The objective of this study was to compare levels of four elements (zinc, copper, selenium, and iron) in the serum and tissue of 68 breast tumor patients (benign and malignant), from a teaching hospital in central Taiwan. Samples of normal tissue (5 cm away from tumor) were also taken from patients with malignant tumors. Only serum was taken from the 25 healthy persons in the control group. Results showed that Zn, Cu, Se, Fe, Cu/Zn, Cu/Se, and Cu/Fe were present in different amounts in the serum of each of the three groups. Zn and Se levels were lower in the serum of the two tumor groups compared to the control group. In tissue samples, Zn, Cu, Se, and Fe concentrations were different in each of the three groups. The malignant tissue had the highest levels of all four elements. In advanced-stage malignant tumors, levels of Cu and the ratios of Cu/Fe and Cu/Zn (in both serum and tissue) were highest. The ratios of serum Cu/Zn, Cu/Fe, and Cu/Se were also higher in malignant patients. The cutoff value of serum Cu/Zn was 1.2 (sensitivity and specificity were both 100%). The Cu/Zn ratio was highest in the advanced stages of cancer and was a better diagnostic tool for breast cancer than Cu/Se and Cu/Fe. The authors suggest that change of trace elements in serum and tissue might be useful and significant as biomarkers involving the initial plastic process.
Dietary polyphenols have been correlated with a reduced risk of developing cancer. Quercetin (a natural polyphenolic compound) induced apoptosis in many human cancer cell lines, including breast cancer MCF-7 cells. However, the involvement of possible signaling pathways and the roles of quercetin in apoptosis are still undefined. The purpose of this study was to investigate the effects of quercetin on the induction of the apoptotic pathway in human breast cancer MCF-7 cells. When MCF-7 cells were treated with quercetin for 24 and 48 h and at various doses (10-175 microM), cell viability decreased significantly in time- and dose-dependent manners. Exposure of MCF-7 cells to 10-175 microM quercetin resulted in an approximate 90.25% decrease in viable cells. To explicate the mechanism underlying the antiproliferative effect of quercetin, cell cycle distribution and apoptosis in MCF-7 cells was investigated after exposure to 150 microM quercetin for 6-48 h. Quercetin caused a remarkable increase in the number of S phase (14.56% to 61.35%) and sub-G1 phase cells (0.1% to 8.32%) in a dose- and time-dependent manner. Quercetin caused S phase arrest by decreasing the protein expression of CDK2, cyclins A and B while increasing the p53 and p57 proteins. Following incubation with quercetin for 48 h, MCF-7 cells showed apoptotic cell death by the decreased levels of Bcl-2 protein and DeltaPsi(m) and increased activations of caspase-6, -8 and -9. Moreover, quercetin increased the AIF protein released from mitochondria to nuclei and the GADD153 protein translocation from endoplasmic reticulum to the nuclei. These data suggested that quercetin may induce apoptosis by direct activation of the caspase cascade through the mitochondrial pathway in MCF-7 cells.
Ultrasound (US) is a useful diagnostic tool to distinguish benign from malignant masses of the breast. It is a very convenient and safe diagnostic method. However, there is a considerable overlap benignancy and malignancy in ultrasonic images and interpretation is subjective. A high performance breast tumors computer-aided diagnosis (CAD) system can provide an accurate and reliable diagnostic second opinion for physicians to distinguish benign breast lesions from malignant ones. The potential of sonographic texture analysis to improve breast tumor classifications has been demonstrated. However, the texture analysis is system-dependent. The disadvantages of these systems which use texture analysis to classify tumors are they usually perform well only in one specific ultrasound system. While Morphological based US diagnosis of breast tumor will take the advantage of nearly independent to either the setting of US system and different US machines. In this study, the tumors are segmented using the newly developed level set method at first and then six morphologic features are used to distinguish the benign and malignant cases. The support vector machine (SVM) is used to classify the tumors. There are 210 ultrasonic images of pathologically proven benign breast tumors from 120 patients and carcinomas from 90 patients in the ultrasonic image database. The database contains only one image from each patient. The ultrasonic images are captured at the largest diameter of the tumor. The images are collected consecutively from August 1, 1999 to May 31, 2000; the patients' ages ranged from 18 to 64 years. Sonography is performed using an ATL HDI 3000 system with a L10-5 small part transducer. In the experiment, the accuracy of SVM with shape information for classifying malignancies is 90.95% (191/210), the sensitivity is 88.89% (80/90), the specificity is 92.5% (111/120), the positive predictive value is 89.89% (80/89), and the negative predictive value is 91.74% (111/121).
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