The Importance of Complementary PCR Analysis in Addition to Serological Testing for the Detection of Transmission Sources of Brucella spp. in Greek Ruminants.

The early and accurate diagnosis of brucellosis, a ubiquitous zoonotic infection, is significant in preventing disease transmission. This study aimed to assess the infection rate of Brucella spp. in ruminants and to evaluate the agreement between a serological test and a molecular method for the detection of infected cases. Blood and milk samples of 136 ruminants were analyzed using two laboratory methods: the Rose Bengal plate (RBP) test to detect B. abortus and B. melitensis antibodies and the molecular polymerase chain reaction (PCR) method for the presence of bacterial DNA. The agreement between the methods was assessed using the kappa statistic. Based on the RBP test, there were 12 (8.8%) seropositive animals (10 sheep and 2 cows), while 2 (1.4%) samples were positive on PCR analysis. The positive PCR samples were from seronegative cow samples on RBP testing. There was slight agreement (k = -0.02) between the two methods, which was not statistically significant. Our results indicate that complementary molecular methods are useful to detect the bacteria in infected animals that are seronegative due to an early stage of infection. Therefore, a combination of molecular methods and serological tests can be applied to detect brucellosis in ruminants efficiently.

hTERT regulation by NF-κB and c-myc in irradiated HER2-positive breast cancer cells.

PURPOSE: Telomerase activity (TA), frequently observed in cancer, compensates for telomere shortening thus preventing cell senescence and conferring resistance to therapy. In the present study, we investigated the expression of human telomerase reverse transcriptase (hTERT) and TA and their regulation, as well as apoptotic rates and correlation with the presence of human epidermal growth factor receptor 2 (HER2), in irradiated tumour-derived breast cancer cells. MATERIALS AND METHODS: In 50 breast cancer tissue samples hTERT mRNA expression and TA were correlated with cell features (HER2, Estrogen and Progesterone Receptor status). Cells from six samples were then irradiated with 10 and 20 Gy; apoptotic rates were measured by flow cytometry, hTERT mRNA expression by real-time polymerase chain reaction and TA by telomeric repeat amplification protocol assay, at 24-144 h post-irradiation. Chromatin immunoprecipitation was performed to investigate hTERT and cellular-myelocytomatosis (c-myc) promoters' activity. HER2 gene knockdown was performed using small interfering RNA technology. RESULTS: hTERT/TA were found increased only in irradiated HER2-positive cells, which were found to be more radioresistant, while HER2 knockdown led to hTERT/TA downregulation. HER2 was found to mediate hTERT expression through activation of Nuclear Factor-kappa B (NF-κB) and c-myc. CONCLUSIONS: The present study suggests that following irradiation, HER2 receptor activates hTERT/telomerase, increasing the breast cancer cells' survival potential, through sequential induction of transcription factors NF-κΒ and c-myc.

Survivin regulation by HER2 through NF-κB and c-myc in irradiated breast cancer cells.

Radiotherapy is an important treatment modality against cancer resulting in apoptosis and inhibition of cell growth. Survivin is an important cancer biomarker conferring to tumour cells increased survival potential by inhibiting apoptosis. In the present study, we investigated the implication of breast cancer cells features, as hormone receptors and p53 status, in the radio-resistance of breast cancer cells and in the regulation of survivin's expression by nuclear factor (NF)-κB and c-myc. Six breast cancer cell lines Michigan Cancer Foundation (MCF-7), MCF-7/Human Epidermal Growth Factor Receptor (HER)2, M. D. Anderson - Metastatic Breast (MDA-MB-231), SK-BR-3, BT-474 and Human Breast Lactating (HBL-100) were irradiated and cell viability as well as cell cycle distribution were evaluated by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and flow cytometry, respectively. Survivin mRNA and protein levels were evaluated by real time PCR and Western blot analysis. Survivin and HER2 gene knockdown was performed with siRNA technology and investigation of transcription factors binding to survivin and c-myc gene promoters was assessed by chromatin immunoprecipitation. Student's t-test and F-statistics were used for statistical evaluation. Our results demonstrated that only HER2(+) breast cancer cells up-regulated survivin upon irradiation, whereas HER2 knockdown in HER2(+) cells led to survivin's down-regulation. Survivin and especially HER2 knockdown abolished the observed G2/M cell cycle checkpoint and reduced the radio-resistance of HER2 overexpressing breast cancer cells. Additionally, HER2 was found to regulate survivin's expression through NF-κB and c-myc transcription factors. This study revealed the significance of HER2 in the radio-resistance of HER2(+) breast cancer cells through induction of transcription factors NF-κB and c-myc, leading to activation of survivin, a downstream target oncogene preventing apoptosis.

Evaluation of imputation methods in ovarian tumor diagnostic models using generalized linear models and support vector machines.

UNLABELLED: Neglecting missing values in diagnostic models can result in unreliable and suboptimal performance on new data. In this study, the authors imputed missing values for the CA-125 tumor marker in a large data set of ovarian tumors that was used to develop models for predicting malignancy. Four imputation techniques were applied: regression imputation, expectation-maximization, data augmentation, and hotdeck. Models using the imputed data sets were compared with models without CA-125 to investigate the important clinical issue concerning the necessity of CA-125 information for diagnostic models and with models using only complete cases to investigate differences between imputation and complete case strategies for missing values. The models are based on Bayesian generalized linear models (GLMs) and Bayesian least squares support vector machines. RESULTS: indicate that the use of CA-125 resulted in small, clinically nonsignificant increases in the AUC of diagnostic models. Minor differences between imputation methods were observed, and imputing CA-125 resulted in minor differences in the AUC compared with complete case analysis (CCA). However, GLM parameter estimates of predictor variables often differed between CCA and models based on imputation. The authors conclude that CA-125 is not indispensable in diagnostic models for ovarian tumors and that missing value imputation is preferred over CCA.

The involvement of HER2 and p53 status in the regulation of telomerase in irradiated breast cancer cells.

Cancer cell characteristics may play a pivotal role in the response to therapy by activating or deactivating different molecular pathways. In the present study, we investigated the implication of breast cancer cell features, such as HER2 and p53 in the activation of telomerase upon exposure to ionizing radiation. Telomerase is among the most important cancer biomarkers, conferring to tumor cells unlimited proliferative capacity, increased survival potential and resistance to several types of cellular stress. We investigated possible mechanisms regulating telomerase in six irradiated breast cancer cell lines (MCF-7, MCF-7/HER2, MDA-MB-231, SK-BR-3, BT-474 and HBL-100) differing in their HER2, p53 and ERalpha status. hTERT mRNA expression was evaluated by real-time PCR and telomerase activity by the TRAP assay. HER2, c-myc, p53 and p21 protein levels were evaluated by Western blotting. Silencing of hTERT and HER2 was achieved by small interfering RNA technology. Chromatin immunoprecipitation was used to evaluate H3 histone acetylation status, as well as myc/mad/max and p53 transcription factors interaction with the hTERT promoter. Our results showed for the first time, that only HER2-positive cells, independently of their p53 status, upregulated hTERT/telomerase, while knockdown of hTERT increased radio-sensitivity. Knockdown of HER2 also led to increased radio-sensitivity and downregulation of hTERT/telomerase. We also demonstrated that c-myc and mad1 regulate hTERT expression in all irradiated breast cancer cells. We conclude, for the first time, that HER2 phenotype upregulates hTERT through c-myc activation and confers radio-resistance to breast cancer cells.

External validation of mathematical models to distinguish between benign and malignant adnexal tumors: a multicenter study by the International Ovarian Tumor Analysis Group.

PURPOSE: Several scoring systems have been developed to distinguish between benign and malignant adnexal tumors. However, few of them have been externally validated in new populations. Our aim was to compare their performance on a prospectively collected large multicenter data set. EXPERIMENTAL DESIGN: In phase I of the International Ovarian Tumor Analysis multicenter study, patients with a persistent adnexal mass were examined with transvaginal ultrasound and color Doppler imaging. More than 50 end point variables were prospectively recorded for analysis. The outcome measure was the histologic classification of excised tissue as malignant or benign. We used the International Ovarian Tumor Analysis data to test the accuracy of previously published scoring systems. Receiver operating characteristic curves were constructed to compare the performance of the models. RESULTS: Data from 1,066 patients were included; 800 patients (75%) had benign tumors and 266 patients (25%) had malignant tumors. The morphologic scoring system used by Lerner gave an area under the receiver operating characteristic curve (AUC) of 0.68, whereas the multimodal risk of malignancy index used by Jacobs gave an AUC of 0.88. The corresponding values for logistic regression and artificial neural network models varied between 0.76 and 0.91 and between 0.87 and 0.90, respectively. Advanced kernel-based classifiers gave an AUC of up to 0.92. CONCLUSION: The performance of the risk of malignancy index was similar to that of most logistic regression and artificial neural network models. The best result was obtained with a relevance vector machine with radial basis function kernel. Because the models were tested on a large multicenter data set, results are likely to be generally applicable.

Classifier fusion approaches for diagnostic cancer models.

Classifier ensembles have produced promising results, improving accuracy, confidence and most importantly feature space coverage in many practical applications. The recent trend is to move from heuristic combinations of classifiers to more statistically sound integrated schemes to produce quantifiable results as far as error bounds and overall generalization capability are concerned. In this study, we are evaluating the use of an ensemble of 8 classifiers based on 15 different fusion strategies on two medical problems. We measure the base classifiers correlation using 11 commonly accepted metrics and provide the grounds for choosing an improved hyper-classifier.