Showing papers in "Asian Pacific Journal of Cancer Prevention in 2019"

Global Trend of Breast Cancer Mortality Rate: A 25-Year Study.

Abstract: Background: breast cancer is the most common cause of cancer death for women worldwide. In the past two decades, published epidemiological reports in different parts of the world show significant increase in breast cancer mortality rate. The aim of this study was to determine the 25-year trend of breast cancer mortality rate in 7 super regions defined by the Health Metrics and Evaluation (IHME), i.e. Sub-Saharan Africa, North Africa and Middle East, South Asia, Southeast Asia and East Asia and Oceania, Latin America and Caribbean, Central Europe and Eastern Europe and Central Asia, High-income. Methods: Our study population consisted of 195 world countries in the IHME pre-defined seven super regions. The age-standardized mortality rates from 1990 to 2015 were extracted from the IHME site. The reference life table for calculating mortality rates was constructed based on the lowest estimated age-specific mortality rates from all locations with populations over 5 million in the 2015 iteration of GBD. To determine the trend of breast cancer mortality rate, a generalized linear mixed model was fitted separately for each IHME region and super region. Results: Statistical analysis showed a significant increase for breast cancer mortality rate in all super regions, except for High-income super region. For total world countries, the mean breast cancer mortality rate was 13.77 per 100,000 in 1990 and the overall slope of mortality rate was 0.7 per 100,000 from 1990 to 2015. The results showed that Latin America and Caribbean the highest increasing trend of breast cancer mortality rate during the years 1990 to 2015 (1.48 per 100,000). Conclusion: In general, our finding showed a significant increase in breast cancer mortality rate in the world during the past 25 years, which could be due to increase in incidence and prevalence of this cancer. Low this increasing trend is an alarm for health policy makers in all countries, especially in developing countries and low-income regions which experienced sharp slopes of breast cancer mortality rate.

Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM)

Abstract: Objective: The main objective of this study is to improve the classification performance of melanoma using deep learning based automatic skin lesion segmentation. It can be assist medical experts on early diagnosis of melanoma on dermoscopy images. Methods: First A Convolutional Neural Network (CNN) based U-net algorithm is used for segmentation process. Then extract color, texture and shape features from the segmented image using Local Binary Pattern ( LBP), Edge Histogram (EH), Histogram of Oriented Gradients (HOG) and Gabor method. Finally all the features extracted from these methods were fed into the Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbor (KNN) and Naive Bayes (NB) classifiers to diagnose the skin image which is either melanoma or benign lesions. Results: Experimental results show the effectiveness of the proposed method. The Dice co-efficiency value of 77.5% is achieved for image segmentation and SVM classifier produced 85.19% of accuracy. Conclusion: In deep learning environment, U-Net segmentation algorithm is found to be the best method for segmentation and it helps to improve the classification performance.

Pretreatment Neutrophil-to-Lymphocyte ratio (NLR) and Platelet-to-Lymphocyte Ratio (PLR) as a Predictive Value of Hematological Markers in Cervical Cancer

Abstract: Background: Inflammation represents a pivotal role in the progression of cervical cancer. The hematological markers of inflammation in complete blood count (CBC) panel are potentially useful in determining the prognosis of the disease. Objective: The aim of the study was to investigate whether the pretreatment neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) could be used as in predicting the stage of cervical cancer. Methods: A retrospective cross-sectional study involving 282 patients with cervical cancer was enrolled at Sanglah General Hospital for five years (2013-2017). The histopathological records and complete blood counts (CBC) of the patients were collected and analyzed using SPSS ver. 16 software. FIGO stage I–II and III-IV were classified as early and advance stage respectively. Results: The median NLR and PLR were significantly higher in the advance stage compared with early stage (7.58 (1.36-33.20) and 247.89 (97.10-707.11); p-value = 0.001). A strong positive correlation was found between the staging of cervical cancer and NLR (r=0.638) and PLR (r=0.668). The AUC, sensitivity, and specificity value of NLR and PLR were 0.803 (82%; 71%) and 0.716 (72%; 70%). Advanced stage of cervical cancer was found in high NLR (adjusted OR: 9.02; 95%CI=2.42-33.64; p=0.001) and PLR (adjusted OR = 2.47; 95% CI = 1.45-4.85; p = 0.032). Conclusion: Increased pretreatment NLR and PLR values may provide a useful information in predicting the staging of cervical cancer.

Analysis of Decision Tree and K-Nearest Neighbor Algorithm in the Classification of Breast Cancer.

Abstract: Objective The death rate of breast tumour is falling as there is progress in its research area. However, it is the most common disease among women. It is a great challenge in designing a machine learning model to evaluate the performance of the classification of breast tumour. Methods Implementing an efficient classification methodology will support in resolving the complications in analyzing breast cancer. This proposed model employs two machine learning (ML) algorithms for the categorization of breast tumour; Decision Tree and K-Nearest Neighbour (KNN) algorithm is used for the breast tumour classification. Result This classification includes the two levels of disease as benign or malignant. These two machine learning algorithms are verified using the Wisconsin Diagnostic Breast Cancer (WDBC) dataset after feature selection using Principal Component Analysis (PCA). The comparison of these two ML algorithms is done using the standard performance metrics. Conclusion The comparative analysis results indicate that the KNN classifier outperforms the result of the decision-tree classifier in the breast cancer classification. .

Lung Cancer Detection using Probabilistic Neural Network with modified Crow-Search Algorithm.

Abstract: Objective: Lung cancer is a type of malignancy that occurs most commonly among men and the third most common type of malignancy among women. The timely recognition of lung cancer is necessary for decreasing the effect of death rate worldwide. Since the symptoms of lung cancer are identified only at an advanced stage, it is essential to predict the disease at its earlier stage using any medical imaging techniques. This work aims to propose a classification methodology for lung cancer automatically at the initial stage. Methods: The work adopts computed tomography (CT) imaging modality of lungs for the examination and probabilistic neural network (PNN) for the classification task. After pre-processing of the input lung images, feature extraction for the work is carried out based on the Gray-Level Co-Occurrence Matrix (GLCM) and chaotic crow search algorithm (CCSA) based feature selection is proposed. Results: Specificity, Sensitivity, Positive and Negative Predictive Values, Accuracy are the computation metrics used. The results indicate that the CCSA based feature selection effectively provides an accuracy of 90%. Conclusion: The strategy for the selection of appropriate extracted features is employed to improve the efficiency of classification and the work shows that the PNN with CCSA based feature selection gives an improved classification than without using CCSA for feature selection.

Cancer Incidence and Mortality in Firefighters: A State-of-the-Art Review and Meta-َAnalysis.

Abstract: Objective: A systematic literature review and meta-analysis was conducted on the association between firefighting and cancer. Methods: A comprehensive literature search of databases including Medline, EMBASE, Biosis, NIOSHTIC2, Web of Science, Cancerlit, and HealthStar, for the period between 1966 to January 2007, was conducted. We also retrieved additional studies by manual searching. Results: A total of 49 studies were included in the meta-analysis. We found statistically significant associations between firefighting and cancers of bladder, brain and CNS, and colorectal cancers, consistent with several previous risk estimates. We also found statistically significant associations of firefighting with non-Hodgkin’s lymphoma, skin melanoma, prostate, and testicular cancer. For kidney, Hodgkin’s lymphoma, leukemia, lymphosarcoma and reticulosarcoma, multiple myeloma, and pancreatic cancer, we found some statistically significant but less consistent results. For all other cancers evaluated (esophageal, laryngeal, oral and pharyngeal, liver and gallbladder, lung, lymphatic and hematopoietic, non-melanoma skin cancer, stomach, and urinary cancer) we did not find any statistically significant associations. Conclusions: Although our meta-analysis showed statistically significant increased risks of either cancer incidence or mortality of certain cancers in association with firefighting, a number of important limitations of the underlying studies exist, which, precluded our ability to arrive at definitive conclusions regarding causation.

Awareness about Breast Cancer and Breast Self-Examination among Female Students at the University of Sharjah: A Cross-Sectional Study.

Abstract: Background: Breast cancer is a leading cause of mortality among women in the United Arab Emirates (UAE). Many young women in the UAE have poor knowledge about breast cancer screening, including risk factors and warning signs/symptoms. We investigated awareness about breast cancer and breast self-examination (BSE) as a screening tool among female students at the University of Sharjah, UAE. Methods: This study used a cross sectional survey design. Participants were 241 undergraduate female students (aged ≥18 years) from three University of Sharjah campuses. Data were collected from March to April 2017 using a self-administered questionnaire. The questionnaire covered: sociodemographic characteristics; knowledge about breast cancer, risk factors, and warning signs/symptoms; and knowledge and practice of BSE. Data were analyzed using descriptive statistics and Pearson’s chi-square tests. Results: About 38.6% of participants were from the Medical campus, 37.3% were from the Women’s campus, and 24% were from the Fine Arts and Design campus. Most (99%) participants had heard of breast cancer. About 50% were knowledgeable about the risk factors, but only 38% were knowledgeable about warning signs/symptoms. The most commonly identified risk factors were family and personal histories of breast cancer, and the most commonly identified warning sign/symptom was breast lump. There was a significant association between knowledge about risk factors and campus type. Participants from the Medical campus were more knowledgeable about risk factors than participants from the other two campuses. Overall, 68.5% of participants had heard of BSE, but few participants actually performed BSE. Reasons for not performing BSE included “forgetting” and “not knowing how.” Conclusions: Although most participants were aware of breast cancer, knowledge about risk factors and warning signs/symptoms was relatively poor. Knowledge about performing BSE was particularly low. This highlights the importance of increasing awareness about breast cancer and BSE among young women in the UAE.

Classification of Skin Disease using Ensemble Data Mining Techniques.

Abstract: Objective: Skin diseases are a major global health problem associated with high number of people. With the rapid development of technologies and the application of various data mining techniques in recent years, the progress of dermatological predictive classification has become more and more predictive and accurate. Therefore, development of machine learning techniques, which can effectively differentiate skin disease classification, is of vast importance. The machine learning techniques applied to skin disease prediction so far, no techniques outperforms over all the others. Methods: In this research paper, we present a new method, which applies five different data mining techniques and then developed an ensemble approach that consists all the five different data mining techniques as a single unit. We use informative Dermatology data to analysis different data mining techniques to classify the skin disease and then, an ensemble machine learning method is applied. Results: The proposed ensemble method, which is based on machine learning was tested on Dermatology datasets and classify the type of skin disease in six different classes like include C1: psoriasis, C2: seborrheic dermatitis, C3: lichen planus, C4: pityriasis rosea, C5: chronic dermatitis, C6: pityriasis rubra. The results show that the dermatological prediction accuracy of the test data set is increased compared to a single classifier. Conclusion: The ensemble method used on Dermatology datasets give better performance as compared to different classifier algorithms. Ensemble method gives more accurate and effective skin disease prediction.

The Carcinogenic Agent Diethylnitrosamine Induces Early Oxidative Stress, Inflammation and Proliferation in Rat Liver, Stomach and Colon: Protective Effect of Ginger Extract.

Abstract: Background: Diethylnitrosamine (DENA), a well-known dietary carcinogen, related to cancer initiation of various organs. The present study investigated the deleterious mechanisms involved in the early destructive changes of DENA in different organs namely, liver, stomach and colon and the potential protective effect of GE against these mechanisms. Methods: Adult male albino rats were assigned into four groups. A normal control group received the vehicle, another group was injected with a single necrogenic dose of DENA (200 mg/kg, i.p) on day 21. Two groups received oral GE (108 or 216 mg/kg) daily for 28 days. Sera, liver, stomach and colon were obtained 7 days after DENA injection. Serum aspartate transaminase and alanine transaminase were detected as well as reduced glutathione (GSH), malondialdehyde, nitric oxide metabolites, interleukin 1β, tumor necrosis factor (TNF-α), alpha-fetoprotein (AFP) and nuclear factorerythroid 2-related factor2 (Nrf2) in liver, stomach and colon. Histopathological studies and immunohistochemical examination of cyclooxygenase-2 (COX2) were conducted. Results: DENA induced elevation in liver function enzymes with significant increase in oxidation and inflammation biomarkers and AFP while decreased levels of Nrf2 in liver, stomach and colon were detected. Histologically, DENA showed degenerative changes in hepatocytes and inflammatory foci. Inflammatory foci displayed increased expression of COX2 in immunohistochemical staining. GE-pretreatment improved liver function and restored normal GSH with significant mitigation of oxidative stress and inflammatory biomarkers compared to DENA-treated group. AFP was reduced by GE in both doses, while Nrf2 increased significantly. Histology and immunostaining of hepatic COX-2 were remarkably improved in GE-treated groups in a dose dependent manner. Conclusion: GE exerted a potential anti-proliferative activity against DENA in liver, stomach and colon via Nrf2 activation, whilst suppression of oxidation and inflammation.

Brain Tumour Segmentation Using Convolutional Neural Network with Tensor Flow.

Abstract: Introduction: The determination of tumour extent is a major challenging task in brain tumour planning and quantitative evaluation. Magnetic Resonance Imaging (MRI) is one of the non-invasive technique has emanated as a front- line diagnostic tool for brain tumour without ionizing radiation. Objective: Among brain tumours, gliomas are the most common aggressive, leading to a very short life expectancy in their highest grade. In the clinical practice manual segmentation is a time consuming task and their performance is highly depended on the operator’s experience. Methods: This paper proposes fully automatic segmentation of brain tumour using convolutional neural network. Further, it uses high grade gilomas brain image from BRATS 2015 database. The suggested work accomplishes brain tumour segmentation using tensor flow, in which the anaconda frameworks are used to implement high level mathematical functions. The survival rates of patients are improved by early diagnosis of brain tumour. Results: Hence, the research work segments brain tumour into four classes like edema, non-enhancing tumour, enhancing tumour and necrotic tumour. Brain tumour segmentation needs to separate healthy tissues from tumour regions such as advancing tumour, necrotic core and surrounding edema. This is an essential step in diagnosis and treatment planning, both of which need to take place quickly in case of a malignancy in order to maximize the likelihood of successful treatment.

MiR-126 Modulates Angiogenesis in Breast Cancer by Targeting VEGF-A -mRNA

Abstract: Background: Breast cancer is most serious reasons of women death around worldwide result in increasing its morbidity and mortality. MicroRNAs are considered as significant regulators of cancer biological processes. The main aim of this study is restoration of miR-126 could lead to modulate breast cell line and impairs their proliferation by targeting vascular endothelial growth factor gene (VEGF-A). Methods: Breast cancer cell line (MCF7) was transfected by miR-126 lipofectamine and negative miR control for 24 hr. Cytotoxic effects of miR-126 lipofectamine were determined by cell viability assay. Cell proliferation and cell cycle were quantitatively measured using PicoGreen assay and DAPI stain-flow cytometer analysis. For further investigation, Taq-Man real time PCR assay was performed to detect relative VEGF-A and miRNA-126 level. Results: MiR-126 was overexpressed in treated breast cancer cell (MCF7) compared with control cells. miR-126 expression has been associated –with a decrease in cell proliferation and arrested MCF7 cells at G1 phase. The study found that vascular endothelial growth factor is regulated by miR- 126. Hence, VEGF-A is considered as functional vital and direct target to miR-126 in breast cancer cell line (MCF7). Conclusions: This study provided that manipulated miR-126 level may suggest a novel therapeutic approach in breast cancer treatment. However, an animal models study is needed to address and prove predictive ability of miR-126 on breast cancer controlling.

Salivary Tumour Necrosis Factor-α as a Biomarker in Oral Leukoplakia and Oral Squamous Cell Carcinoma

Abstract: Background: Oral cancer is one of the life threatening disease which requires an availability of a biomarker for its early detection and also for effective treatment strategies. The current study is done to evaluate the efficacy of one such biomarker i.e. TNF- α as an indicator for oral precancer and oral cancer. Objectives: To evaluate the efficacy of Tumour necrosis factor - alpha (TNF)-α as a salivary biomarker in histopathologically diagnosed cases of oral leukoplakia and Oral squamous cell carcinoma. To correlate the levels of TNF- α with varying histologic grading in Oral Squamous Cell Carcinoma and dysplasia grading in Oral leukoplakia or Hyperkeratosis. Materials and Methods: The study group included 90 subjects that were divided into three groups. OSCC (n=30), leukoplakia (n=30) and controls (n=30). Cases were selected based on inclusion and exclusion criteria of the study. Salivary samples were then collected from all three groups. Salivary levels of TNF-α were estimated using Enzyme Linked Immunosorbent Assay (ELISA). The data on concentration gradients obtained were subjected to appropriate statistical analysis. Results: The results of the present study demonstrated higher levels of salivary TNF-α in individuals with OSCC compared to leukoplakia and healthy control subjects with a high level of statistical significance. ROC curve analysis along with diagnostic parameter calculation also revealed that salivary TNF-α to be a better medium for detecting OSCC. There is also an increase in the salivary TNF-α levels with increase in the histological grade of differentiation in OSCC as well as leukoplakia. Conclusion: The present study concludes that salivary TNF – α can be used as a prognostic biomarker of OSCC. In view of the elevated levels of TNF – α in saliva of individuals with severe dysplasia, it can also be used to monitor the malignant transformation to leukoplakia to OSCC.

Nasopharyngeal Carcinoma (NPC) Risk Factors: A Systematic Review and Meta-Analysis of the Association with Lifestyle, Diets, Socioeconomic and Sociodemographic in Asian Region.

Abstract: Objective: Risk factors of nasopharyngeal carcinoma (NPC) have been linked with diets, life style and viral infections. NPC is more rampant in Asian populations than non-Asian countries. Our study aims to assess the validity of the suggestions provided by multiple case control studies demonstrating that salted fish consumption, smoking and alcohol consumption are associated with the risk of NPC in Asia. Methods: Search for related literature on salted fish, smoking and alcohol consumption were performed via Science Direct, PubMed databases and Google Scholar. Articles included in this study were from 2009 to 2017, with specific focus on salted fish, smoking and alcohol consumption as risk factors of NPC. This study excluded all articles published prior to 2009 and articles involving other cancers. Data were extracted independently by two different researchers and harmonized. Meta-analysis was conducted on the obtained data, by using R package Meta to create funnel and forest plots. Results: The meta-analysis revealed that salted fish, smoking and alcohol consumption were significantly associated to NPC risk with random effect model score showing OR of 1.41 at 95% confidence interval (CI) of 1.13-1.75 (P<0.01), OR of 1.89 at 95 % CI of 1.49 – 2.38, and OR: 1.42 at 95 % CI of 1.23 – 1.65 respectively. Our results also revealed significant association of salted meat, salted vegetables, house type, wood dust exposure associated with NPC risk with p values less than 0.05. Conclusion: This study proposes that salted fish intake, smoking and alcohol consumption might be linked to NPC risk in Asians. Further studies are necessary to ascertain the molecular mechanisms and clarify if the associated path that could function as therapeutic target.

An Investigation on the Therapeutic Potential of Butein, A Tretrahydroxychalcone Against Human Oral Squamous Cell Carcinoma.

Abstract: Background Oral squamous cell carcinoma (OSCC) is one of the most predominant cancers in India. With advances in the field of oncology, a number of therapies have emerged; however, they are minimally effective. Consequently, there is a need to develop safe and effective regimens for the treatment of OSCC. Butein, a tetrahydroxychalcone has been found to exhibit potent antioxidant, anti-inflammatory, and also anti-tumor effects against several cancer types. However, its effect on OSCC is not studied yet. Methods The effect of butein on the viability, apoptosis, migration and invasion of OSCC cells was evaluated using MTT, colony formation, PI/FACS, live and dead, scratch wound healing, and matrigel invasion assays. Further Western blot analysis was done to evaluate the expression of different proteins involved in the regulation of cancer hallmarks. Results This is the first report exemplifying the anti-cancer effect of butein against OSCC. Our results showed that butein exhibited potent anti-proliferative, cytotoxic, anti-migratory, and anti-invasive effects in OSCC cells. It suppressed the expression of NF-κB and NF-κB-regulated gene products such as COX-2, survivin and MMP-9 which are involved in the regulation of different processes like proliferation, survival, invasion, and metastasis of OSCC cells. Conclusion Collectively, these results suggest that butein has immense potential in the management of OSCC. Nonetheless, in vivo validation is critical before moving to clinical trials.

Family Caregivers' Involvement in Caring with Cancer and their Quality of Life.

Abstract: Background: Cancer is a chronic disease and a major health problem. It affects both patients and their family caregivers multidimensionally. The family caregivers may be affected by not only the disease process but also hospital policies, economic difficulties, accessibility and communication of health care service and can be in need of help. This process may affect their quality of life. However, there have not been enough studies on quality of life of family caregivers of patients with cancer in Turkish culture. Therefore, this study aimed to evaluate the quality of life of family caregivers of patients with cancer in Turkey. Objectives: The purpose of study was to evaluate the quality of life of family caregivers with cancer patients in Turkey. Methods: Participants consist of the family caregivers who volunteered to take part in this descriptive study from 11 hospitals (n =378) which has a daily chemotherapy units and located within the boundaries of Ankara, Turkey. ‘Sociodemographic Characteristic Form’ and ‘Quality of Life Scale-Family Version were used as data collection tool. The Kruskal-Wallis and Mann-Whitney U, tests were used for data analysis. Resultes:It is found that there are statistically significant difference among the factors of gender, employment status, income level, and whether caregivers reside with their patients. Family caregivers’ quality of life is negatively affected during the caregiving process (p < 0.05). Conclusion: The results indicate that family caregivers’ quality of life are negatively affected to care process. The results of this research are important as they highlight the need to also consider family caregivers’ quality of life when caring for patients, and study highlight possible areas in which support can be provided for family caregivers of cancer patients in Turkey.

Urine and Serum Exosomes as Novel Biomarkers in Detection of Bladder Cancer.

Abstract: Background: The gold standard for initial clinical diagnosis of bladder cancer involves cystoscopic examination of bladder and histological evaluation of tissues. There is a critical need to identify non-invasive and sensitive biomarkers. Early detection is essential challenge in diagnosis and surveillance of bladder carcinoma. Exosomes are nano- sized vesicles present in many biological fluids and have significant role in cancer. Thus, quantification of exosomes in different stages of bladder cancer may be of critical concern for clinical diagnosis and prognosis. Methods: Tumor derived exosomes levels in urine and serum samples of 70 bladder cancer Egyptian patients from stages T0-T3 and 12 healthy control people were measured using ELISA technique. Results: When compared to health subjects, exosomes levels in bladder cancer patients were increased in urine and serum samples at different stages of the disease. A gradual increase in tumor derived exosomes in serum (1.21, 3.31, 4.71, 6.47μg/ml) and urine (1.59, 2.84, 4.75, 6.67μg/ml) was observed comparative to invasiveness of tumor (T0-T3). Serum was more specific (100%) sample for detection of exosomes in bladder cancer. Conclusion: our findings suggest that tumor derived exosomes may offer a convenient tool for early diagnosis and monitoring of bladder cancer.

Association of Dietary Intake Ratio of n-3/n-6 Polyunsaturated Fatty Acids with Breast Cancer Risk in Western and Asian Countries: A Meta-Analysis

Abstract: Objective: This systematic review and meta-analysis were performed to determine association of dietary intake ratio of n-3/n-6 polyunsaturated fatty acids with breast cancer risk in Western and Asian countries. Methods: The authors conducted a meta-analysis of published research articles on association of dietary intake ratio of n-3/n-6 polyunsaturated fatty acids (PUFAs) with breast cancer risk in Western and Asian countries published between January 2000 and February 2019 in online article databases of PubMed, ProQuest and EBSCO. Pooled risk ratios (RR) were calculated using fixed and random-effect models. Publication bias was visually evaluated by performing funnel plots and statistically assessed by Egger’s and Begg’s tests. Data were processed by using Stata version 14.2 (Stata Corporation). Results: This study reviewed 913 articles. There were 13 studies included in systematic review continued by meta-analysis of relevant data with total number of samples: 275,264 patients. The results showed dietary intake ratio of n-3/n-6 PUFAs with breast cancer risk in Western and Asian countries (RR = 0.99; 95% CI: 0.92-1.07). Dietary intake ratio of n-3/n-6 PUFAs with breast cancer risk in Western countries reached (RR = 0.98; 95% CI: 0.91-1.06) and there was any significant publication bias for studies included. Dietary intake ratio of n-3/n-6 PUFAs with breast cancer risk in Asian countries reached (RR = 1.18; 95% CI: 0.94-1.47) and there was not any significant publication bias for studies included. Conclusion: This analysis confirmed association of dietary intake ratio of n-3/n-6 PUFAs with breast cancer risk in Western and Asian countries. Higher dietary intake ratio is associated with lower risk of breast cancer in Asian countries rather than Western countries. This study suggests increasing dietary intake ratio n-3/n-6 PUFAs will provide benefit for breast cancer prevention.

High Effective of 14-Day High-Dose PPI- Bismuth-Containing Quadruple Therapy with Probiotics Supplement for Helicobacter Pylori Eradication: A Double Blinded-Randomized Placebo-Controlled Study

Abstract: Background: Helicobacter pylori (H. pylori) infection is important risk factors for chronic gastritis, peptic ulcer and gastric cancer. Bismuth-containing quadruple therapy has recently been the first-line regimen recommended in many European countries but has limited efficacy in ASEAN especially Thailand. This study was aim to evaluate efficacy of high dose PPI Bismuth-containing quadruple therapy with probiotics supplement for H. pylori eradication. Methods: In this double-blind randomized placebo-controlled study, H. pylori infected patients were randomized to receive 7-or 14-day high dose PPI- bismuth-containing quadruple therapy with or without probiotics supplement. Probiotic was 37.5 mg Lactobacillus reuteri (Biogaia®) in tablet twice daily. CYP2C19 genotyping and antibiotic susceptibility tests were also done. H. pylori eradication was defined as a negative 13C-urea breath test at least 4 weeks after treatment. Results: 100 subjects were enrolled (72 females, 28 males, mean age=54 years). Antibiotic resistance was 15.6% for clarithromycin, 34.1% for metronidazole. CYP2C19 genotyping was performed in both group and revealed 13%, 50% and 37% for poor, intermediate and rapid metabolizers, respectively. Overall eradication rates of 7-day and 14-day regimens with probiotic were 68% and 96%; P value=0.027. The eradication rate for all patients with poor and rapid metabolizers were 100% with 14-day regimen. 14-day regimen with probiotics can provide 100% eradication with clarithromycin resistance, metronidazole resistance or dual clarithromycin and metronidazole resistance group. Furthermore, the incidence of nausea and vomiting, abdominal discomfort, and bitter taste were significantly lower in patients with probiotics group compared with placebo (6%vs.26%, P=0.002,OR=0.126,95% CI=0.03-0.53; 4%vs.18.0%, P=0.017, OR= 0.155,95% CI=0.03-0.81 and 4%vs.26%, P= 0.001,OR= 0.08, 95%CI= 0.016-0.41, respectively). Conclusions: The 14-day high dose PPI- bismuth-containing quadruple therapy with probiotic can provide an excellent cure rate for H. pylori infection as first line treatment irrespective of CYP2C19 and antibiotic resistance pattern. Adding probiotic also significantly reduced treatment-related adverse events and improve the patients’ compliance.

Protective Effect of Omega-3 Fatty Acids in Fish Consumption Against Breast Cancer in Asian Patients: A Meta-Analysis

Abstract: Objective: This systematic review and meta-analysis was performed to determine the protective effect of omega-3 fatty acids in fish consumption against breast cancer in Asian patients. Methods: The authors conducted a meta-analysis of published research articles on protective effect of omega-3 fatty acids in fish consumption against breast cancer in Asian patients published between January 2000 and July 2018 in online database of PubMed, ProQuest and EBSCO. Pooled odds ratios (OR) were calculated by using fixed and random-effect models. Publication bias was visually evaluated by using funnel plots and statistically assessed in Egger’s and Begg’s tests. Data were processed by Review Manager 5.3 (RevMan 5.3) and Stata version 14.2 (Stata Corporation). Results: This study reviewed 913 articles. There were 11 studies which conducted systematic review then continued by meta-analysis of relevant data with total number of samples were 130,365 patients. The results showed there was protective effect of omega-3 fatty acids in fish consumption against breast cancer in Asian patients (OR = 0.80 [95% CI 0.73-0.87, p <0.00001]). There was not any study with significant publication bias included. Conclusion: This analysis confirmed the protective effect of omega-3 fatty acids in fish consumption against breast cancer in Asian patients.

Knowledge and Attitude Toward Human Papillomavirus and HPV Vaccination in Iranian Population: A Systematic Review.

Abstract: Background and objective: Human papillomavirus (HPV) is the main cause of cervical cancer. This systematic review was performed to provide an overview of knowledge and attitude about HPV infection and HPV vaccine in Iranian population. Materials and Methods: The information was identified by searching international and national databases; pubmed/MEDLINE (NCBI), Embase (Elsevier), Google Scholar, Scientific Information Database, MagIran, and IranDoc. The current research was performed using the terms of medical subject headings (MeSH) and combinations of the keywords including: “human papillomavirus” or “human papillomavirus vaccine” with the words “knowledge,” “awareness,” “attitude” and “Iran.” Studies were evaluated according to the checklist of STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE). Results: A total of 10 observational studies that met the inclusion criteria were included in this review. The overall knowledge and awareness of the Iranian population (parents, women, university students, medical students, nurses and hospital staff) about HPV and HPV vaccination was low; however, the attitude toward this issue was positive and strong. Conclusion: Due to the low levels of knowledge about HPV infection and its methods of prevention, efforts should be increased to enhance the knowledge of the general population about HPV infection and vaccination in order to prevent its incidence and complications.

Awareness Level about Breast Cancer Risk Factors, Barriers, Attitude and Breast Cancer Screening among Indonesian Women

Abstract: Background: Globally, breast cancer is the second most common cancer in women and is a leading cause of mortality in Indonesia. Raising awareness of breast cancer is particularly important to help at risk women seek medical treatment for this disease. This study aimed to comprehensively investigate the Indonesian women’s level of knowledge about breast cancer risk factors, barriers, attitude and breast cancer screening. Methods: This population-based cross-sectional study administered the breast cancer awareness Indonesian scale (BCAS-I) to 856 Indonesian women. Samples were selected in rural and urban combinations from three provinces by stratified random sampling. The ordinal logistic model was used to investigate the clustering effect of the participant’s characteristics in this study. Results: Of the women, 62% lived in rural areas and 38% lived in urban areas. Living in an urban area was significantly associated with a lower knowledge of the risk factors. However, living in an urban area was significantly associated with better attitudes and healthier behaviours related to breast cancer awareness. Women with higher education levels had 70% worse attitudes toward breast cancer awareness. Women living South of Sumatera, women living in Yogyakarta, and unmarried women were 5.03, 3.84, and 1.56 times as likely to have higher perceived barriers, respectively. Conclusion: Urban women had a poorer level of knowledge of breast cancer risk factors compared to women living in more rural areas. The result of this study may reflect inadequate breast cancer awareness campaigns or a lack of breast cancer awareness campaigns. These findings suggest that additional education programs aiming to increase awareness and educate the public are needed.

To Generate an Ensemble Model for Women Thyroid Prediction Using Data Mining Techniques

Abstract: Objective: The main objective of this paper is to easily identify thyroid symptom for treatment. Methods: In this paper two main techniques are proposed for mining the hidden pattern in the dataset. Ensemble-I and Ensemble- II both are machine learning techniques. Ensemble-I generated from decision tree, over fitting and neural network and Ensemble-II generated from combinations of Bagging and Boosting techniques. Finally proposed experiment is conducted by Ensemble-I vs. Ensemble-II. Results: In the entire experimental setup find an ensemble –II generated model is the higher compare to other ensemble-I model. In each experiment observe and compare the value of all the performance of ROC, MAE, RMSE, RAE and RRSE. Stacking (ensemble-I) ensemble model estimate the weights for input with output model by thyroid dataset. After the measurement find out the results ROC=(98.80), MAE= (0.89), 6RMSE=(0.21), RAE= (52.78), RRSE=(83.71)and in the ensemble-II observe thyroid dataset and measure all performance of the model ROC=(98.79), MAE= (0.31), RMSE=(0.05) and RAE= (35.89) and RRSE=(52.67). Finally concluded that (Bagging+ Boosting) ensemble-II model is the best compare to other.

Validation of the Scored Patient-Generated Subjective Global Assessment (PG-SGA) in Thai Setting and Association with Nutritional Parameters in Cancer Patients

Abstract: Background: The Scored Patient-Generated Subjective Global Assessment (PG-SGA) is a multidimensional tool to assess malnutrition and risk factors. The objectives of this study are to determine the validity of the Thai version of the Scored PG-SGA (Thai PG-SGA) and examine the correlations with selected nutritional parameters. Methods: This observational analytic study included 195 cancer patients aged greater than 18 years at a university-affiliated hospital in Bangkok, Thailand. All patients were assessed for nutritional status by Thai PG-SGA in comparison to subjective global assessment (SGA). Anthropometry, body composition, and hand grip strength were evaluated. Results: According to PG-SGA global assessment categories, 39% (75) of 195 cancer patients were well nourished, 27% (53) were moderately malnourished and 34% (67) of patients were severely malnourished. Thai PG-SGA had a sensitivity of 99.1% and a specificity of 86.0% at predicting SGA classification. PG-SGA numerical scores were significantly different between well-nourished and malnourished groups (4.2 ± 2.4 Vs 16.3 ± 4.9; p < 0.001). The PG-SGA scores, nutritional status assessed by PG-SGA, and nutritional status assessed by SGA were correlated with weight, % weight loss in one month, body mass index, body fat, and hand grip strength (p < 0.001) respectively. Conclusions: Thai PG-SGA showed high sensitivity and good specificity in predicting malnutrition in Thai cancer patients. This tool demonstrated the correlations with anthropometric parameters, body composition, and muscle strength.

Immunohistochemical Evaluation of Ki-67 and Comparison with Clinicopathologic Factors in Breast Carcinomas

Abstract: Background: Patients primarily received tamoxifen based on their menopausal status due to the lack of immunohistochemistry. A recent study has shown that hormonal receptors were not correlated with menopausal status, and thus, indicating that they present limited therapeutic and prognostic significance in breast cancer management. This study aimed to evaluate Ki-67 value and analyze its association with clinicopathologic parameters in breast cancer patients. Methods: The formalin-fixed paraffin-embedded breast tissue blocks of 125 patients with primary breast carcinomas were subjected to immunohistochemical analysis using Ventana Benchmark® GX automated immunostainer. Analysis of variance and Chi-2 test were used to examine the relationship between Ki-67 and clinicopathologic variables. Results: The mean age of 125 patients included in the study was 47.7 years. The average score of Ki-67 was 56.0%. 84.8% of patients showed Ki-67 ≥ 14%. Mean scores of Ki-67 were correlated with grade (p = 0.006), PR (p = 0.026), histological type, ER, combined ER/RP, and molecular subtype (p < 0.001). Ki-67 was independent of HER2 (p = 0.402) and menopausal status (p = 0.471). The frequency of Ki-67 according to St Gallen 2011 was associated with histological type (p = 0.005), grade (p = 0.005), ER (p < 0.001), combined ER/PR (p = 0.004), and molecular subtype (p = 0.004). There was no significant relationship between the distribution of Ki-67 and the age of the patients (p = 0.859), menopausal status (p = 0.979), PR (p = 0.149), and HER2 (p = 0.597). Conclusion: Ki-67 is useful for treatment decisions in primary breast cancer patients. The high value of Ki-67 was associated with adverse clinicopathologic factors. The increased Ki-67 value should be carefully investigated in triple negative patients.

Over-Expression of Cyclooxygenase-2 in Colorectal Cancer Patients.

Abstract: Background: Colorectal carcinoma (CRC) is the most common neoplasm of the gastrointestinal tract. COX-2 plays an important role in CRC development and is a key target for the regression of colorectal tumorigenesis by nonsteroidal anti-inflammatory drugs. The present study was conducted to examine the relationship of the levels of COX-2 in CRC patients with the clinico-pathological parameters and also to assess its usefulness as a potential biomarker for diagnosis of CRC. Methods: Prior to surgery, 30 CRC patients were enrolled and the samples from colon tumors and surrounding tissues were taken after they underwent surgical intervention at PGIMER, Chandigarh. mRNA expression levels of COX-2 were examined in 30 CRC and adjacent normal colonic mucosa by quantitative polymerase chain reaction (qPCR). The expression of COX-2 was assessed by immunohistochemical method using rabbit polyclonal antibodies against human COX-2 protein. Results: The quantitative relative expression of COX-2 mRNA was observed to be significantly higher (p<0.05) in colorectal cancer tissues as compared to adjacent normal colon tissues. Also, female CRC patients showed significantly higher (p<0.009) expression of COX-2 mRNA vis-a-vis male colorectal cancer patients. This is the first study which has reported a direct relationship between COX-2 mRNA expressions in male colorectal cancer patients versus females. Further, immunohistochemistry of COX-2 confirmed the quantitative real time-PCR findings. Conclusion: Our study shows that COX-2 over expression in colorectal carcinoma patients is closely associated with clinico-pathological parameters and is more pronounced in males versus females. Further, COX-2 mRNA expression can serve as a potential biomarker for the diagnosis of CRC.

Antibacterial and Anticancer Activities of Fenugreek Seed Extract.

Abstract: This work is about the utilization of fenugreek seed as an antibacterial and anticancer agents. The antibacterial activity of fenugreek seed extract on six pathological bacteria strains were specified through conventional biochemical tests using the Vitek2 automated system and diffusion agar method. The anticancer activities of fenugreek seed extract, on MCF-7 breast cancer cells, liver cancer HCAM cells and the non-cancerous Vero cell lines, were investigated using colorimetric MTT assay. Results showed that the highest activity of the extract of the seed was found on Staphylococcus aureus and Pseudomonas aeruginosa (22 mm and 17 mm diameter of inhibition zones respectively). The seed extract showed proliferative inhibition on MCF-7 cell line at a concentration of 400 µg/ml and 72 h of the incubation period. This was accompanied by insignificant apoptosis or necrosis. The seed extract showed no anticancer effect on liver and Vero cell lines. This work emphasizes that fenugreek seed extract is a potential source of antibacterial and anticancer agents.

Prevalence of Intestinal Parasitic Infection in Cancer, Organ Transplant and Primary Immunodeficiency Patients in Tehran, Iran

Abstract: Background: Intestinal parasitic infection in immunodeficient patients especially those with impaired cellular immunity, like neoplasia, renal or heart transplant needs careful consideration. The objective of this study is to evaluate the prevalence of intestinal parasites in different group of patients including cancer patients; organ transplants recipients, and primary immunodeficiency patients. Methods: Stool samples from 190 patients including 80 patients with Primary Immunodeficiency, 85 cancer patients and 25 organ transplant recipients were collected; a direct examination with Phosphate buffered saline (PBS) and formalin ether concentration was performed. The DNA was extracted from parasitologically confirmed patients and nested PCR and sequencing was performed and new obtained sequences of Cryptosporidium parvum and Enterocytozoon bieneusi were compared with deposited ones. Results: In general, the prevalence of parasites was 26/80 (32.5%) in primary immunodeficiency, 22/85(25.9%) in cancer group, and 7/25 (28%) in organ transplant. The prevalence of intestinal parasitic infections in primary immunodeficiency patients were Blastocystis hominis 13 (16.2%), Giardia lamblia 10 (12.5%), Cryptosporidium 1(1.2%), Chilomastix mesnilii 1 (1.2%), Dientamoeba fragilis 1(1.2%). Of 25 organ transplants, 6 (24%) Cryptosporidium sp were found, all of which were confirmed as Cryptosporidium parvum and one case of Microspora in a heart transplant recipient was confirmed as Enterocytozoon bieneusi by PCR sequencing. The predominant intestinal parasitic infection in cancer patients was 19 (22.3%) Blastocystis hominis followed by two (2.3%) Giardia lamblia and one Dientamoeba fragilis 1 (1.1%). Conclusion: The high rate of infection with Blastocystis hominis was found in cancer patients especially colorectal cancer patients, so careful consideration should be given by physicians. Cryptosporidium sp was found to be the major cause of parasitic intestinal infection in patients with organ transplant compared to primary immunodeficiency patients; so transplant recipients undergoing immunosuppressive therapy should be considered as a risk group for acquiring microsporidiosis and Cryptosporidium infection.

Upregulation of Circulating MiR-21 Expression as a Potential Biomarker for Therapeutic Monitoring and Clinical Outcome in Breast Cancer

Abstract: Background: Aberrant patterns of microRNA expression have been highlighted as a potential clinical biomarker in breast cancer as the most frequent cancer among women that contributes nearly a quarter of total cancer incidence in 2018. Upregulation of microRNA-21 (miR-21) is associated with adverse clinical outcomes in breast cancer. However, the use of circulating free miR-21 as a non-invasive biomarker for diagnosis and therapeutic monitoring in breast cancer is not well established. We quantified the levels of circulating miR-21 expression and analyzed their correlation with clinicopathological variables and progression-free survival. Materials and Methods: This initial study included a cohort of 102 breast cancer patients of different subtypes and clinicat stages. We also included 15 unrelated healthy women. Venous blood from patients was collected at diagnosis and after treatment of surgery and chemotherapy. MiR-21 expression was quantified from total RNA fraction isolated from patient’s plasma. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to analyzed miR-21 expression. Results: Expression of circulating miR-21 was significantly elevated in breast cancer patients compared to healthy women (median miR-21 expression levels were 7.67±2.2 and 1.28±0.16, respectively; p<0.0001). Significant reduction of miR-21 expression was observed in breast cancer patients after completion of surgery and chemotherapy (median miR-21 expression levels were 7.67±2.2 at diagnosis and 2.16±1.28 after treatment, respectively; p<0.0001). MiR-21 expression was higher in breast cancer patients younger than 40-year-old but was not significantly different according to different histopathological grades and clinical stages at diagnosis. Patients with upregulation of circulating miR-21 were associated with poor progression-free survival (median survival 72 vs 86 weeks, respectively; log-rank (Mantel-Cox) test, p=0.049). Conclusion: MiR-21 expression was upregulated in breast cancer patients and might serve as a therapeutic monitoring marker.

An In silico Approach to Identify High Affinity Small Molecule Targeting m-TOR Inhibitors for the Clinical Treatment of Breast Cancer

Abstract: Breast cancer is the most frequent malignancy among women. It is a heterogeneous disease with different subtypes defined by its hormone receptor. A hormone receptor is mainly concerned with the progression of the PI3K/AKT/ mTOR pathway which is often dysregulated in breast cancer. This is a major signaling pathway that controls the activities such as cell growth, cell division, and cell proliferation. The present study aims to suppress mTOR protein by its various inhibitors and to select one with the highest binding affinity to the receptor protein. Out of 40 inhibitors of mTOR against breast cancer, SF1126 was identified to have the best docking score of -8.705, using Schrodinger Suite which was further subjected for high throughput screening to obtain best similar compound using Lipinski’s filters. The compound obtained after virtual screening, ID: ZINC85569445 is seen to have the highest affinity with the target protein mTOR. The same result based on the binding free energy analysis using MM-GBSA showed that the compound ZINC85569445 to have the the highest binding free energy. The next study of interaction between the ligand and receptor protein with the pharmacophore mapping showed the best conjugates, and the ZINC85569445 can be further studied for future benefits of treatment of breast cancer.

Deep Convolution Neural Network for Malignancy Detection and Classification in Microscopic Uterine Cervix Cell Images.

Abstract: Automated Pap smear cervical screening is one of the most effective imaging based cancer detection tools used for categorizing cervical cell images as normal and abnormal. Traditional classification methods depend on hand-engineered features and show limitations in large, diverse datasets. Effective feature extraction requires an efficient image preprocessing and segmentation, which remains prominent challenge in the field of Pathology. In this paper, a deep learning concept is used for cell image classification in large datasets. Methods: This relatively proposed novel method, combines abstract and complicated representations of data acquired in a hierarchical architecture. Convolution Neural Network (CNN) learns meaningful kernels that simulate the extraction of visual features such as edges, size, shape and colors in image classification. A deep prediction model is built using such a CNN network to classify the various grades of cancer: normal, mild, moderate, severe and carcinoma. It is an effective computational model which uses multiple processing layers to learn complex features. A large dataset is prepared for this study by systematically augmenting the images in Herlev dataset. Result: Among the three sets considered for the study, the first set of single cell enhanced original images achieved an accuracy of 94.1% for 5 class, 96.2% for 4 class, 94.8% for 3 class and 95.7% for 2 class problems. The second set includes contour extracted images showed an accuracy of 92.14%, 92.9%, 94.7% and 89.9% for 5, 4, 3 and 2 class problems. The third set of binary images showed 85.07% for 5 class, 84% for 4 class, 92.07% for 3 class and highest accuracy of 99.97% for 2 class problems. Conclusion: The experimental results of the proposed model showed an effective classification of different grades of cancer in cervical cell images, exhibiting the extensive potential of deep learning in Pap smear cell image classification