The lymphotoxin alpha is a highly polymorphic gene and any genetic variation in it may lead to an increased production of cytokine LTA thus helping tumor development and progression. The aim of this work was to investigate the association of LTA polymorphism with the risk of breast cancer among Iraqi women. The findings of this study demonstrated that the age group > 50 years old formed 52% of the breast cancer patients (P <0.001). Hardy–Weinberg equilibrium analysis revealed that genotype frequencies of most SNPs in BC patients and HC were consistent with HWE. No association was found between LTA polymorphisms and BC. Moreover, seven haplotypes were detected in BC group. However, only one of them developed sign

Breast cancer is the most prevalent malignancy among women worldwide, in Iraq it ranks the first among the population and the leading cause of cancer related female mortality. This study is designed to investigate the correlations between serum and tissue markers in order to clarify their role in progression or regression breast cancer. Tumor Markers are groups of substances, mainly proteins, produced from cancer cell or from other cells in the body in response to tumor.  The study was carried out from April 2018 to April 2019 with total number of 60 breast cancer women. The blood samples were collected from breast cancer women in postoperative and pretherapeutic who attended teaching oncology hospital of the medical city in Baghdad and

Objectives: The study aimed to determine the effect of chemotherapy on the life style of patients who
receive chemotherapy.
Methodology: A descriptive study was conducted in Specialty Surgery Teaching Hospital, Al-yamok
Teaching Hospital, and Radiation and Nuclear Medicine Hospital in Baghdad for the period from May
2007 to October 2008. A purposive "non-probability" sample of (loo) patients with bladder cancer
who receive chemotherapy where concerned in this study.
A questionnaire fom was constnicted for the purpose of the study and it was comprised of
two parts. The questiormaire consists of (125) items. They include (1) demographic information (2)
assessment of lifestyle dimension. The content validity of the q

Aims: Because of the high incidence of cancer in females, we need to identify an accurate therapy to deal with the treatment of different types and stages of cancer. Histopathology acts as an important step to foresee the stage in which the cancer is present, its risk of metastasis, and the health outcomes after completion of treatment. Histopathology grading acts as an important criterion to determine the treatment pattern to be adopted, the prognosis in patients and other possible future risks. Hence conducting novel histopathologcial studies in major female cancers is necessary in determining the treatment plan to be chosen for the patient.

Study design: Retrospective Observational study

Human cytomegalovirus (HCMV) has a worldwide distribution and extremely common infections. The presence of HCMV genome and antigens has been detected in many kinds of human cancers especially breast cancer. In Iraq, the incidence of breast cancer generally exceeds any other type of malignancies among Iraqi population. The study was performed in the period between October 2016 and June 2017 in Central public health laboratory/Baghdad. It involve samples from 90 women including 60 breast cancer patients, 20 benign tumor patients, and 10 normal breast tissues. A blood sample was obtained from each woman included in this study. Anti-HCMV IgG antibody was presented in 9/10 (90%) of normal women, benign breast tumor patients 19/20 (95%) and malig

Background: The early detection of oral cancers gives the greatest chance of curing and the delay in presentation has a significant impact on the associated morbidity and mortality. The lack of general dental practitioners (GDP) knowledge in early cancer detection has been shown to contribute to delays in referral and treatment. The aim of this study was to investigate the oral cancer awareness among a group of GDP by assessing their knowledge of detection and prevention of oral cancer. Materials and methods: A questionnaire based study was designed. The questionnaire was delivered to 200 GDP assessing oral examination method, knowledge of oral cancer risk factors, clinical appearance and the most common site, point of referral and requests

The study included the collection of 75 bronchial wash samples from patients suspected to have lung cancer. These samples were subjected to a diagnostic cytological study to detect the dominant type of lung cancer. It was noticed that 33 patients proved to have a lung cancer out of 75 (44%) of these, 19 cases (57.6%)were diagnosed having Squamus cell carcinoma,7cases (21.21%) showed Adenocarcinoma ,6 cases (18.18%) were having small cell carcinoma while only one case (3.03%)was large cell carcinoma .Nearly 70% of cases were correlated with smokers .Bacteria were isolated from 53 patients in which 33 isolates were associated with the cancer cases while 20 of them from non infected patients. By using different morphological ,biochemical test

Background: Epstein Barr Virus (EBV) infection has been implicated in pathogenesis of several types of carcinomas such as nasopharyngeal carcinoma, gastric cancer and bladder cancer and has recently been associated with breast cancer.
Objective: To evaluate the relations between Epstein Barr virus-encoded small RNA (EBER) and breast cancer.
Methods: Twenty two cases of breast cancer were retrieved from the Al-Kadhimiya Teaching Hospital in Baghdad. Clinical data were analyzed from the medical records and formalin fixed, paraffin embedded tumor tissue were examined by Chromogeneic in situ hybridization (ISH) technique for the detection of EBER.
Results: The expression of EBER in tissues patients with breast cancer in the present

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum err

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu