High frequency of immature dendritic cells and altered in situ production of interleukin-4 and tumor necrosis factor-alpha in lung cancer

Introduction Antigen-presenting cells, like dendritic cells (DCs) and macrophages, play a significant role in the induction of an immune response and an imbalance in the proportion of macrophages, immature and mature DCs within the tumor could affect significantly the immune response to cancer. DCs and macrophages can differentiate from monocytes, depending on the milieu, where cytokines, like interleukin (IL)-4 and granulocyte-macrophage colony-stimulating factor (GM-CSF) induce DC differentiation and tumor necrosis factor (TNF)-alpha induce DC maturation. Thus, the aim of this work was to analyze by immunohistochemistry the presence of DCs (S100+ or CD1a+), macrophages (CD68+), IL-4 and TNF-alpha within the microenvironment of primary lung carcinomas. Results Higher frequencies of both immature DCs and macrophages were detected in the tumor-affected lung, when compared to the non-affected lung. Also, TNF-alpha-positive cells were more frequent, while IL-4-positive cells were less frequent in neoplastic tissues. This decreased frequency of mature DCs within the tumor was further confirmed by the lower frequency of CD14-CD80+ cells in cell suspensions obtained from the same lung tissues analyzed by flow cytometry. Conclusion These data are discussed and interpreted as the result of an environment that does not oppose monocyte differentiation into DCs, but that could impair DC maturation, thus affecting the induction of effective immune responses against the tumor.

Investigation of a new GRASP-based clustering algorithm applied to biological data

A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

Multi-objective clustering ensemble for gene expression data analysis

In this paper, we present an algorithm for cluster analysis that integrates aspects from cluster ensemble and multi-objective clustering. The algorithm is based on a Pareto-based multi-objective genetic algorithm, with a special crossover operator, which uses clustering validation measures as objective functions. The algorithm proposed can deal with data sets presenting different types of clusters, without the need of expertise in cluster analysis. its result is a concise set of partitions representing alternative trade-offs among the objective functions. We compare the results obtained with our algorithm, in the context of gene expression data sets, to those achieved with multi-objective Clustering with automatic K-determination (MOCK). the algorithm most closely related to ours. (C) 2009 Elsevier B.V. All rights reserved.

Severe novel influenza A (H1N1) infection in cancer patients

Patients and methods: Clinical data from all patients admitted with acute respiratory failure due to novel viral H1N1 infection were reviewed. Lung tissue was submitted for viral and bacteriological analyses by real-time RT-PCR, and autopsy was conducted on all patients who died. Results: Eight patients were admitted, with ages ranging from 55 to 65 years old. There were five patients with solid organ tumors (62.5%) and three with hematological malignancies (37.5%). Five patients required mechanical ventilation and all died. Four patients had bacterial bronchopneumonia. All deaths occurred due to multiple organ failure. A milder form of lung disease was present in the three cases who survived. Lung tissue analysis was performed in all patients and showed diffuse alveolar damage in most patients. Other lung findings were necrotizing bronchiolitis or extensive hemorrhage. Conclusions: H1N1 viral infection in patients with cancer can cause severe illness, resulting in acute respiratory distress syndrome and death. More data are needed to identify predictors of unfavorable evolution in these patients.

Effects of Raloxifene on Ki-67 and CD34 Antigen Expression in Breast Cancer

Background: The aim of this study was to evaluate the effect of raloxifene on CD34 and Ki-67 antigen expression in breast cancer specimens from postmenopausal women. Methods: Sixteen postmenopausal patients with operable, stage II (>= 3 cm), estrogen receptor-positive breast cancer, who took 60 mg of raloxifene daily for 28 days, participated in this study. Immunohistochemistry was carried out in tumor samples prior to and following raloxifene treatment to evaluate CD34 and Ki-67 protein expression. Angiogenesis was quantified in 10 randomly selected fields per slide, and Ki-67-stained nuclei were counted in 1,000 cells per slide using an image capture and analysis system with 400 ! magnification. Student`s t test for paired samples was used for the statistical analysis of data. Statistical significance was established at p < 0.05. Results: The mean number of microvessels was 44.44 +/- 3.54 prior to raloxifene therapy and 22.63 +/- 1.61 following therapy (p < 0.001), and the mean percentage of Ki-67-stained nuclei was 19.28 +/- 8 1.61 and 12.13 +/- 8 1.48 prior to and following raloxifene treatment, respectively (p < 0.001). Conclusion: Raloxifene significantly reduces CD34 and Ki-67 protein expression in breast carcinoma in postmenopausal women. Copyright (C) 2008 S. Karger AG, Basel

Comparison of three vascular endothelial markers in the evaluation of microvessel density in breast cancer

Purpose: To evaluate the microvessel density by comparing the performance of anti-factor VIII-related antigen, anti-CD31 and, anti-CD34 monoclonal antibodies in breast cancer. Methods: Twenty-three postmenopausal women diagnosed with Stage II breast cancer submitted to definitive surgical treatment were evaluated. The monoclonal antibodies used were anti-factor VIII, anti-CD31 and anti-CD34. Microvessels were counted in the areas of highest microvessel density in ten random fields (200 x). The data were analyzed using the Kruskal-Wallis nonparametric test (p < 0.05). Results: Mean microvessel densities with anti-factor VIII, anti-CD31 and anti-CD34 were 4.16 +/- 0.38, 4.09 +/- 0.23 and 6.59 +/- 0.42, respectively. Microvessel density as assessed by anti-CD34 was significantly greater than that detected by anti-CD31 or anti-factor VIII (p < 0.0001). There was no statistically significant difference between anti-CD31 and anti-factor VIII (p = 0.4889). Conclusion: The density of stained microvessels was greater and staining was more intense with anti-CD34 compared to anti-CD31 and anti-factor VII-related antigen.

Human papillomavirus type 16 variants in cervical cancer from an admixtured population in Brazil

Several studies indicate that molecular variants of HPV-16 have different geographic distribution and risk associated with persistent infection and development of high-grade cervical lesions. In the present study, the frequency of HPV-16 variants was determined in 81 biopsies from women with cervical intraepithelial neoplasia grade III or invasive cervical cancer from the city of Belem, Northern Brazil. Host DNAs were also genotyped in order to analyze the ethnicity-related distribution of these variants. Ninie different HPV-16 LCR variants belonging to four phylogenetic branches were identified. Among these, two new isolates were characterized. The most prevalent HPV-16 variant detected was the Asian-American B-2,followed by the European B-12 and the European prototype. Infections by multiple variants were observed in both invasive cervical cancer and cervical intraepithelial neoplasia grade III cases. The analysis of a specific polymorphism within the E6 viral gene was performed in a subset of 76 isolates. The E6-350G polymorphism was significantly more frequent in Asian-American variants. The HPV-16 variability detected followed the same pattern of the genetic ancestry observed in Northern Brazil, with European, Amerindian and African roots. Although African ancestry was higher among women infected by the prototype, no correlation between ethnical origin and HPV-16 variants was found. These results corroborate previous data showing a high frequency of Asian-American variants in cervical neoplasia among women with multiethnic origin.