were then reversed to yield a second operating case, we called them case A and case B, respectively. The prediction results based on the Adaboost were compared with those from Fisher discriminant analysis (FDA). On the test set, the final Adaboost classifiers achieved a sensitivity of 100% for both cases, a specificity of 93.8%, 95.7%, and an overall accuracy of 95.1%, 96.7%, for case A and case B, respectively. In either case, Adaboost always achieves better performance than FDA; also, it is less sensitive to the composition of the training set compared to FDA and easy to control over-fitting. It seems that Adaboost is superior to FDA in the present task, indicating that integrating Adaboost and trace element analysis of urine can serve as a useful tool for diagnosing early lung cancer in clinical practice.

Ultraviolet influence on catalase activity and mineral content in eyeballs of gibel carp (Carassius auratus gibelio)

UV radiation present in the environment may induce several eye disorders including inflammation and cataract. The aim of this work was to study catalase activity and Mg, Cu, Ca and Zn contents in the eyeballs of gibel carp exposed to ecologically relevant doses of UV radiation (0.09 kJ/m2 for UV-A and 0.98 kJ/m2 for UV-B) simulated in laboratory conditions. Ultraviolet exposure resulted in significant reduction of catalase activity in the eyeballs of tested fish. Reductions in Mg, Cu and Ca contents after UV exposure were also observed. The differences in Mg and Cu levels between control and UV exposed animals were statistically significant, whereas the reduction of Ca level was insignificant. Zinc level in the eyeballs of UV-exposed fish was significantly higher than in non-irradiated specimens. The results suggest that ultraviolet radiation affects prooxidant/antioxidant balance and Mg, Cu, Zn contents in the eyes of fish living in shallow habitats. These may lead to cataract formation.

Study on the relationship between intake of trace elements and breast cancer mortality with chemometric methods

Several chemometric methods were employed to survey the interaction among the trace elements and the relationship between the intake of these elements and the breast cancer mortality. It is indicated that there are strong interactions among the trace elements so as to form a dynamic balance; the intake of Cr is the most important factor that could cause the increase of breast cancer mortality; no definite relation can be observed between the intake of Cu and that of Zn. However, either the ratio of the intake of Cu and that of Zn or the intake of Cd could show a certain state of dynamic balance among some of the trace elements. Comparison of the analytical methods reveals that it is important to select a suitable method so as to obtain the most appropriate explanation.

Serum levels of antioxidant vitamins, copper, zinc and magnesium in children with chronic rhinosinusitis

Reactive oxygen species including hydroxyl radicals, superoxide anions and hydrogen peroxide which are produced by activated granulocytes play an essential role in many biochemical processes and diseases. Oxidant-mediated tissue damage may be important in the development of chronic sinusitis. The aim of this study was to investigate the serum levels of antioxidant vitamins and elements in 24 children (14 boys and 10 girls, age range: 7-12 years, mean age: 9.2 years) with chronic rhinosinusitis, compared to 20 age and sex matched healthy children. Blood samples were collected in the morning before breakfast and prior to any medication. Vitamin A, E and C levels were determined using reagent kits for high performance liquid chromatography. Cu, Zn and Mg levels were analyzed by atomic absorption spectrometry. Vitamin E, vitamin C, Cu and Zn levels were significantly lower in the patients group than in the control group. However, vitamin A and Mg levels did not differ. In conclusion, serum levels of antioxidant vitamins and elements may be important in the pathogenesis and treatment of chronic rhinosinusitis in children.