Immunohistochemical evaluation of human epidermal growth factor receptor 2 and estrogen and progesterone receptors in breast carcinoma in Jordan

INTRODUCTION: Although breast carcinoma (BC) is the most common malignancy affecting Jordanian females and the affected population in Jordan is younger than that in the West, no information is available on its biological characteristics. Our aims in this study are to evaluate the expression of estrogen receptor (ER) and progesterone receptor (PR) and Her-2/neu overexpression in BC in Jordan, and to compare the expression of these with other prognostic parameters for BC such as histological type, histological grade, tumor size, patients' age, and number of lymph node metastases. METHOD: This is a retrospective study conducted in the Department of Pathology at Jordan University of Science and Technology. A confirmed 91 cases of BC diagnosed in the period 1995 to 1998 were reviewed and graded. We used immunohistochemistry to evaluate the expression of ER, PR, and Her-2. Immunohistochemical findings were correlated with age, tumor size, grade and axillary lymph node status. RESULTS: Her-2 was overexpressed in 24% of the cases. The mean age of Her-2 positive cases was 42 years as opposed to 53 years among Her-2 negative cases (p = 0.0001). Her-2 expression was inversely related to ER and PR expression. Her-2 positive tumors tended to be larger than Her-2 negative tumors with 35% overexpression among T3 tumors as opposed to 22% among T2 tumors (p = 0.13). Her-2 positive cases tended to have higher rates of axillary metastases, but this did not reach statistical significance. ER and PR positive cases were seen in older patients with smaller tumor sizes. CONCLUSION: Her-2 overexpression was seen in 24% of BC affecting Jordanian females. Her-2 overexpression was associated with young age at presentation, larger tumor size, and was inversely related to ER and PR expression. One-fifth of the carcinomas were Her-2 positive and ER negative. This group appears to represent an aggressive form of BC presenting at a young age with large primary tumors and a high rate of four or more axillary lymph node metastases

Integration of Data Mining Classification Techniques and Ensemble Learning for Predicting the Type of Breast Cancer Recurrence

Conservative surgery plus radiotherapy is an alternative to radical mastectomy in the early stages of breast cancer, presenting equivalent survival rates. Data mining facilitates to manage the data and provide the useful medical progression and treatment of cancerous conditions as these methods can help to reduce the number of false positive and false negative decisions. Various machine learning techniques can be used to support the doctors in effective and accurate decision making. In this paper, various classifiers have been tested for the prediction of type of breast cancer recurrence and the results show that neural networks outperform others

Three-Dimensional Analysis of Spiny Dendrites Using Straightening and Unrolling Transforms

Current understanding of the synaptic organization of the brain depends to a large extent on knowledge about the synaptic inputs to the neurons. Indeed, the dendritic surfaces of pyramidal cells (the most common neuron in the cerebral cortex) are covered by thin protrusions named dendritic spines. These represent the targets of most excitatory synapses in the cerebral cortex and therefore, dendritic spines prove critical in learning, memory and cognition. This paper presents a new method that facilitates the analysis of the 3D structure of spine insertions in dendrites, providing insight on spine distribution patterns. This method is based both on the implementation of straightening and unrolling transformations to move the analysis process to a planar, unfolded arrangement, and on the design of DISPINE, an interactive environment that supports the visual analysis of 3D patterns

Predictors of long-term outcome following high-dose chemotherapy in high-risk primary breast cancer

We report on a predictive model of long-term outcome in 114 high-risk breast cancer patients treated with high-dose chemotherapy between 1989 and 1994. Paraffin-blocks from 90 of the 114 primaries were assessed for the presence of five risk factors: grade, mitotic index, protein expression of p53, HER2/neu, and oestrogen/progesterone receptor status; we could analyse the effect of risk factors in 84 of these 90 tumours. Seven-year relapse-free and overall survival was 58% (95% confidence interval 44–74%) and 82% (95% confidence interval 71–94%) vs 33% (95% confidence interval 21–52%) and 41% (95% confidence interval 28–60%) for patients whose primary tumours displayed ⩾3 risk factors vs patients with ⩽2 risk factors. For the entire group of 168 high-risk breast cancer patients, inflammatory stage IIIB disease and involved post-mastectomy margins were associated with decreased relapse-free survival and overall survival; patients treated with non-doxorubicin containing standard adjuvant therapy experienced worse overall survival (RR, 2.08; 95% confidence interval 1.04 to 4.16; P=0.04), while adjuvant tamoxifen improved overall survival (RR, 0.65; 95% confidence interval 0.41–1.01; P=0.054). Future trial designs and patient selection for studies specific for high-risk breast cancer patients should include appropriate prognostic models. Validation of such models could come from recently completed randomised, prospective trials

Prognostic factors for patients with hepatic metastases from breast cancer

Median survival from liver metastases secondary to breast cancer is only a few months, with very rare 5-year survival. This study reviewed 145 patients with liver metastases from breast cancer to determine factors that may influence survival. Data were analysed using Kaplan–Meier survival curves, univariate and multivariate analysis. Median survival was 4.23 months (range 0.16–51), with a 27.6% 1-year survival. Factors that significantly predicted a poor prognosis on univariate analysis included symptomatic liver disease, deranged liver function tests, the presence of ascites, histological grade 3 disease at primary presentation, advanced age, oestrogen receptor (ER) negative tumours, carcinoembryonic antigen of over 1000 ng ml−1 and multiple vs single liver metastases. Response to treatment was also a significant predictor of survival with patients responding to chemo- or endocrine therapy surviving for a median of 13 and 13.9 months, respectively. Multivariate analysis of pretreatment variables identified a low albumin, advanced age and ER negativity as independent predictors of poor survival. The time interval between primary and metastatic disease, metastases at extrahepatic sites, histological subtype and nodal stage at primary presentation did not predict prognosis. Awareness of the prognostic implications of the above factors may assist in selecting the most appropriate treatment for these patients

Aspects of molecular phenotype and its correlations with breast cancer behaviour and taxonomy

The assessment of breast cancer morphology remains an important element in the evaluation of prognosis and therapeutic planning for this disease. The tumour morphology reflects the molecular profile that produced it and consequently each can be predictive of the other

Electrotonic Signals along Intracellular Membranes May Interconnect Dendritic Spines and Nucleus

Synapses on dendritic spines of pyramidal neurons show a remarkable ability to induce phosphorylation of transcription factors at the nuclear level with a short latency, incompatible with a diffusion process from the dendritic spines to the nucleus. To account for these findings, we formulated a novel extension of the classical cable theory by considering the fact that the endoplasmic reticulum (ER) is an effective charge separator, forming an intrinsic compartment that extends from the spine to the nuclear membrane. We use realistic parameters to show that an electrotonic signal may be transmitted along the ER from the dendritic spines to the nucleus. We found that this type of signal transduction can additionally account for the remarkable ability of the cell nucleus to differentiate between depolarizing synaptic signals that originate from the dendritic spines and back-propagating action potentials. This study considers a novel computational role for dendritic spines, and sheds new light on how spines and ER may jointly create an additional level of processing within the single neuron