WorldWideScience

Sample records for cancer network study

  1. The Rare Cancer Network: ongoing studies and future strategy

    Directory of Open Access Journals (Sweden)

    Mahmut Ozsahin

    2014-08-01

    Full Text Available The Rare Cancer Network (RCN was formed in the early 1990’s to create a global network that could pool knowledge and resources in the studies of rare malignancies whose infrequency prevented both their study with prospective clinical trials. To date, the RCN has initiated 74 studies resulting in 46 peer reviewed publications. The First International Symposium of the Rare Cancer Network took place in Nice in March of 2014. Status updates and proposals for new studies were heard for fifteen topics. Ongoing studies continue for cardiac sarcomas, thyroid cancers, glomus tumors, and adult medulloblastomas. New proposals were presented at the symposium for primary hepatic lymphoma, solitary fibrous tumors, Rosai-Dorfman disease, tumors of the ampulla of Vater, salivary gland tumors, anorectal melanoma, midline nuclear protein in testes carcinoma, pulmonary lymphoepithelioma-like carcinoma, adenoid cystic carcinoma of the trachea, osteosarcomas of the mandible, and extra-cranial hemangiopericytoma. This manuscript presents the abstracts of those proposals and updates on ongoing studies, as well a brief summary of the vision and future of the RCN.

  2. Bladder Cancer Advocacy Network

    Science.gov (United States)

    ... Grants Bladder Cancer Think Tank Bladder Cancer Research Network Bladder Cancer Genomics Consortium Get Involved Ways to ... us? Who we are The Bladder Cancer Advocacy Network (BCAN) is a community of patients, caregivers, survivors, ...

  3. Prostate Cancer Biorepository Network

    Science.gov (United States)

    2017-10-01

    AWARD NUMBER: W81XWH-14-2-0185 TITLE: Prostate Cancer Biorepository Network PRINCIPAL INVESTIGATOR: Jonathan Melamed, MD CONTRACTING ORGANIZATION...AND SUBTITLE 5a. CONTRACT NUMBER Prostate Cancer Biorepository Network 5b. GRANT NUMBER W81XWH-14-2-0185 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...infrastructure and operations of the Prostate Cancer Biorepository Network (PCBN). The aim of the PCBN is to provide prostate researchers with high-quality

  4. International Cancer Screening Network

    Science.gov (United States)

    The International Cancer Screening Network promotes evidence-based cancer screening implementation and evaluation with cooperation from multilateral organizations around the globe. Learn more about how ICSN aims to reduce the global burden of cancer by supporting research and international collaboration.

  5. Social support networks and depression of women suffering from early-stage breast cancer: a case control study.

    Science.gov (United States)

    Gagliardi, Cristina; Vespa, Anna; Papa, Roberta; Mariotti, Carlo; Cascinu, Stefano; Rossini, Simonetta

    2009-01-01

    The aim of this study was to investigate the areas of depression, anxiety, and social support using the structural model of the social network. By comparing the networks of two samples of breast cancer sufferers and healthy control participants, it was possible to identify differences in their relationships, in the shape of the networks themselves, and in the levels of depression and anxiety. Women with breast cancer described smaller and denser networks, including mainly kins whereas the healthy women included more friends, coworkers, and leisure companions. The levels of anxiety and depression were higher in women with breast cancer. Social network and social support measure correlated differently with depression and anxiety in the two groups.

  6. Introduction: Cancer Gene Networks.

    Science.gov (United States)

    Clarke, Robert

    2017-01-01

    Constructing, evaluating, and interpreting gene networks generally sits within the broader field of systems biology, which continues to emerge rapidly, particular with respect to its application to understanding the complexity of signaling in the context of cancer biology. For the purposes of this volume, we take a broad definition of systems biology. Considering an organism or disease within an organism as a system, systems biology is the study of the integrated and coordinated interactions of the network(s) of genes, their variants both natural and mutated (e.g., polymorphisms, rearrangements, alternate splicing, mutations), their proteins and isoforms, and the organic and inorganic molecules with which they interact, to execute the biochemical reactions (e.g., as enzymes, substrates, products) that reflect the function of that system. Central to systems biology, and perhaps the only approach that can effectively manage the complexity of such systems, is the building of quantitative multiscale predictive models. The predictions of the models can vary substantially depending on the nature of the model and its inputoutput relationships. For example, a model may predict the outcome of a specific molecular reaction(s), a cellular phenotype (e.g., alive, dead, growth arrest, proliferation, and motility), a change in the respective prevalence of cell or subpopulations, a patient or patient subgroup outcome(s). Such models necessarily require computers. Computational modeling can be thought of as using machine learning and related tools to integrate the very high dimensional data generated from modern, high throughput omics technologies including genomics (next generation sequencing), transcriptomics (gene expression microarrays; RNAseq), metabolomics and proteomics (ultra high performance liquid chromatography, mass spectrometry), and "subomic" technologies to study the kinome, methylome, and others. Mathematical modeling can be thought of as the use of ordinary

  7. Subjective cognitive impairment and brain structural networks in Chinese gynaecological cancer survivors compared with age-matched controls: a cross-sectional study.

    Science.gov (United States)

    Zeng, Yingchun; Cheng, Andy S K; Song, Ting; Sheng, Xiujie; Zhang, Yang; Liu, Xiangyu; Chan, Chetwyn C H

    2017-11-28

    Subjective cognitive impairment can be a significant and prevalent problem for gynaecological cancer survivors. The aims of this study were to assess subjective cognitive functioning in gynaecological cancer survivors after primary cancer treatment, and to investigate the impact of cancer treatment on brain structural networks and its association with subjective cognitive impairment. This was a cross-sectional survey using a self-reported questionnaire by the Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) to assess subjective cognitive functioning, and applying DTI (diffusion tensor imaging) and graph theoretical analyses to investigate brain structural networks after primary cancer treatment. A total of 158 patients with gynaecological cancer (mean age, 45.86 years) and 130 age-matched non-cancer controls (mean age, 44.55 years) were assessed. Patients reported significantly greater subjective cognitive functioning on the FACT-Cog total score and two subscales of perceived cognitive impairment and perceived cognitive ability (all p values impairment (r = -0.388, p = 0.034). When compared with non-cancer controls, a considerable proportion of gynaecological cancer survivors may exhibit subjective cognitive impairment. This study provides the first evidence of brain structural network alteration in gynaecological cancer patients at post-treatment, and offers novel insights regarding the possible neurobiological mechanism of cancer-related cognitive impairment (CRCI) in gynaecological cancer patients. As primary cancer treatment can result in a more random organisation of structural brain networks, this may reduce brain functional specificity and segregation, and have implications for cognitive impairment. Future prospective and longitudinal studies are needed to build upon the study findings in order to assess potentially relevant clinical and psychosocial variables and brain network measures, so as to more accurately understand the

  8. Cancer association study of aminoacyl-tRNA synthetase signaling network in glioblastoma.

    Directory of Open Access Journals (Sweden)

    Yong-Wan Kim

    Full Text Available Aminoacyl-tRNA synthetases (ARSs and ARS-interacting multifunctional proteins (AIMPs exhibit remarkable functional versatility beyond their catalytic activities in protein synthesis. Their non-canonical functions have been pathologically linked to cancers. Here we described our integrative genome-wide analysis of ARSs to show cancer-associated activities in glioblastoma multiforme (GBM, the most aggressive malignant primary brain tumor. We first selected 23 ARS/AIMPs (together referred to as ARSN, 124 cancer-associated druggable target genes (DTGs and 404 protein-protein interactors (PPIs of ARSs using NCI's cancer gene index. 254 GBM affymetrix microarray data in The Cancer Genome Atlas (TCGA were used to identify the probe sets whose expression were most strongly correlated with survival (Kaplan-Meier plots versus survival times, log-rank t-test <0.05. The analysis identified 122 probe sets as survival signatures, including 5 of ARSN (VARS, QARS, CARS, NARS, FARS, and 115 of DTGs and PPIs (PARD3, RXRB, ATP5C1, HSP90AA1, CD44, THRA, TRAF2, KRT10, MED12, etc. Of note, 61 survival-related probes were differentially expressed in three different prognosis subgroups in GBM patients and showed correlation with established prognosis markers such as age and phenotypic molecular signatures. CARS and FARS also showed significantly higher association with different molecular networks in GBM patients. Taken together, our findings demonstrate evidence for an ARSN biology-dominant contribution in the biology of GBM.

  9. A comparative study of breast cancer diagnosis based on neural network ensemble via improved training algorithms.

    Science.gov (United States)

    Azami, Hamed; Escudero, Javier

    2015-08-01

    Breast cancer is one of the most common types of cancer in women all over the world. Early diagnosis of this kind of cancer can significantly increase the chances of long-term survival. Since diagnosis of breast cancer is a complex problem, neural network (NN) approaches have been used as a promising solution. Considering the low speed of the back-propagation (BP) algorithm to train a feed-forward NN, we consider a number of improved NN trainings for the Wisconsin breast cancer dataset: BP with momentum, BP with adaptive learning rate, BP with adaptive learning rate and momentum, Polak-Ribikre conjugate gradient algorithm (CGA), Fletcher-Reeves CGA, Powell-Beale CGA, scaled CGA, resilient BP (RBP), one-step secant and quasi-Newton methods. An NN ensemble, which is a learning paradigm to combine a number of NN outputs, is used to improve the accuracy of the classification task. Results demonstrate that NN ensemble-based classification methods have better performance than NN-based algorithms. The highest overall average accuracy is 97.68% obtained by NN ensemble trained by RBP for 50%-50% training-test evaluation method.

  10. Social networks, social support, and burden in relationships, and mortality after breast cancer diagnosis in the Life After Breast Cancer Epidemiology (LACE) study.

    Science.gov (United States)

    Kroenke, Candyce H; Quesenberry, Charles; Kwan, Marilyn L; Sweeney, Carol; Castillo, Adrienne; Caan, Bette J

    2013-01-01

    Larger social networks have been associated with lower breast cancer mortality. The authors evaluated how levels of social support and burden influenced this association. We included 2,264 women from the Life After Cancer Epidemiology study who were diagnosed with early-stage, invasive breast cancer between 1997 and 2000, and provided data on social networks (spouse or intimate partner, religious/social ties, volunteering, time socializing with friends, and number of first-degree female relatives), social support, and caregiving. 401 died during a median follow-up of 10.8 years follow-up with 215 from breast cancer. We used delayed entry Cox proportional hazards regression to evaluate associations. In multivariate-adjusted analyses, social isolation was unrelated to recurrence or breast cancer-specific mortality. However, socially isolated women had higher all-cause mortality (HR = 1.34, 95 % CI: 1.03-1.73) and mortality from other causes (HR = 1.79, 95 % CI: 1.19-2.68). Levels of social support and burden modified associations. Among those with low, but not high, levels of social support from friends and family, lack of religious/social participation (HR = 1.58, 95 % CI: 1.07-2.36, p = 0.02, p interaction = 0.01) and lack of volunteering (HR = 1.78, 95 % CI: 1.15-2.77, p = 0.01, p interaction = 0.01) predicted higher all-cause mortality. In cross-classification analyses, only women with both small networks and low levels of support (HR = 1.61, 95 % CI: 1.10-2.38) had a significantly higher risk of mortality than women with large networks and high levels of support; women with small networks and high levels of support had no higher risk of mortality (HR = 1.13, 95 % CI: 0.74-1.72). Social networks were also more important for caregivers versus noncaregivers. Larger social networks predicted better prognosis after breast cancer, but associations depended on the quality and burden of family relationships.

  11. Prognostic factors in urothelial renal pelvis and ureter tumors: a multicenter rare cancer network study

    International Nuclear Information System (INIS)

    Ozsahin, M.; Zouhair, A.; Villa, S.; Storme, G.; Chauvet, B.; Taussky, D.; Houtte, P. van; Ries, G.; Bontemps, P.; Coucke, P.; Mirimanoff, R.O.

    1997-01-01

    Purpose: To assess the prognostic factors and the outcome in patients with transitional-cell carcinoma of the renal pelvis and/or ureter. Materials and Methods: A series of 138 patients treated between 1971 and 1996 for transitional-cell carcinoma of the renal pelvis and/or ureter was collected in a retrospective multicenter study of the Rare Cancer Network. Twelve patients with distant metastases were excluded from the statistical evaluation. In the remaining 126 patients, median age was 66 years (range: 41-87). The male to female ratio was 2.5 ((90(36))). All but 3 patients underwent a radical surgery: nephroureterectomy (n = 71), nephroureterectomy and lymphadenectomy (n = 20), nephroureterectomy and partial bladder resection or transurethral resection (n = 20), nephrectomy (n = 8), and ureterectomy (n = 4). There were 6 stage pTa, 22 pT1, 17 pT2, 37 pT3, 37 pT4, and 7 pTx tumors. The pN-stage distribution was as follows: 69 pN0, 8 pN1, 14 pN2, 4 pN3, and 31 pNx. Sixty-one percent (n = 77) of the tumors were located in the renal pelvis, and 21% (n = 27) in the ureter. Renal pelvis and ureter localization was present together in 22 (17%) patients. There were 4 grade 1, 37 grade 2, 42 grade 3 tumors (grade was not registered in 43). Following surgery, microscopic (n = 16) or macroscopic (n = 17) tumor rest was detected in 33 patients. Postoperative radiotherapy was given in 45 (36%) patients with a median total dose of 50 Gy (range: 20-66) in median 25 fractions (range: 4-33). Adjuvant systemic chemotherapy was administered in 12 (10%) patients. The median follow-up period was 39 months (range: 5-220). Results: In a median period of 9 months (range: 1-141), 66% (n = 81) of the patients relapsed (local in 34, locoregional in 7, regional in 16, and distant in 24). The 5- and 10-year overall survival (Kaplan-Meier product-limit estimates) was respectively 29% (± 5) and 19% (± 5) in all patients. In univariate analyses (logrank test), statistically significant

  12. [Scientific production and cancer-related collaboration networks in Peru 2000-2011: a bibliometric study in Scopus and Science Citation Index].

    Science.gov (United States)

    Mayta-Tristán, Percy; Huamaní, Charles; Montenegro-Idrogo, Juan José; Samanez-Figari, César; González-Alcaide, Gregorio

    2013-03-01

    A bibliometric study was carried out to describe the scientific production on cancer written by Peruvians and published in international health journals, as well as to assess the scientific collaboration networks. It included articles on cancer written in Peru between the years 2000 and 2011 and published in health journals indexed in SCOPUS or Science Citation Index Expanded. In the 358 articles identified, an increase in the production was seen, from 4 articles in 2000 to 57 in 2011.The most studied types were cervical cancer (77 publications); breast cancer (53), and gastric cancer (37). The National Institute of Neoplastic Diseases (INEN) was the most productive institution (121 articles) and had the highest number of collaborations (180 different institutions). 52 clinical trials were identified, 29 of which had at least one author from INEN. We can conclude that, cancer research is increasing in Peru, the INEN being the most productive institution, with an important participation in clinical trials.

  13. Comment on 'Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study'.

    Science.gov (United States)

    Valdes, Gilmer; Interian, Yannet

    2018-03-15

    The application of machine learning (ML) presents tremendous opportunities for the field of oncology, thus we read 'Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study' with great interest. In this article, the authors used state of the art techniques: a pre-trained convolutional neural network (VGG-16 CNN), transfer learning, data augmentation, drop out and early stopping, all of which are directly responsible for the success and the excitement that these algorithms have created in other fields. We believe that the use of these techniques can offer tremendous opportunities in the field of Medical Physics and as such we would like to praise the authors for their pioneering application to the field of Radiation Oncology. That being said, given that the field of Medical Physics has unique characteristics that differentiate us from those fields where these techniques have been applied successfully, we would like to raise some points for future discussion and follow up studies that could help the community understand the limitations and nuances of deep learning techniques.

  14. Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study

    Science.gov (United States)

    Zhen, Xin; Chen, Jiawei; Zhong, Zichun; Hrycushko, Brian; Zhou, Linghong; Jiang, Steve; Albuquerque, Kevin; Gu, Xuejun

    2017-11-01

    Better understanding of the dose-toxicity relationship is critical for safe dose escalation to improve local control in late-stage cervical cancer radiotherapy. In this study, we introduced a convolutional neural network (CNN) model to analyze rectum dose distribution and predict rectum toxicity. Forty-two cervical cancer patients treated with combined external beam radiotherapy (EBRT) and brachytherapy (BT) were retrospectively collected, including twelve toxicity patients and thirty non-toxicity patients. We adopted a transfer learning strategy to overcome the limited patient data issue. A 16-layers CNN developed by the visual geometry group (VGG-16) of the University of Oxford was pre-trained on a large-scale natural image database, ImageNet, and fine-tuned with patient rectum surface dose maps (RSDMs), which were accumulated EBRT  +  BT doses on the unfolded rectum surface. We used the adaptive synthetic sampling approach and the data augmentation method to address the two challenges, data imbalance and data scarcity. The gradient-weighted class activation maps (Grad-CAM) were also generated to highlight the discriminative regions on the RSDM along with the prediction model. We compare different CNN coefficients fine-tuning strategies, and compare the predictive performance using the traditional dose volume parameters, e.g. D 0.1/1/2cc, and the texture features extracted from the RSDM. Satisfactory prediction performance was achieved with the proposed scheme, and we found that the mean Grad-CAM over the toxicity patient group has geometric consistence of distribution with the statistical analysis result, which indicates possible rectum toxicity location. The evaluation results have demonstrated the feasibility of building a CNN-based rectum dose-toxicity prediction model with transfer learning for cervical cancer radiotherapy.

  15. Decoding network dynamics in cancer

    DEFF Research Database (Denmark)

    Linding, Rune

    2014-01-01

    Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language and with an accur......Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language...... and with an accuracy that parallels our characterisation of other physical systems such as Jumbo-jets. Decades of targeted molecular and biological studies have led to numerous pathway models of developmental and disease related processes. However, so far no global models have been derived from pathways, capable...

  16. Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

    Science.gov (United States)

    Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-06

    Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

  17. Legacy of the Pacific Islander cancer control network.

    Science.gov (United States)

    Hubbell, F Allan; Luce, Pat H; Afeaki, William P; Cruz, Lee Ann C; McMullin, Juliet M; Mummert, Angelina; Pouesi, June; Reyes, Maria Lourdes; Taumoepeau, Leafa Tuita; Tu'ufuli, Galeai Moali'itele; Wenzel, Lari

    2006-10-15

    The groundwork for the Pacific Islander cancer control network (PICCN) began in the early 1990s with a study of the cancer control needs of American Samoans. The necessity for similar studies among other Pacific Islander populations led to the development of PICCN. The project's principal objectives were to increase cancer awareness and to enhance cancer control research among American Samoans, Tongans, and Chamorros. PICCN was organized around a steering committee and 6 community advisory boards, 2 from each of the targeted populations. Membership included community leaders, cancer control experts, and various academic and technical organizations involved with cancer control. Through this infrastructure, the investigators developed new culturally sensitive cancer education materials and distributed them in a culturally appropriate manner. They also initiated a cancer control research training program, educated Pacific Islander students in this field, and conducted pilot research projects. PICCN conducted nearly 200 cancer awareness activities in its 6 study sites and developed cancer educational materials on prostate, colorectal, lung, breast, and cervical cancer and tobacco control in the Samoan, Tongan, and Chamorro languages. PICCN trained 9 students who conducted 7 pilot research projects designed to answer important questions regarding the cancer control needs of Pacific Islanders and to inform interventions targeting those needs. The legacy of PICCN lies in its advancement of improving cancer control among Pacific Islanders and setting the stage for interventions that will help to eliminate cancer-related health disparities. Cancer 2006. (c) 2006 American Cancer Society.

  18. The association between active participation in a sports club, physical activity and social network on the development of lung cancer in smokers: a case-control study

    Directory of Open Access Journals (Sweden)

    Schmidt Anna

    2012-01-01

    Full Text Available Abstract Background This study analyses the effect of active participation in a sports club, physical activity and social networks on the development of lung cancer in patients who smoke. Our hypothesis is that study participants who lack social networks and do not actively participate in a sports club are at a greater risk for lung cancer than those who do. Methods Data for the study were taken from the Cologne Smoking Study (CoSmoS, a retrospective case-control study examining potential psychosocial risk factors for the development of lung cancer. Our sample consisted of n = 158 participants who had suffered lung cancer (diagnosis in the patient document and n = 144 control group participants. Both groups had a history of smoking. Data on social networks were collected by asking participants whether they participated in a sports club and about the number of friends and relatives in their social environment. In addition, sociodemographic data (gender, age, education, marital status, residence and religion, physical activity and data on pack years (the cumulative number of cigarettes smoked by an individual, calculated by multiplying the number of cigarettes smoked per day by the number of years the person has smoked divided by 20 were collected to control for potential confounders. Logistic regression was used for the statistical analysis. Results The results reveal that participants who are physically active are at a lower risk of lung cancer than those who are not (adjusted OR = 0.53*; CI = 0.29-0.97. Older age and lower education seem also to be risk factors for the development of lung cancer. The extent of smoking, furthermore, measured by pack years is statistically significant. Active participation in a sports club, number of friends and relatives had no statistically significant influence on the development of the cancer. Conclusions The results of the study suggest that there is a lower risk for physically active participants to develop

  19. Human cancer protein-protein interaction network: a structural perspective.

    Directory of Open Access Journals (Sweden)

    Gozde Kar

    2009-12-01

    Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

  20. Treatment results of 165 pediatric patients with non-metastatic nasopharyngeal carcinoma: A Rare Cancer Network study

    International Nuclear Information System (INIS)

    Ozyar, Enis; Selek, Ugur; Laskar, Siddihartha; Uzel, Omer; Anacak, Yavuz; Ben-Arush, Miriam; Polychronopoulou, Sopiha; Akman, Fadime; Wolden, Suzanne L.; Sarihan, Suereyya; Miller, Robert C.; Ozsahin, Mahmut; Abacioglu, Ufuk; Martin, Margarita; Caloglu, Murat; Scandolaro, Luciano; Szutowicz, Eva; Atahan, Ibtisam Lale

    2006-01-01

    Purpose: This Rare Cancer Network (RCN) study was performed in pediatric nasopharyngeal carcinoma (PNPC) patients to evaluate the optimal dose of radiotherapy and to determine prognostic factors. Patients and Methods: The study included 165 patients with the diagnosis of PNPC treated between 1978 and 2003. The median age was 14 years. There were 3 (1.8%) patients with stage I, 1 (0.6%) with IIA, 10 (6.1%) with IIB, 60 (36.4%) with III, 44 (26.7%) with IVA, and 47 (29%) with IVB disease. While 21 (12.7%) patients were treated with radiotherapy (RT) alone, 144 (87.3%) received chemotherapy and RT. The median follow-up time was 48 months. Results: The actuarial 5-year overall survival (OS) was 77.4% (95% CI: 70.06-84.72), whereas the actuarial 5-year disease-free survival (DFS) rate was 68.8% (95% CI: 61.33-76.31). In multivariate analysis, unfavorable factors were age >14 years for LRC (p = 0.04); male gender for DMFS (p = 0.03); T3/T4 disease for LRFS (p = 0.01); and N3 disease for DFS (p = 0.002) and OS (p = 0.002); EBRT dose of less than 66 Gy for LRFS (p = 0.02) and LRRFS (p = 0.0028); and patients treated with RT alone for LRFS (p = 0.0001), LRRFS (p = 0.007) and DFS (p = 0.02). Conclusion: Our results support the current practice of using combined radiation and chemotherapy for optimal treatment of NPC. However, research should be encouraged in an attempt to reduce the potential for long-term sequelae in pediatric patients given their relatively favorable prognosis and potential for longevity

  1. Outcome and prognostic factors in breast sarcoma: A multicenter study from the rare cancer network

    International Nuclear Information System (INIS)

    Bousquet, Guilhem; Confavreux, Cyril; Magne, Nicolas; Tunon de Lara, Christine; Poortmans, Philip; Senkus, Elzbieta; Lafontan, Brigitte de; Bolla, Michel; Largillier, Remy; Lagneau, Edouard; Kadish, Sidney; Lemanski, Claire; Ozsahin, Mahmut; Belkacemi, Yazid

    2007-01-01

    Background and purpose: Breast sarcoma (BS) is a rare tumour. While surgical resection is the primary treatment, the role of radiation therapy (RT) and chemotherapy remains unclear. This study aimed at defining prognostic factors and treatment strategies. Materials and methods: Data from 103 patients treated between 1976 and 2002 were collected. The median age was 55 years (range: 13-86); the median histological tumour size was 4.45 cm (range: 0.8-22). There were 42 angiosarcomas. Surgery consisted of wide excision in 34 cases, and total mastectomy in 69 cases. A total dose of 50 Gy in 25 fractions was delivered in 50 patients. At the completion of treatment, 89 patients had no residual tumour. Results: After a median follow-up of 64 months, 56 patients developed recurrent disease: 38 presented a local relapse and 37 developed distant metastases. The 5-year disease-free survival (DFS) and overall survival (OS) were 44% (95% confidence interval [CI], 39-49%) and 55% (95% CI, 50-60%), respectively. In multivariate analysis, favourable prognostic factors for better local control were: no residual tumour after treatment, no cellular pleomorphism, and histology other than angiosarcoma. For DFS, the five favourable prognostic factors were non-menopausal status, no residual tumour after treatment, non-angiosarcoma histology, absence of tumour necrosis, and grade 1-2 histology. Conclusion: While angiosarcoma has the worst prognosis, the outcome of the other types of sarcomas may be worsened by residual tumour after loco-regional treatment and high grade histology, a classical prognostic factor of the other soft tissue sarcomas. During surgical procedure axillary dissection is not mandatory

  2. Networked Microgrids Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Backhaus, Scott N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Dobriansky, Larisa [General MicroGrids, San Diego, CA (United States); Glover, Steve [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Liu, Chen-Ching [Washington State Univ., Pullman, WA (United States); Looney, Patrick [Brookhaven National Lab. (BNL), Upton, NY (United States); Mashayekh, Salman [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pratt, Annabelle [National Renewable Energy Lab. (NREL), Golden, CO (United States); Schneider, Kevin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Stadler, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Starke, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wang, Jianhui [Argonne National Lab. (ANL), Argonne, IL (United States); Yue, Meng [Brookhaven National Lab. (BNL), Upton, NY (United States)

    2016-12-05

    Much like individual microgrids, the range of opportunities and potential architectures of networked microgrids is very diverse. The goals of this scoping study are to provide an early assessment of research and development needs by examining the benefits of, risks created by, and risks to networked microgrids. At this time there are very few, if any, examples of deployed microgrid networks. In addition, there are very few tools to simulate or otherwise analyze the behavior of networked microgrids. In this setting, it is very difficult to evaluate networked microgrids systematically or quantitatively. At this early stage, this study is relying on inputs, estimations, and literature reviews by subject matter experts who are engaged in individual microgrid research and development projects, i.e., the authors of this study The initial step of the study gathered input about the potential opportunities provided by networked microgrids from these subject matter experts. These opportunities were divided between the subject matter experts for further review. Part 2 of this study is comprised of these reviews. Part 1 of this study is a summary of the benefits and risks identified in the reviews in Part 2 and synthesis of the research needs required to enable networked microgrids.

  3. Network information improves cancer outcome prediction.

    Science.gov (United States)

    Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

    2014-07-01

    Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  4. The gene regulatory network for breast cancer: Integrated regulatory landscape of cancer hallmarks

    Directory of Open Access Journals (Sweden)

    Frank eEmmert-Streib

    2014-02-01

    Full Text Available In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of $351$ patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome $21$ is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.

  5. Small Cell Carcinoma of the Urinary Bladder: A Retrospective, Multicenter Rare Cancer Network Study of 107 Patients

    Energy Technology Data Exchange (ETDEWEB)

    Pasquier, David, E-mail: d-pasquier@o-lambret.fr [Academic Radiation Oncology Department, Centre Oscar Lambret, Lille (France); Barney, Brandon [Mayo Clinic, Rochester, Minnesota (United States); Sundar, Santhanam [Department of Oncology, Nottingham University Hospitals National Health Service Trust, Nottingham (United Kingdom); Poortmans, Philip [Department of Radiation Oncology, Radboud university medical center, Nijmegen (Netherlands); Villa, Salvador [Radiation Oncology, Catalan Institute of Oncology, H. Universitari Germans Trías, Badalona, Barcelona (Spain); Nasrallah, Haitam [Division of Oncology, Rambam Health Care Campus and Faculty of Medicine, Technion-Israel Institute of Technology, Haifa (Israel); Boujelbene, Noureddine [Department of Radiation Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland); Ghadjar, Pirus [Department of Radiation Oncology, Bern University Hospital, Bern (Switzerland); Lassen-Ramshad, Yasmin [Department of Oncology, Aarhus University Hospital, Aarhus (Denmark); Senkus, Elżbieta [Department of Oncology and Radiotherapy, Medical University of Gdansk, Gdansk (Poland); Oar, Andrew [Genesis Cancer Care, Southport (Australia); Roelandts, Martine [Institut Jules Bordet, Brussels (Belgium); Amichetti, Maurizio [Provincial Agency for Proton Therapy, Trento (Italy); Vees, Hansjoerg [Department of Radiation Oncology, Hopital de Sion, Sion (Switzerland); Zilli, Thomas [Department of Radiation Oncology, Geneva University Hospital, Geneva (Switzerland); Ozsahin, Mahmut [Department of Radiation Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland)

    2015-07-15

    Purpose: Small cell carcinomas of the bladder (SCCB) account for fewer than 1% of all urinary bladder tumors. There is no consensus regarding the optimal treatment for SCCB. Methods and Materials: Fifteen academic Rare Cancer Network medical centers contributed SCCB cases. The eligibility criteria were as follows: pure or mixed SCC; local, locoregional, and metastatic stages; and age ≥18 years. The overall survival (OS) and disease-free survival (DFS) were calculated from the date of diagnosis according to the Kaplan-Meier method. The log-rank and Wilcoxon tests were used to analyze survival as functions of clinical and therapeutic factors. Results: The study included 107 patients (mean [±standard deviation, SD] age, 69.6 [±10.6] years; mean follow-up time, 4.4 years) with primary bladder SCC, with 66% of these patients having pure SCC. Seventy-two percent and 12% of the patients presented with T2-4N0M0 and T2-4N1-3M0 stages, respectively, and 16% presented with synchronous metastases. The most frequent curative treatments were radical surgery and chemotherapy, sequential chemotherapy and radiation therapy, and radical surgery alone. The median (interquartile range, IQR) OS and DFS times were 12.9 months (IQR, 7-32 months) and 9 months (IQR, 5-23 months), respectively. The metastatic, T2-4N0M0, and T2-4N1-3M0 groups differed significantly (P=.001) in terms of median OS and DFS. In a multivariate analysis, impaired creatinine clearance (OS and DFS), clinical stage (OS and DFS), a Karnofsky performance status <80 (OS), and pure SCC histology (OS) were independent and significant adverse prognostic factors. In the patients with nonmetastatic disease, the type of treatment (ie radical surgery with or without adjuvant chemotherapy vs conservative treatment) did not significantly influence OS or DFS (P=.7). Conclusions: The prognosis for SCCB remains poor. The finding that radical cystectomy did not influence DFS or OS in the patients with nonmetastatic disease

  6. Small Cell Carcinoma of the Urinary Bladder: A Retrospective, Multicenter Rare Cancer Network Study of 107 Patients.

    Science.gov (United States)

    Pasquier, David; Barney, Brandon; Sundar, Santhanam; Poortmans, Philip; Villa, Salvador; Nasrallah, Haitam; Boujelbene, Noureddine; Ghadjar, Pirus; Lassen-Ramshad, Yasmin; Senkus, Elżbieta; Oar, Andrew; Roelandts, Martine; Amichetti, Maurizio; Vees, Hansjoerg; Zilli, Thomas; Ozsahin, Mahmut

    2015-07-15

    Small cell carcinomas of the bladder (SCCB) account for fewer than 1% of all urinary bladder tumors. There is no consensus regarding the optimal treatment for SCCB. Fifteen academic Rare Cancer Network medical centers contributed SCCB cases. The eligibility criteria were as follows: pure or mixed SCC; local, locoregional, and metastatic stages; and age ≥18 years. The overall survival (OS) and disease-free survival (DFS) were calculated from the date of diagnosis according to the Kaplan-Meier method. The log-rank and Wilcoxon tests were used to analyze survival as functions of clinical and therapeutic factors. The study included 107 patients (mean [±standard deviation, SD] age, 69.6 [±10.6] years; mean follow-up time, 4.4 years) with primary bladder SCC, with 66% of these patients having pure SCC. Seventy-two percent and 12% of the patients presented with T2-4N0M0 and T2-4N1-3M0 stages, respectively, and 16% presented with synchronous metastases. The most frequent curative treatments were radical surgery and chemotherapy, sequential chemotherapy and radiation therapy, and radical surgery alone. The median (interquartile range, IQR) OS and DFS times were 12.9 months (IQR, 7-32 months) and 9 months (IQR, 5-23 months), respectively. The metastatic, T2-4N0M0, and T2-4N1-3M0 groups differed significantly (P=.001) in terms of median OS and DFS. In a multivariate analysis, impaired creatinine clearance (OS and DFS), clinical stage (OS and DFS), a Karnofsky performance status <80 (OS), and pure SCC histology (OS) were independent and significant adverse prognostic factors. In the patients with nonmetastatic disease, the type of treatment (ie radical surgery with or without adjuvant chemotherapy vs conservative treatment) did not significantly influence OS or DFS (P=.7). The prognosis for SCCB remains poor. The finding that radical cystectomy did not influence DFS or OS in the patients with nonmetastatic disease suggests that conservative treatment is appropriate in this

  7. Primary Mucosa-Associated Lymphoid Tissue Lymphoma of the Salivary Glands: A Multicenter Rare Cancer Network Study

    Energy Technology Data Exchange (ETDEWEB)

    Anacak, Yavuz, E-mail: yavuz.anacak@ege.edu.tr [Department of Radiation Oncology, Ege University Medical School, Izmir (Turkey); Miller, Robert C. [Department of Radiation Oncology, Mayo Clinic, Rochester, MN (United States); Constantinou, Nikos [Department of Hematology, Theagenion Cancer Center, Thessaloniki (Greece); Mamusa, Angela M. [Division of Hematology, Armando Businco Cancer Center, Cagliari (Italy); Epelbaum, Ron [Department of Oncology, Rambam Medical Center, Haifa (Israel); Li Yexiong [Department of Radiation Oncology, Cancer Hospital of Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing (China); Calduch, Anna Lucas [Servicio de Oncologia Radioterapica, Institut Catala d' Oncologia, Barcelona (Spain); Kowalczyk, Anna [Department of Oncology and Radiotherapy, Medical University of Gdansk (Poland); Weber, Damien C. [Department of Radiation Oncology, Geneva University Hospital (Switzerland); Kadish, Sidney P. [Department of Radiation Oncology, University of Massachusetts Medical School/Center, North Worcester, MA (United States); Bese, Nuran [Department of Radiation Oncology, Istanbul University Cerrahpasa Medical School, Istanbul (Turkey); Poortmans, Philip [Institute Verbeeten, Tilburg (Netherlands); Kamer, Serra [Department of Radiation Oncology, Ege University Medical School, Izmir (Turkey); Ozsahin, Mahmut [Department of Radiation Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland)

    2012-01-01

    Purpose: Involvement of salivary glands with mucosa-associated lymphoid tissue (MALT) lymphoma is rare. This retrospective study was performed to assess the clinical profile, treatment outcome, and prognostic factors of MALT lymphoma of the salivary glands. Methods and Materials: Thirteen member centers of the Rare Cancer Network from 10 countries participated, providing data on 63 patients. The median age was 58 years; 47 patients were female and 16 were male. The parotid glands were involved in 49 cases, submandibular in 15, and minor glands in 3. Multiple glands were involved in 9 patients. Staging was as follows: IE in 34, IIE in 12, IIIE in 2, and IV in 15 patients. Results: Surgery (S) alone was performed in 9, radiotherapy (RT) alone in 8, and chemotherapy (CT) alone in 4 patients. Forty-one patients received combined modality treatment (S + RT in 23, S + CT in 8, RT + CT in 4, and all three modalities in 6 patients). No active treatment was given in one case. After initial treatment there was no tumor in 57 patients and residual tumor in 5. Tumor progression was observed in 23 (36.5%) (local in 1, other salivary glands in 10, lymph nodes in 11, and elsewhere in 6). Five patients died of disease progression and the other 5 of other causes. The 5-year disease-free survival, disease-specific survival, and overall survival were 54.4%, 93.2%, and 81.7%, respectively. Factors influencing disease-free survival were use of RT, stage, and residual tumor (p < 0.01). Factors influencing disease-specific survival were stage, recurrence, and residual tumor (p < 0.01). Conclusions: To our knowledge, this report represents the largest series of MALT lymphomas of the salivary glands published to date. This disease may involve all salivary glands either initially or subsequently in 30% of patients. Recurrences may occur in up to 35% of patients at 5 years; however, survival is not affected. Radiotherapy is the only treatment modality that improves disease-free survival.

  8. Drawbacks and benefits associated with inter-organizational collaboration along the discovery-development-delivery continuum: a cancer research network case study.

    Science.gov (United States)

    Harris, Jenine K; Provan, Keith G; Johnson, Kimberly J; Leischow, Scott J

    2012-07-25

    The scientific process around cancer research begins with scientific discovery, followed by development of interventions, and finally delivery of needed interventions to people with cancer. Numerous studies have identified substantial gaps between discovery and delivery in health research. Team science has been identified as a possible solution for closing the discovery to delivery gap; however, little is known about effective ways of collaborating within teams and across organizations. The purpose of this study was to determine benefits and drawbacks associated with organizational collaboration across the discovery-development-delivery research continuum. Representatives of organizations working on cancer research across a state answered a survey about how they collaborated with other cancer research organizations in the state and what benefits and drawbacks they experienced while collaborating. We used exponential random graph modeling to determine the association between these benefits and drawbacks and the presence of a collaboration tie between any two network members. Different drawbacks and benefits were associated with discovery, development, and delivery collaborations. The only consistent association across all three was with the drawback of difficulty due to geographic differences, which was negatively associated with collaboration, indicating that those organizations that had collaborated were less likely to perceive a barrier related to geography. The benefit, enhanced access to other knowledge, was positive and significant in the development and delivery networks, indicating that collaborating organizations viewed improved knowledge exchange as a benefit of collaboration. 'Acquisition of additional funding or other resources' and 'development of new tools and methods' were negatively significantly related to collaboration in these networks. So, although improved knowledge access was an outcome of collaboration, more tangible outcomes were not being

  9. Navigating cancer network attractors for tumor-specific therapy

    DEFF Research Database (Denmark)

    Creixell, Pau; Schoof, Erwin; Erler, Janine Terra

    2012-01-01

    understanding of the processes by which genetic lesions perturb these networks and lead to disease phenotypes. Network biology will help circumvent fundamental obstacles in cancer treatment, such as drug resistance and metastasis, empowering personalized and tumor-specific cancer therapies....

  10. Prostate Cancer Biorepository Network (PCBN)

    Science.gov (United States)

    2017-10-01

    are linked to clinical and outcome data and supported by an informatics infrastructure . In this 2nd year of operation the University of Washington...REPORT Unclassified b. ABSTRACT Unclassified c. THIS PAGE Unclassified Unclassified 19b. TELEPHONE NUMBER (include area code ) Standard Form 298...informatics infrastructure . Keywords Biorepository, prostate cancer, patient derived xenografts, rapid autopsy, biomarkers. Accomplishments The

  11. A network-based method to evaluate quality of reproducibility of differential expression in cancer genomics studies.

    Science.gov (United States)

    Li, Robin; Lin, Xiao; Geng, Haijiang; Li, Zhihui; Li, Jiabing; Lu, Tao; Yan, Fangrong

    2015-12-29

    Personalized cancer treatments depend on the determination of a patient's genetic status according to known genetic profiles for which targeted treatments exist. Such genetic profiles must be scientifically validated before they is applied to general patient population. Reproducibility of findings that support such genetic profiles is a fundamental challenge in validation studies. The percentage of overlapping genes (POG) criterion and derivative methods produce unstable and misleading results. Furthermore, in a complex disease, comparisons between different tumor subtypes can produce high POG scores that do not capture the consistencies in the functions. We focused on the quality rather than the quantity of the overlapping genes. We defined the rank value of each gene according to importance or quality by PageRank on basis of a particular topological structure. Then, we used the p-value of the rank-sum of the overlapping genes (PRSOG) to evaluate the quality of reproducibility. Though the POG scores were low in different studies of the same disease, the PRSOG was statistically significant, which suggests that sets of differentially expressed genes might be highly reproducible. Evaluations of eight datasets from breast cancer, lung cancer and four other disorders indicate that quality-based PRSOG method performs better than a quantity-based method. Our analysis of the components of the sets of overlapping genes supports the utility of the PRSOG method.

  12. Communication networks of men facing a diagnosis of prostate cancer.

    Science.gov (United States)

    Brown, Dot; Oetzel, John; Henderson, Alison

    2016-11-01

    This study seeks to identify the factors that shape the communication networks of men who face a potential diagnosis of prostate cancer, and how these factors relate to their disclosure about their changing health status. Men facing a potential diagnosis of prostate cancer are in a challenging situation; the support benefits of disclosing their changing health status to others in their communication networks is set against a backdrop of the potential stigma and uncertainty of the diagnosis. All men on a prostate biopsy waiting list were eligible for inclusion in an exploratory and interpretive study. Semi-structured interviews with 40 men explored their network structures and disclosure of health information. Thematic analysis highlighted the factors which contributed to their network structures and their disclosure about their health status. Four network factors shaped men's perspectives about disclosing their health status: (1) tie strength, comprising both strong and weak ties; (2) knowledgeable others, with a focus on medical professionals in the family; (3) homophily, which included other individuals with a similar medical condition; and (4) geographical proximity, with a preference for face-to-face communication. Communication networks influence men's disclosure of their health status and in particular weak ties with medical knowledge have an important role. Men who use the potential for support in their networks may experience improved psychosocial outcomes. Using these four network factors-tie strength, knowledgeable others, homophily or geographical proximity-to forecast men's willingness to disclose helps identify men who lack potential support and so are at risk of poor psychosocial health. Those with few strong ties or knowledgeable others in their networks may be in the at-risk cohort. The support provided in communication networks complements formal medical care from nurses and other health professionals, and encouraging patients to use their

  13. Non-coding RNA networks in cancer.

    Science.gov (United States)

    Anastasiadou, Eleni; Jacob, Leni S; Slack, Frank J

    2018-01-01

    Thousands of unique non-coding RNA (ncRNA) sequences exist within cells. Work from the past decade has altered our perception of ncRNAs from 'junk' transcriptional products to functional regulatory molecules that mediate cellular processes including chromatin remodelling, transcription, post-transcriptional modifications and signal transduction. The networks in which ncRNAs engage can influence numerous molecular targets to drive specific cell biological responses and fates. Consequently, ncRNAs act as key regulators of physiological programmes in developmental and disease contexts. Particularly relevant in cancer, ncRNAs have been identified as oncogenic drivers and tumour suppressors in every major cancer type. Thus, a deeper understanding of the complex networks of interactions that ncRNAs coordinate would provide a unique opportunity to design better therapeutic interventions.

  14. Pathway and network analysis of cancer genomes

    DEFF Research Database (Denmark)

    Creixell, Pau; Reimand, Jueri; Haider, Syed

    2015-01-01

    Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been...

  15. Scoping Study: Networked Microgrids.

    Energy Technology Data Exchange (ETDEWEB)

    Trinklei, Eddy; Parker, Gordon; Weaver, Wayne; Robinett, Rush; Babe Gauchia, Lucia; Ten, Chee-Wooi; Bower, Ward; Glover, Steven F.; Bukowski, Steve

    2014-10-01

    This report presents a scoping study for networked microgrids which are defined as "Interoperable groups of multiple Advanced Microgrids that become an integral part of the electricity grid while providing enhanced resiliency through self-healing, aggregated ancillary services, and real-time communication." They result in optimal electrical system configurations and controls whether grid-connected or in islanded modes and enable high penetrations of distributed and renewable energy resources. The vision for the purpose of this document is: "Networked microgrids seamlessly integrate with the electricity grid or other Electric Power Sources (EPS) providing cost effective, high quality, reliable, resilient, self-healing power delivery systems." Scoping Study: Networked Microgrids September 4, 2014 Eddy Trinklein, Michigan Technological University Gordon Parker, Michigan Technological University Wayne Weaver, Michigan Technological University Rush Robinett, Michigan Technological University Lucia Gauchia Babe, Michigan Technological University Chee-Wooi Ten, Michigan Technological University Ward Bower, Ward Bower Innovations LLC Steve Glover, Sandia National Laboratories Steve Bukowski, Sandia National Laboratories Prepared by Michigan Technological University Houghton, Michigan 49931 Michigan Technological University

  16. Addressing cancer disparities via community network mobilization and intersectoral partnerships: a social network analysis.

    Directory of Open Access Journals (Sweden)

    Shoba Ramanadhan

    Full Text Available Community mobilization and collaboration among diverse partners are vital components of the effort to reduce and eliminate cancer disparities in the United States. We studied the development and impact of intersectoral connections among the members of the Massachusetts Community Network for Cancer Education, Research, and Training (MassCONECT. As one of the Community Network Program sites funded by the National Cancer Institute, this infrastructure-building initiative utilized principles of Community-based Participatory Research (CBPR to unite community coalitions, researchers, policymakers, and other important stakeholders to address cancer disparities in three Massachusetts communities: Boston, Lawrence, and Worcester. We conducted a cross-sectional, sociometric network analysis four years after the network was formed. A total of 38 of 55 members participated in the study (69% response rate. Over four years of collaboration, the number of intersectoral connections reported by members (intersectoral out-degree increased, as did the extent to which such connections were reported reciprocally (intersectoral reciprocity. We assessed relationships between these markers of intersectoral collaboration and three intermediate outcomes in the effort to reduce and eliminate cancer disparities: delivery of community activities, policy engagement, and grants/publications. We found a positive and statistically significant relationship between intersectoral out-degree and community activities and policy engagement (the relationship was borderline significant for grants/publications. We found a positive and statistically significant relationship between intersectoral reciprocity and community activities and grants/publications (the relationship was borderline significant for policy engagement. The study suggests that intersectoral connections may be important drivers of diverse intermediate outcomes in the effort to reduce and eliminate cancer disparities

  17. Using Social Network Analysis to Evaluate Community Capacity Building of a Regional Community Cancer Network

    Science.gov (United States)

    Luque, John; Tyson, Dinorah Martinez; Lee, Ji-Hyun; Gwede, Clement; Vadaparampil, Susan; Noel-Thomas, Shalewa; Meade, Cathy

    2010-01-01

    The Tampa Bay Community Cancer Network (TBCCN) is one of 25 Community Network Programs funded by the National Cancer Institute's (NCI's) Center to Reduce Cancer Health Disparities with the objectives to create a collaborative infrastructure of academic and community based organizations and to develop effective and sustainable interventions to…

  18. A network-based biomarker approach for molecular investigation and diagnosis of lung cancer

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2011-01-01

    Full Text Available Abstract Background Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, based on the research dedicated to this field, there is no highly sensitive network-based method for carcinogenesis characterization and diagnosis from the systems perspective. Methods In this study, a systems biology approach integrating microarray gene expression profiles and protein-protein interaction information was proposed to develop a network-based biomarker for molecular investigation into the network mechanism of lung carcinogenesis and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and non-cancer samples. Results Based on the network-based biomarker, a total of 40 significant proteins in lung carcinogenesis were identified with carcinogenesis relevance values (CRVs. In addition, the network-based biomarker, acting as the screening test, proved to be effective in diagnosing smokers with signs of lung cancer. Conclusions A network-based biomarker using constructed protein association networks is a useful tool to highlight the pathways and mechanisms of the lung carcinogenic process and, more importantly, provides potential therapeutic targets to combat cancer.

  19. Comparison of Back propagation neural network and Back propagation neural network Based Particle Swarm intelligence in Diagnostic Breast Cancer

    Directory of Open Access Journals (Sweden)

    Farahnaz SADOUGHI

    2014-03-01

    Full Text Available Breast cancer is the most commonly diagnosed cancer and the most common cause of death in women all over the world. Use of computer technology supporting breast cancer diagnosing is now widespread and pervasive across a broad range of medical areas. Early diagnosis of this disease can greatly enhance the chances of long-term survival of breast cancer victims. Artificial Neural Networks (ANN as mainly method play important role in early diagnoses breast cancer. This paper studies Levenberg Marquardet Backpropagation (LMBP neural network and Levenberg Marquardet Backpropagation based Particle Swarm Optimization(LMBP-PSO for the diagnosis of breast cancer. The obtained results show that LMBP and LMBP based PSO system provides higher classification efficiency. But LMBP based PSO needs minimum training and testing time. It helps in developing Medical Decision System (MDS for breast cancer diagnosing. It can also be used as secondary observer in clinical decision making.

  20. [The survival prediction model of advanced gallbladder cancer based on Bayesian network: a multi-institutional study].

    Science.gov (United States)

    Tang, Z H; Geng, Z M; Chen, C; Si, S B; Cai, Z Q; Song, T Q; Gong, P; Jiang, L; Qiu, Y H; He, Y; Zhai, W L; Li, S P; Zhang, Y C; Yang, Y

    2018-05-01

    Objective: To investigate the clinical value of Bayesian network in predicting survival of patients with advanced gallbladder cancer(GBC)who underwent curative intent surgery. Methods: The clinical data of patients with advanced GBC who underwent curative intent surgery in 9 institutions from January 2010 to December 2015 were analyzed retrospectively.A median survival time model based on a tree augmented naïve Bayes algorithm was established by Bayesia Lab software.The survival time, number of metastatic lymph nodes(NMLN), T stage, pathological grade, margin, jaundice, liver invasion, age, sex and tumor morphology were included in this model.Confusion matrix, the receiver operating characteristic curve and area under the curve were used to evaluate the accuracy of the model.A priori statistical analysis of these 10 variables and a posterior analysis(survival time as the target variable, the remaining factors as the attribute variables)was performed.The importance rankings of each variable was calculated with the polymorphic Birnbaum importance calculation based on the posterior analysis results.The survival probability forecast table was constructed based on the top 4 prognosis factors. The survival curve was drawn by the Kaplan-Meier method, and differences in survival curves were compared using the Log-rank test. Results: A total of 316 patients were enrolled, including 109 males and 207 females.The ratio of male to female was 1.0∶1.9, the age was (62.0±10.8)years.There was 298 cases(94.3%) R0 resection and 18 cases(5.7%) R1 resection.T staging: 287 cases(90.8%) T3 and 29 cases(9.2%) T4.The median survival time(MST) was 23.77 months, and the 1, 3, 5-year survival rates were 67.4%, 40.8%, 32.0%, respectively.For the Bayesian model, the number of correctly predicted cases was 121(≤23.77 months) and 115(>23.77 months) respectively, leading to a 74.86% accuracy of this model.The prior probability of survival time was 0.503 2(≤23.77 months) and 0.496 8

  1. No study left behind: a network meta-analysis in non-small-cell lung cancer demonstrating the importance of considering all relevant data.

    Science.gov (United States)

    Hawkins, Neil; Scott, David A; Woods, Beth S; Thatcher, Nicholas

    2009-09-01

    To demonstrate the importance of considering all relevant indirect data in a network meta-analysis of treatments for non-small-cell lung cancer (NSCLC). A recent National Institute for Health and Clinical Excellence appraisal focussed on the indirect comparison of docetaxel with erlotinib in second-line treatment of NSCLC based on trials including a common comparator. We compared the results of this analysis to a network meta-analysis including other trials that formed a network of evidence. We also examined the importance of allowing for the correlations between the estimated treatment effects that can arise when analysing such networks. The analysis of the restricted network including only trials of docetaxel and erlotinib linked via the common placebo comparator produced an estimated mean hazard ratio (HR) for erlotinib compared with docetaxel of 1.55 (95% confidence interval [CI] 0.72-2.97). In contrast, the network meta-analysis produced an estimated HR for erlotinib compared with docetaxel of 0.83 (95% CI 0.65-1.06). Analyzing the wider network improved the precision of estimated treatment effects, altered their rankings and also allowed further treatments to be compared. Some of the estimated treatment effects from the wider network were highly correlated. This empirical example shows the importance of considering all potentially relevant data when comparing treatments. Care should therefore be taken to consider all relevant information, including correlations induced by the network of trial data, when comparing treatments.

  2. Altered small-world properties of gray matter networks in breast cancer

    Directory of Open Access Journals (Sweden)

    Hosseini S M

    2012-05-01

    Full Text Available Abstract Background Breast cancer survivors, particularly those treated with chemotherapy, are at significantly increased risk for long-term cognitive and neurobiologic impairments. These deficits tend to involve skills that are subserved by distributed brain networks. Additionally, neuroimaging studies have shown a diffuse pattern of brain structure changes in chemotherapy-treated breast cancer survivors that might impact large-scale brain networks. Methods We therefore applied graph theoretical analysis to compare the gray matter structural networks of female breast cancer survivors with a history of chemotherapy treatment and healthy age and education matched female controls. Results Results revealed reduced clustering coefficient and small-world index in the brain network of the breast cancer patients across a range of network densities. In addition, the network of the breast cancer group had less highly interactive nodes and reduced degree/centrality in the frontotemporal regions compared to controls, which may help explain the common impairments of memory and executive functioning among these patients. Conclusions These results suggest that breast cancer and chemotherapy may decrease regional connectivity as well as global network organization and integration, reducing efficiency of the network. To our knowledge, this is the first report of altered large-scale brain networks associated with breast cancer and chemotherapy.

  3. Prostate Cancer Biospecimen Cohort Study

    Science.gov (United States)

    2017-10-01

    opinions and/or findings contained in this report are those of the author(s) and should not be construed as an official Department of the Army...SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION / AVAILABILITY STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES...14. ABSTRACT The goal of the study is development of a Prostate Cancer Biorepository Network (PCBN) resource site with high quality and well

  4. The Essential Role of Radiotherapy in the Treatment of Merkel Cell Carcinoma: A Study From the Rare Cancer Network

    Energy Technology Data Exchange (ETDEWEB)

    Ghadjar, Pirus, E-mail: pirus.ghadjar@insel.ch [Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern (Switzerland); Kaanders, Johannes H. [Department of Radiation Oncology, Radboud University Nijmegen Medical Centre, Institute of Oncology (Netherlands); Poortmans, Philipp [Department of Radiation Oncology, Institute Verbeeten, Tilburg (Netherlands); Zaucha, Renata [Department of Oncology and Radiotherapy, Medical University, Gdansk (Poland); Krengli, Marco [Department of Radiotherapy, University Hospital Maggiore della Carita, Novara (Italy); Lagrange, Jean L. [Service de Radiotherapie, Hopital Henri-Mondor, Creteil (France); Oezsoy, Orhan [Department of Radiation Oncology, CHCVs-RSV, Sion (Switzerland); Nguyen, Tan D. [Department of Radiation Oncology, Institut Jean Godinot, Reims (France); Miralbell, Raymond [Department of Radiation Oncology, Hopitaux Universitaires de Geneve, Geneva (Switzerland); Baize, Adele [Department de Radio-Oncologie, Institut Jules Bordet, Bruxelles (Belgium); Boujelbene, Noureddine [Department of Radiation Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland); Collen, Timothy [Department of Radiation Oncology, Kantonsspital St. Gallen (Switzerland); Scandolaro, Luciano [Radioterapia, Azienda Ospedale Sant' Anna, Como (Italy); Untereiner, Michel [Centre Francois Baclesse, Luxembourg (Luxembourg); Goldberg, Hadassah [Oncology Departement, Rambam Medical Center, Haifa (Israel); Pesce, Gianfranco A. [Department of Radiation Oncology, Oncology Institute of Southern Switzerland, Opedale San Giovanni, Bellinzona (Switzerland); Anacak, Yavuz [Department of Radiation Oncology, EGE University, Izmir (Turkey); Friedrich, Esther E.; Aebersold, Daniel M. [Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern (Switzerland); Beer, Karl T. [Radio Onkologiezentrum Biel (Switzerland)

    2011-11-15

    Purpose: To evaluate the role of postoperative radiotherapy (RT) in Merkel cell carcinoma (MCC). Methods and Materials: A retrospective multicenter study was performed in 180 patients with MCC treated between February 1988 and September 2009. Patients who had had surgery alone were compared with patients who received surgery and postoperative RT or radical RT. Local relapse-free survival (LRFS), regional relapse-free survival (RRFS), and distant metastasis-free survival (DMFS) rates were assessed together with disease-free survival (DFS), cancer-specific survival (CSS), and overall survival (OS) rates. Results: Seventy-nine patients were male and 101 patients were female, and the median age was 73 years old (range, 38-93 years). The majority of patients had localized disease (n = 146), and the remaining patients had regional lymph node metastasis (n = 34). Forty-nine patients underwent surgery for the primary tumor without postoperative RT to the primary site; the other 131 patients received surgery for the primary tumor, followed by postoperative RT (n = 118) or a biopsy of the primary tumor followed by radical RT (n = 13). Median follow-up was 5 years (range, 0.2-16.5 years). Patients in the RT group had improved LRFS (93% vs. 64%; p < 0.001), RRFS (76% vs. 27%; p < 0.001), DMFS (70% vs. 42%; p = 0.01), DFS (59% vs. 4%; p < 0.001), and CSS (65% vs. 49%; p = 0.03) rates compared to patients who underwent surgery for the primary tumor alone; LRFS, RRFS, DMFS, and DFS rates remained significant with multivariable Cox regression analysis. However OS was not significantly improved by postoperative RT (56% vs. 46%; p = 0.2). Conclusions: After multivariable analysis, postoperative RT was associated with improved outcome and seems to be an important component in the multimodality treatment of MCC.

  5. CDC's Cervical Cancer Study

    Science.gov (United States)

    ... Materials Infographics Cancer and Alcohol Web Features Breast Cancer Awareness Breast Cancer in Young Women Cancer and Men ... in Childhood Cancer, the Flu, and You Cervical Cancer Awareness Colorectal Cancer Awareness Gynecologic Cancer Awareness Health Disparities ...

  6. A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens.

    Science.gov (United States)

    Jacobson, Rebecca S; Becich, Michael J; Bollag, Roni J; Chavan, Girish; Corrigan, Julia; Dhir, Rajiv; Feldman, Michael D; Gaudioso, Carmelo; Legowski, Elizabeth; Maihle, Nita J; Mitchell, Kevin; Murphy, Monica; Sakthivel, Mayurapriyan; Tseytlin, Eugene; Weaver, JoEllen

    2015-12-15

    Advances in cancer research and personalized medicine will require significant new bridging infrastructures, including more robust biorepositories that link human tissue to clinical phenotypes and outcomes. In order to meet that challenge, four cancer centers formed the Text Information Extraction System (TIES) Cancer Research Network, a federated network that facilitates data and biospecimen sharing among member institutions. Member sites can access pathology data that are de-identified and processed with the TIES natural language processing system, which creates a repository of rich phenotype data linked to clinical biospecimens. TIES incorporates multiple security and privacy best practices that, combined with legal agreements, network policies, and procedures, enable regulatory compliance. The TIES Cancer Research Network now provides integrated access to investigators at all member institutions, where multiple investigator-driven pilot projects are underway. Examples of federated search across the network illustrate the potential impact on translational research, particularly for studies involving rare cancers, rare phenotypes, and specific biologic behaviors. The network satisfies several key desiderata including local control of data and credentialing, inclusion of rich phenotype information, and applicability to diverse research objectives. The TIES Cancer Research Network presents a model for a national data and biospecimen network. ©2015 American Association for Cancer Research.

  7. Online Social Networks - Opportunities for Empowering Cancer Patients.

    Science.gov (United States)

    Mohammadzadeh, Zeinab; Davoodi, Somayeh; Ghazisaeidi, Marjan

    2016-01-01

    Online social network technologies have become important to health and apply in most health care areas. Particularly in cancer care, because it is a disease which involves many social aspects, online social networks can be very useful. Use of online social networks provides a suitable platform for cancer patients and families to present and share information about their medical conditions, address their educational needs, support decision making, and help to coping with their disease and improve their own outcomes. Like any other new technologies, online social networks, along with many benefits, have some negative effects such as violation of privacy and publication of incorrect information. However, if these effects are managed properly, they can empower patients to manage cancer through changing behavioral patterns and enhancing the quality of cancer patients lives This paper explains some application of online social networks in the cancer patient care process. It also covers advantages and disadvantages of related technologies.

  8. Rural Health Networks: How Network Analysis Can Inform Patient Care and Organizational Collaboration in a Rural Breast Cancer Screening Network.

    Science.gov (United States)

    Prusaczyk, Beth; Maki, Julia; Luke, Douglas A; Lobb, Rebecca

    2018-04-15

    Rural health networks have the potential to improve health care quality and access. Despite this, the use of network analysis to study rural health networks is limited. The purpose of this study was to use network analysis to understand how a network of rural breast cancer care providers deliver services and to demonstrate the value of this methodology in this research area. Leaders at 47 Federally Qualified Health Centers and Rural Health Clinics across 10 adjacent rural counties were asked where they refer patients for mammograms or breast biopsies. These clinics and the 22 referral providers that respondents named comprised the network. The network was analyzed graphically and statistically with exponential random graph modeling. Most (96%, n = 45) of the clinics and referral sites (95%, n = 21) are connected to each other. Two clinics of the same type were 62% less likely to refer patients to the same providers as 2 clinics of different types (OR = 0.38, 95% CI = 0.29-0.50). Clinics in the same county have approximately 8 times higher odds of referring patients to the same providers compared to clinics in different counties (OR = 7.80, CI = 4.57-13.31). This study found that geographic location of resources is an important factor in rural health care providers' referral decisions and demonstrated the usefulness of network analysis for understanding rural health networks. These results can be used to guide delivery of patient care and strengthen the network by building resources that take location into account. © 2018 National Rural Health Association.

  9. Prediction of Bladder Cancer Recurrences Using Artificial Neural Networks

    Science.gov (United States)

    Zulueta Guerrero, Ekaitz; Garay, Naiara Telleria; Lopez-Guede, Jose Manuel; Vilches, Borja Ayerdi; Iragorri, Eider Egilegor; Castaños, David Lecumberri; de La Hoz Rastrollo, Ana Belén; Peña, Carlos Pertusa

    Even if considerable advances have been made in the field of early diagnosis, there is no simple, cheap and non-invasive method that can be applied to the clinical monitorisation of bladder cancer patients. Moreover, bladder cancer recurrences or the reappearance of the tumour after its surgical resection cannot be predicted in the current clinical setting. In this study, Artificial Neural Networks (ANN) were used to assess how different combinations of classical clinical parameters (stage-grade and age) and two urinary markers (growth factor and pro-inflammatory mediator) could predict post surgical recurrences in bladder cancer patients. Different ANN methods, input parameter combinations and recurrence related output variables were used and the resulting positive and negative prediction rates compared. MultiLayer Perceptron (MLP) was selected as the most predictive model and urinary markers showed the highest sensitivity, predicting correctly 50% of the patients that would recur in a 2 year follow-up period.

  10. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks | Center for Cancer Research

    Science.gov (United States)

    The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in

  11. Assessing Breast Cancer Risk with an Artificial Neural Network

    Science.gov (United States)

    Sepandi, Mojtaba; Taghdir, Maryam; Rezaianzadeh, Abbas; Rahimikazerooni, Salar

    2018-04-25

    Objectives: Radiologists face uncertainty in making decisions based on their judgment of breast cancer risk. Artificial intelligence and machine learning techniques have been widely applied in detection/recognition of cancer. This study aimed to establish a model to aid radiologists in breast cancer risk estimation. This incorporated imaging methods and fine needle aspiration biopsy (FNAB) for cyto-pathological diagnosis. Methods: An artificial neural network (ANN) technique was used on a retrospectively collected dataset including mammographic results, risk factors, and clinical findings to accurately predict the probability of breast cancer in individual patients. Area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values were used to evaluate discriminative performance. Result: The network incorporating the selected features performed best (AUC = 0.955). Sensitivity and specificity of the ANN were respectively calculated as 0.82 and 0.90. In addition, negative and positive predictive values were respectively computed as 0.90 and 0.80. Conclusion: ANN has potential applications as a decision-support tool to help underperforming practitioners to improve the positive predictive value of biopsy recommendations. Creative Commons Attribution License

  12. Robust gene network analysis reveals alteration of the STAT5a network as a hallmark of prostate cancer.

    Science.gov (United States)

    Reddy, Anupama; Huang, C Chris; Liu, Huiqing; Delisi, Charles; Nevalainen, Marja T; Szalma, Sandor; Bhanot, Gyan

    2010-01-01

    We develop a general method to identify gene networks from pair-wise correlations between genes in a microarray data set and apply it to a public prostate cancer gene expression data from 69 primary prostate tumors. We define the degree of a node as the number of genes significantly associated with the node and identify hub genes as those with the highest degree. The correlation network was pruned using transcription factor binding information in VisANT (http://visant.bu.edu/) as a biological filter. The reliability of hub genes was determined using a strict permutation test. Separate networks for normal prostate samples, and prostate cancer samples from African Americans (AA) and European Americans (EA) were generated and compared. We found that the same hubs control disease progression in AA and EA networks. Combining AA and EA samples, we generated networks for low low (cancer (e.g. possible turning on of oncogenes). (ii) Some hubs reduced their degree in the tumor network compared to their degree in the normal network, suggesting that these genes are associated with loss of regulatory control in cancer (e.g. possible loss of tumor suppressor genes). A striking result was that for both AA and EA tumor samples, STAT5a, CEBPB and EGR1 are major hubs that gain neighbors compared to the normal prostate network. Conversely, HIF-lα is a major hub that loses connections in the prostate cancer network compared to the normal prostate network. We also find that the degree of these hubs changes progressively from normal to low grade to high grade disease, suggesting that these hubs are master regulators of prostate cancer and marks disease progression. STAT5a was identified as a central hub, with ~120 neighbors in the prostate cancer network and only 81 neighbors in the normal prostate network. Of the 120 neighbors of STAT5a, 57 are known cancer related genes, known to be involved in functional pathways associated with tumorigenesis. Our method is general and can easily

  13. Efficient Cancer Detection Using Multiple Neural Networks.

    Science.gov (United States)

    Shell, John; Gregory, William D

    2017-01-01

    The inspection of live excised tissue specimens to ascertain malignancy is a challenging task in dermatopathology and generally in histopathology. We introduce a portable desktop prototype device that provides highly accurate neural network classification of malignant and benign tissue. The handheld device collects 47 impedance data samples from 1 Hz to 32 MHz via tetrapolar blackened platinum electrodes. The data analysis was implemented with six different backpropagation neural networks (BNN). A data set consisting of 180 malignant and 180 benign breast tissue data files in an approved IRB study at the Aurora Medical Center, Milwaukee, WI, USA, were utilized as a neural network input. The BNN structure consisted of a multi-tiered consensus approach autonomously selecting four of six neural networks to determine a malignant or benign classification. The BNN analysis was then compared with the histology results with consistent sensitivity of 100% and a specificity of 100%. This implementation successfully relied solely on statistical variation between the benign and malignant impedance data and intricate neural network configuration. This device and BNN implementation provides a novel approach that could be a valuable tool to augment current medical practice assessment of the health of breast, squamous, and basal cell carcinoma and other excised tissue without requisite tissue specimen expertise. It has the potential to provide clinical management personnel with a fast non-invasive accurate assessment of biopsied or sectioned excised tissue in various clinical settings.

  14. Postdiagnosis social networks and breast cancer mortality in the After Breast Cancer Pooling Project.

    Science.gov (United States)

    Kroenke, Candyce H; Michael, Yvonne L; Poole, Elizabeth M; Kwan, Marilyn L; Nechuta, Sarah; Leas, Eric; Caan, Bette J; Pierce, John; Shu, Xiao-Ou; Zheng, Ying; Chen, Wendy Y

    2017-04-01

    Large social networks have been associated with better overall survival, though not consistently with breast cancer (BC)-specific outcomes. This study evaluated associations of postdiagnosis social networks and BC outcomes in a large cohort. Women from the After Breast Cancer Pooling Project (n = 9267) provided data on social networks within approximately 2 years of their diagnosis. A social network index was derived from information about the presence of a spouse/partner, religious ties, community ties, friendship ties, and numbers of living first-degree relatives. Cox models were used to evaluate associations, and a meta-analysis was used to determine whether effect estimates differed by cohort. Stratification by demographic, social, tumor, and treatment factors was performed. There were 1448 recurrences and 1521 deaths (990 due to BC). Associations were similar in 3 of 4 cohorts. After covariate adjustments, socially isolated women (small networks) had higher risks of recurrence (hazard ratio [HR], 1.43; 95% confidence interval [CI], 1.15-1.77), BC-specific mortality (HR, 1.64; 95% CI, 1.33-2.03), and total mortality (HR, 1.69; 95% CI, 1.43-1.99) than socially integrated women; associations were stronger in those with stage I/II cancer. In the fourth cohort, there were no significant associations with BC-specific outcomes. A lack of a spouse/partner (P = .02) and community ties (P = .04) predicted higher BC-specific mortality in older white women but not in other women. However, a lack of relatives (P = .02) and friendship ties (P = .01) predicted higher BC-specific mortality in nonwhite women only. In a large pooled cohort, larger social networks were associated with better BC-specific and overall survival. Clinicians should assess social network information as a marker of prognosis because critical supports may differ with sociodemographic factors. Cancer 2017;123:1228-1237. © 2016 American Cancer Society. © 2016 American Cancer Society.

  15. A cloud-based data network approach for translational cancer research.

    Science.gov (United States)

    Xing, Wei; Tsoumakos, Dimitrios; Ghanem, Moustafa

    2015-01-01

    We develop a new model and associated technology for constructing and managing self-organizing data to support translational cancer research studies. We employ a semantic content network approach to address the challenges of managing cancer research data. Such data is heterogeneous, large, decentralized, growing and continually being updated. Moreover, the data originates from different information sources that may be partially overlapping, creating redundancies as well as contradictions and inconsistencies. Building on the advantages of elasticity of cloud computing, we deploy the cancer data networks on top of the CELAR Cloud platform to enable more effective processing and analysis of Big cancer data.

  16. Lessons Learned from the Young Breast Cancer Survivorship Network.

    Science.gov (United States)

    Gisiger-Camata, Silvia; Nolan, Timiya S; Vo, Jacqueline B; Bail, Jennifer R; Lewis, Kayla A; Meneses, Karen

    2017-11-30

    The Young Breast Cancer Survivors Network (Network) is an academic and community-based partnership dedicated to education, support, and networking. The Network used a multi-pronged approach via monthly support and networking, annual education seminars, website networking, and individual survivor consultation. Formative and summative evaluations were conducted using group survey and individual survivor interviews for monthly gatherings, annual education meetings, and individual consultation. Google Analytics was applied to evaluate website use. The Network began with 4 initial partnerships and grew to 38 in the period from 2011 to 2017. During this 5-year period, 5 annual meetings (598 attendees), 23 support and networking meetings (373), and 115 individual survivor consultations were conducted. The Network website had nearly 12,000 individual users and more than 25,000 page views. Lessons learned include active community engagement, survivor empowerment, capacity building, social media outreach, and network sustainability. The 5-year experiences with the Network demonstrated that a regional program dedicated to the education, support, networking, and needs of young breast cancer survivors and their families can become a vital part of cancer survivorship services in a community. Strong community support, engagement, and encouragement were vital components to sustain the program.

  17. Social Network Structures of Breast Cancer Patients and the Contributing Role of Patient Navigators.

    Science.gov (United States)

    Gunn, Christine M; Parker, Victoria A; Bak, Sharon M; Ko, Naomi; Nelson, Kerrie P; Battaglia, Tracy A

    2017-08-01

    Minority women in the U.S. continue to experience inferior breast cancer outcomes compared with white women, in part due to delays in care delivery. Emerging cancer care delivery models like patient navigation focus on social barriers, but evidence demonstrating how these models increase social capital is lacking. This pilot study describes the social networks of newly diagnosed breast cancer patients and explores the contributing role of patient navigators. Twenty-five women completed a one hour interview about their social networks related to cancer care support. Network metrics identified important structural attributes and influential individuals. Bivariate associations between network metrics, type of network, and whether the network included a navigator were measured. Secondary analyses explored associations between network structures and clinical outcomes. We identified three types of networks: kin-based, role and/or affect-based, or heterogeneous. Network metrics did not vary significantly by network type. There was a low prevalence of navigators included in the support networks (25%). Network density scores were significantly higher in those networks without a navigator. Network metrics were not predictive of clinical outcomes in multivariate models. Patient navigators were not frequently included in support networks, but provided distinctive types of support. If navigators can identify patients with poorly integrated (less dense) social networks, or who have unmet tangible support needs, the intensity of navigation services could be tailored. Services and systems that address gaps and variations in patient social networks should be explored for their potential to reduce cancer health disparities. This study used a new method to identify the breadth and strength of social support following a diagnosis of breast cancer, especially examining the role of patient navigators in providing support. While navigators were only included in one quarter of patient

  18. Studying Dynamics in Business Networks

    DEFF Research Database (Denmark)

    Andersen, Poul Houman; Anderson, Helen; Havila, Virpi

    1998-01-01

    This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland......This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland...

  19. National Native American Breast Cancer Survivor's Network

    National Research Council Canada - National Science Library

    Burhansstipanov, Linda

    2002-01-01

    .... The purpose of this project is to improve the survival from breast cancer and quality of life after being diagnosed with breast cancer for both the patient and loved ones of the cancer patient...

  20. National Native American Breast Cancer Survivor's Network

    National Research Council Canada - National Science Library

    Burhansstipanov, Linda

    2003-01-01

    .... The purpose of this project is to improve the survival from breast cancer and quality of life after being diagnosed with breast cancer for both the patient and loved ones of the cancer patient...

  1. Biomarkers of Treatment Toxicity in Combined-Modality Cancer Therapies with Radiation and Systemic Drugs: Study Design, Multiplex Methods, Molecular Networks

    Directory of Open Access Journals (Sweden)

    Anne Hansen Ree

    2014-12-01

    Full Text Available Organ toxicity in cancer therapy is likely caused by an underlying disposition for given pathophysiological mechanisms in the individual patient. Mechanistic data on treatment toxicity at the patient level are scarce; hence, probabilistic and translational linkages among different layers of data information, all the way from cellular targets of the therapeutic exposure to tissues and ultimately the patient’s organ systems, are required. Throughout all of these layers, untoward treatment effects may be viewed as perturbations that propagate within a hierarchically structured network from one functional level to the next, at each level causing disturbances that reach a critical threshold, which ultimately are manifested as clinical adverse reactions. Advances in bioinformatics permit compilation of information across the various levels of data organization, presumably enabling integrated systems biology-based prediction of treatment safety. In view of the complexity of biological responses to cancer therapy, this communication reports on a “top-down” strategy, starting with the systematic assessment of adverse effects within a defined therapeutic context and proceeding to transcriptomic and proteomic analysis of relevant patient tissue samples and computational exploration of the resulting data, with the ultimate aim of utilizing information from functional connectivity networks in evaluation of patient safety in multimodal cancer therapy.

  2. A process for assessing the feasibility of a network meta-analysis: a case study of everolimus in combination with hormonal therapy versus chemotherapy for advanced breast cancer.

    Science.gov (United States)

    Cope, Shannon; Zhang, Jie; Saletan, Stephen; Smiechowski, Brielan; Jansen, Jeroen P; Schmid, Peter

    2014-06-05

    The aim of this study is to outline a general process for assessing the feasibility of performing a valid network meta-analysis (NMA) of randomized controlled trials (RCTs) to synthesize direct and indirect evidence for alternative treatments for a specific disease population. Several steps to assess the feasibility of an NMA are proposed based on existing recommendations. Next, a case study is used to illustrate this NMA feasibility assessment process in order to compare everolimus in combination with hormonal therapy to alternative chemotherapies in terms of progression-free survival for women with advanced breast cancer. A general process for assessing the feasibility of an NMA is outlined that incorporates explicit steps to visualize the heterogeneity in terms of treatment and outcome characteristics (Part A) as well as the study and patient characteristics (Part B). Additionally, steps are performed to illustrate differences within and across different types of direct comparisons in terms of baseline risk (Part C) and observed treatment effects (Part D) since there is a risk that the treatment effect modifiers identified may not explain the observed heterogeneity or inconsistency in the results due to unexpected, unreported or unmeasured differences. Depending on the data available, alternative approaches are suggested: list assumptions, perform a meta-regression analysis, subgroup analysis, sensitivity analyses, or summarize why an NMA is not feasible. The process outlined to assess the feasibility of an NMA provides a stepwise framework that will help to ensure that the underlying assumptions are systematically explored and that the risks (and benefits) of pooling and indirectly comparing treatment effects from RCTs for a particular research question are transparent.

  3. Case Studies - Cervical Cancer

    Centers for Disease Control (CDC) Podcasts

    2010-10-15

    Dr. Alan Waxman, a professor of obstetrics and gynecology at the University of New Mexico and chair of the American College of Obstetricians and Gynecologists (ACOG) committee for the underserved, talks about several case studies for cervical cancer screening and management.  Created: 10/15/2010 by National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP), Division of Cancer Prevention and Control (DCPC).   Date Released: 6/9/2010.

  4. Campus network security model study

    Science.gov (United States)

    Zhang, Yong-ku; Song, Li-ren

    2011-12-01

    Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.

  5. Fox Chase Network: Fox Chase Cancer Center's community hospital affiliation program.

    Science.gov (United States)

    Higman, S A; McKay, F J; Engstrom, P F; O'Grady, M A; Young, R C

    2000-01-01

    Fox Chase Cancer Center developed a format for affiliation with community providers in 1986. Fox Chase Network was formed to establish hospital-based community cancer centers to increase access to patients involved in clinical research. Under this program, the Fox Chase Network now contributes 500 patients per year to prevention and clinical research studies. As relationships with community providers form, patient referrals have increased at Fox Chase Cancer Center and for each Fox Chase Network member. A dedicated staff is required to operate the central office on a day-to-day basis as well as at each affiliate. We have found this to be a critical element in each program's success. New challenges in the cancer business-increasing volumes with declining revenue-have caused us to reconfigure the services offered to affiliates, while maintaining true to our mission: to reduce the burden of human cancer.

  6. TROVE: A User-friendly Tool for Visualizing and Analyzing Cancer Hallmarks in Signaling Networks.

    Science.gov (United States)

    Chua, Huey Eng; Bhowmick, Sourav S; Zheng, Jie

    2017-09-22

    Cancer hallmarks, a concept that seeks to explain the complexity of cancer initiation and development, provide a new perspective of studying cancer signaling which could lead to a greater understanding of this complex disease. However, to the best of our knowledge, there is currently a lack of tools that support such hallmark-based study of the cancer signaling network, thereby impeding the gain of knowledge in this area. We present TROVE, a user-friendly software that facilitates hallmark annotation, visualization and analysis in cancer signaling networks. In particular, TROVE facilitates hallmark analysis specific to particular cancer types. Available under the Eclipse Public License from: https://sites.google.com/site/cosbyntu/softwares/trove and https://github.com/trove2017/Trove. hechua@ntu.edu.sg or assourav@ntu.edu.sg. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  7. Modeling Cancer Metastasis using Global, Quantitative and Integrative Network Biology

    DEFF Research Database (Denmark)

    Schoof, Erwin; Erler, Janine

    understanding of molecular processes which are fundamental to tumorigenesis. In Article 1, we propose a novel framework for how cancer mutations can be studied by taking into account their effect at the protein network level. In Article 2, we demonstrate how global, quantitative data on phosphorylation dynamics...... can be generated using MS, and how this can be modeled using a computational framework for deciphering kinase-substrate dynamics. This framework is described in depth in Article 3, and covers the design of KinomeXplorer, which allows the prediction of kinases responsible for modulating observed...... phosphorylation dynamics in a given biological sample. In Chapter III, we move into Integrative Network Biology, where, by combining two fundamental technologies (MS & NGS), we can obtain more in-depth insights into the links between cellular phenotype and genotype. Article 4 describes the proof...

  8. Trends in intensity modulated radiation therapy use for locally advanced rectal cancer at National Comprehensive Cancer Network centers

    OpenAIRE

    Marsha Reyngold, MD, PhD; Joyce Niland, PhD; Anna ter Veer, MS; Tanios Bekaii-Saab, MD; Lily Lai, MD; Joshua E. Meyer, MD; Steven J. Nurkin, MD, MS; Deborah Schrag, MD, MPH; John M. Skibber, MD, FACS; Al B. Benson, MD; Martin R. Weiser, MD; Christopher H. Crane, MD; Karyn A. Goodman, MD, MS

    2018-01-01

    Purpose: Intensity modulated radiation therapy (IMRT) has been rapidly incorporated into clinical practice because of its technological advantages over 3-dimensional conformal radiation therapy (CRT). We characterized trends in IMRT utilization in trimodality treatment of locally advanced rectal cancer at National Comprehensive Cancer Network cancer centers between 2005 and 2011. Methods and materials: Using the prospective National Comprehensive Cancer Network Colorectal Cancer Database, ...

  9. Cancer signaling networks and their implications for personalized medicine

    DEFF Research Database (Denmark)

    Creixell, Pau

    Amongst the unique features of cancer cells perhaps the most crucial one is the change in the cellular decision-making process. While both non-cancer and cancer cells are constantly integrating different external cues that reach them and computing cellular decisions (e.g. proliferation or apoptosis......) based on the integration of these cues; this integration and consequently the cellular decisions taken by cancer cells are arguably very distinct from the decisions that would be expected from non-cancer cells. Since cellular signaling networks and its different states are the computational circuits...

  10. Breast cancer detection via Hu moment invariant and feedforward neural network

    Science.gov (United States)

    Zhang, Xiaowei; Yang, Jiquan; Nguyen, Elijah

    2018-04-01

    One of eight women can get breast cancer during all her life. This study used Hu moment invariant and feedforward neural network to diagnose breast cancer. With the help of K-fold cross validation, we can test the out-of-sample accuracy of our method. Finally, we found that our methods can improve the accuracy of detecting breast cancer and reduce the difficulty of judging.

  11. Gene Expression Correlation for Cancer Diagnosis: A Pilot Study

    Directory of Open Access Journals (Sweden)

    Binbing Ling

    2014-01-01

    Full Text Available Poor prognosis for late-stage, high-grade, and recurrent cancers has been motivating cancer researchers to search for more efficient biomarkers to identify the onset of cancer. Recent advances in constructing and dynamically analyzing biomolecular networks for different types of cancer have provided a promising novel strategy to detect tumorigenesis and metastasis. The observation of different biomolecular networks associated with normal and cancerous states led us to hypothesize that correlations for gene expressions could serve as valid indicators of early cancer development. In this pilot study, we tested our hypothesis by examining whether the mRNA expressions of three randomly selected cancer-related genes PIK3C3, PIM3, and PTEN were correlated during cancer progression and the correlation coefficients could be used for cancer diagnosis. Strong correlations (0.68≤r≤1.0 were observed between PIK3C3 and PIM3 in breast cancer, between PIK3C3 and PTEN in breast and ovary cancers, and between PIM3 and PTEN in breast, kidney, liver, and thyroid cancers during disease progression, implicating that the correlations for cancer network gene expressions could serve as a supplement to current clinical biomarkers, such as cancer antigens, for early cancer diagnosis.

  12. A Comprehensive Nuclear Receptor Network for Breast Cancer Cells

    Directory of Open Access Journals (Sweden)

    Ralf Kittler

    2013-02-01

    Full Text Available In breast cancer, nuclear receptors (NRs play a prominent role in governing gene expression, have prognostic utility, and are therapeutic targets. We built a regulatory map for 24 NRs, six chromatin state markers, and 14 breast-cancer-associated transcription factors (TFs that are expressed in the breast cancer cell line MCF-7. The resulting network reveals a highly interconnected regulatory matrix where extensive crosstalk occurs among NRs and other breast -cancer-associated TFs. We show that large numbers of factors are coordinately bound to highly occupied target regions throughout the genome, and these regions are associated with active chromatin state and hormone-responsive gene expression. This network also provides a framework for stratifying and predicting patient outcomes, and we use it to show that the peroxisome proliferator-activated receptor delta binds to a set of genes also regulated by the retinoic acid receptors and whose expression is associated with poor prognosis in breast cancer.

  13. Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks.

    Science.gov (United States)

    Ghanat Bari, Mehrab; Ung, Choong Yong; Zhang, Cheng; Zhu, Shizhen; Li, Hu

    2017-08-01

    Emerging evidence indicates the existence of a new class of cancer genes that act as "signal linkers" coordinating oncogenic signals between mutated and differentially expressed genes. While frequently mutated oncogenes and differentially expressed genes, which we term Class I cancer genes, are readily detected by most analytical tools, the new class of cancer-related genes, i.e., Class II, escape detection because they are neither mutated nor differentially expressed. Given this hypothesis, we developed a Machine Learning-Assisted Network Inference (MALANI) algorithm, which assesses all genes regardless of expression or mutational status in the context of cancer etiology. We used 8807 expression arrays, corresponding to 9 cancer types, to build more than 2 × 10 8 Support Vector Machine (SVM) models for reconstructing a cancer network. We found that ~3% of ~19,000 not differentially expressed genes are Class II cancer gene candidates. Some Class II genes that we found, such as SLC19A1 and ATAD3B, have been recently reported to associate with cancer outcomes. To our knowledge, this is the first study that utilizes both machine learning and network biology approaches to uncover Class II cancer genes in coordinating functionality in cancer networks and will illuminate our understanding of how genes are modulated in a tissue-specific network contribute to tumorigenesis and therapy development.

  14. Case Studies - Cervical Cancer

    Centers for Disease Control (CDC) Podcasts

    Dr. Alan Waxman, a professor of obstetrics and gynecology at the University of New Mexico and chair of the American College of Obstetricians and Gynecologists (ACOG) committee for the underserved, talks about several case studies for cervical cancer screening and management.

  15. Southeastern Cancer Study Group: breast cancer studies

    International Nuclear Information System (INIS)

    Smalley, R.V.; Bartolucci, A.A.; Moore, M.

    1983-01-01

    During the past 10 years, the Southeastern Cancer Study Group (SECSG) has been engaged in one major adjuvant study and three major advanced disease studies for patients with adenocarcinoma of the breast. The adjuvant study is demonstrating that six months of adjuvant CMF is the therapeutic equivalent of 12 months and that post-operative irradiation is of no added therapeutic benefit. In patients with advanced disease, a low dose 5 drug combination of CMFVP induces more objective responses than single agent 5FU, but improves survival only for those patients with liver metastases when compared to the sequential use of the same 5 single agents. The three drug combination, CAF, utilizing doxorubicin, induces more objective responses than low dose CMFVP, but it does not improve overall survival. The addition of a phase active combination, CAMELEON, (i.e., sequentially alternating therapy) of CAF has not improved the duration of disease control and survival for patients with liver metastases, lymphangitic and nodular lung metastases compared to CAF. Aggressive combination chemotherapeutic approaches to patients with advanced disease provide better and longer disease and tumor control but only marginal improvements in overall survival. Adding additional agents to a maximally tolerable regimen has not improved the therapeutic outcome

  16. A social network analysis of treatment discoveries in cancer.

    Directory of Open Access Journals (Sweden)

    Athanasios Tsalatsanis

    2011-03-01

    Full Text Available Controlled clinical trials are widely considered to be the vehicle to treatment discovery in cancer that leads to significant improvements in health outcomes including an increase in life expectancy. We have previously shown that the pattern of therapeutic discovery in randomized controlled trials (RCTs can be described by a power law distribution. However, the mechanism generating this pattern is unknown. Here, we propose an explanation in terms of the social relations between researchers in RCTs. We use social network analysis to study the impact of interactions between RCTs on treatment success. Our dataset consists of 280 phase III RCTs conducted by the NCI from 1955 to 2006. The RCT networks are formed through trial interactions formed i at random, ii based on common characteristics, or iii based on treatment success. We analyze treatment success in terms of survival hazard ratio as a function of the network structures. Our results show that the discovery process displays power law if there are preferential interactions between trials that may stem from researchers' tendency to interact selectively with established and successful peers. Furthermore, the RCT networks are "small worlds": trials are connected through a small number of ties, yet there is much clustering among subsets of trials. We also find that treatment success (improved survival is proportional to the network centrality measures of closeness and betweenness. Negative correlation exists between survival and the extent to which trials operate within a limited scope of information. Finally, the trials testing curative treatments in solid tumors showed the highest centrality and the most influential group was the ECOG. We conclude that the chances of discovering life-saving treatments are directly related to the richness of social interactions between researchers inherent in a preferential interaction model.

  17. Analysis of metastasis associated signal regulatory network in colorectal cancer.

    Science.gov (United States)

    Qi, Lu; Ding, Yanqing

    2018-06-18

    Metastasis is a key factor that affects the survival and prognosis of colorectal cancer patients. To elucidate molecular mechanism associated with the metastasis of colorectal cancer, genes related to the metastasis time of colorectal cancer were screened. Then, a network was constructed with this genes. Data was obtained from colorectal cancer expression profile. Molecular mechanism elucidated the time of tumor metastasis and the expression of genes related to colorectal cancer. We found that metastasis-promoting and metastasis-inhibiting networks included protein hubs of high connectivity. These protein hubs were components of organelles. Some ribosomal proteins promoted the metastasis of colorectal cancer. In some components of organelles, such as proteasomes, mitochondrial ribosome, ATP synthase, and splicing factors, the metastasis of colorectal cancer was inhibited by some sections of these organelles. After performing survival analysis of proteins in organelles, joint survival curve of proteins was constructed in ribosomal network. This joint survival curve showed metastasis was promoted in patients with colorectal cancer (P = 0.0022939). Joint survival curve of proteins was plotted against proteasomes (P = 7 e-07), mitochondrial ribosome (P = 0.0001157), ATP synthase (P = 0.0001936), and splicing factors (P = 1.35e-05). These curves indicate that metastasis of colorectal cancer can be inhibited. After analyzing proteins that bind with organelle components, we also found that some proteins were associated with the time of colorectal cancer metastasis. Hence, different cellular components play different roles in the metastasis of colorectal cancer. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

    Science.gov (United States)

    Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-01-01

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

  19. Construction and analysis of circular RNA molecular regulatory networks in liver cancer.

    Science.gov (United States)

    Ren, Shuangchun; Xin, Zhuoyuan; Xu, Yinyan; Xu, Jianting; Wang, Guoqing

    2017-01-01

    Liver cancer is the sixth most prevalent cancer, and the third most frequent cause of cancer-related deaths. Circular RNAs (circRNAs), a kind of special endogenous ncRNAs, have been coming back to the forefront of cancer genomics research. In this study, we used a systems biology approach to construct and analyze the circRNA molecular regulatory networks in the context of liver cancer. We detected a total of 127 differentially expressed circRNAs and 3,235 differentially expressed mRNAs. We selected the top-5 upregulated circRNAs to construct a circRNA-miRNA-mRNA network. We enriched the pathways and gene ontology items and determined their participation in cancer-related pathways such as p53 signaling pathway and pathways involved in angiogenesis and cell cycle. Quantitative real-time PCR was performed to verify the top-five circRNAs. ROC analysis showed circZFR, circFUT8, circIPO11 could significantly distinguish the cancer samples, with an AUC of 0.7069, 0.7575, and 0.7103, respectively. Our results suggest the circRNA-miRNA-mRNA network may help us further understand the molecular mechanisms of tumor progression in liver cancer, and reveal novel biomarkers and therapeutic targets.

  20. ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

    Science.gov (United States)

    Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

    2015-01-01

    Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

  1. Application of artificial neural network model combined with four biomarkers in auxiliary diagnosis of lung cancer.

    Science.gov (United States)

    Duan, Xiaoran; Yang, Yongli; Tan, Shanjuan; Wang, Sihua; Feng, Xiaolei; Cui, Liuxin; Feng, Feifei; Yu, Songcheng; Wang, Wei; Wu, Yongjun

    2017-08-01

    The purpose of the study was to explore the application of artificial neural network model in the auxiliary diagnosis of lung cancer and compare the effects of back-propagation (BP) neural network with Fisher discrimination model for lung cancer screening by the combined detections of four biomarkers of p16, RASSF1A and FHIT gene promoter methylation levels and the relative telomere length. Real-time quantitative methylation-specific PCR was used to detect the levels of three-gene promoter methylation, and real-time PCR method was applied to determine the relative telomere length. BP neural network and Fisher discrimination analysis were used to establish the discrimination diagnosis model. The levels of three-gene promoter methylation in patients with lung cancer were significantly higher than those of the normal controls. The values of Z(P) in two groups were 2.641 (0.008), 2.075 (0.038) and 3.044 (0.002), respectively. The relative telomere lengths of patients with lung cancer (0.93 ± 0.32) were significantly lower than those of the normal controls (1.16 ± 0.57), t = 4.072, P < 0.001. The areas under the ROC curve (AUC) and 95 % CI of prediction set from Fisher discrimination analysis and BP neural network were 0.670 (0.569-0.761) and 0.760 (0.664-0.840). The AUC of BP neural network was higher than that of Fisher discrimination analysis, and Z(P) was 0.76. Four biomarkers are associated with lung cancer. BP neural network model for the prediction of lung cancer is better than Fisher discrimination analysis, and it can provide an excellent and intelligent diagnosis tool for lung cancer.

  2. Incidence of colorectal cancer in new users and non-users of low-dose aspirin without existing cardiovascular disease: A cohort study using The Health Improvement Network.

    Science.gov (United States)

    Cea Soriano, Lucía; Soriano-Gabarró, Montse; García Rodríguez, Luis A

    2017-12-01

    Evidence regarding the chemo-protective effects of aspirin has influenced expert opinion in favour of low-dose aspirin use in certain patient populations without cardiovascular disease (CVD). The effects of aspirin in reducing the incidence of colorectal cancer (CRC) may be a large contributor to this favourable risk-benefit profile of low-dose aspirin in primary CVD prevention. Using The Health Improvement Network, we estimated the incidence of CRC in individuals free of CVD and either prescribed or not prescribed prophylactic low-dose aspirin. Two cohorts - new-users of low-dose aspirin (N=109,426) and a comparator cohort of non-users (N=154,056) at start of follow-up - were followed (maximum 13years) to identify incident CRC cases. Individuals with a record of CVD, cancer or low-dose aspirin prescription before start of follow-up were excluded. 2330 incident cases of CRC occurred; 885 in the aspirin cohort and 1445 in the comparator cohort, after mean follow-ups of 5.43years and 5.17years, respectively. Incidence rates of CRC per 10,000 person-years (95% confidence interval) were 14.90 (13.95-15.92) in the aspirin cohort and 18.15 (17.24-19.12) in the comparator cohort; incidence rate ratio 0.82 (0.76-0.89) adjusted for age, sex and primary care practitioner (PCP) visits in the previous year. Lower incidence rates were seen in the aspirin cohort for all strata evaluated (gender, age group and number of PCP visits in the previous year) except those aged ≥80years. Among most individuals without established CVD, initiation of low-dose aspirin is associated with a reduced incidence of CRC. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Network perturbation by recurrent regulatory variants in cancer.

    Directory of Open Access Journals (Sweden)

    Kiwon Jang

    2017-03-01

    Full Text Available Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes.

  4. Reconstructing the Prostate Cancer Transcriptional Regulatory Network

    Science.gov (United States)

    2010-09-01

    and disease prognosis. J Clin Oncol 2006;24:3763–70. 13. Klein CA, Schmidt- Kittler O, Schardt JA, Pantel K, Speicher MR, Riethmuller G. Comparative...Cancer Gene Discovery Jessica Kao1., Keyan Salari1,2., Melanie Bocanegra1, Yoon-La Choi1,3, Luc Girard4, Jeet Gandhi4, Kevin A. Kwei1, Tina Hernandez...JM, Klein RC, Oka M, Cowan KH (1995) Posttranscriptional regulation of the c-myb proto-oncogene in estrogen receptor-positive breast cancer cells

  5. Quantitative proteomics reveals middle infrared radiation-interfered networks in breast cancer cells.

    Science.gov (United States)

    Chang, Hsin-Yi; Li, Ming-Hua; Huang, Tsui-Chin; Hsu, Chia-Lang; Tsai, Shang-Ru; Lee, Si-Chen; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

    2015-02-06

    Breast cancer is one of the leading cancer-related causes of death worldwide. Treatment of triple-negative breast cancer (TNBC) is complex and challenging, especially when metastasis has developed. In this study, we applied infrared radiation as an alternative approach for the treatment of TNBC. We used middle infrared (MIR) with a wavelength range of 3-5 μm to irradiate breast cancer cells. MIR significantly inhibited cell proliferation in several breast cancer cells but did not affect the growth of normal breast epithelial cells. We performed iTRAQ-coupled LC-MS/MS analysis to investigate the MIR-triggered molecular mechanisms in breast cancer cells. A total of 1749 proteins were identified, quantified, and subjected to functional enrichment analysis. From the constructed functionally enriched network, we confirmed that MIR caused G2/M cell cycle arrest, remodeled the microtubule network to an astral pole arrangement, altered the actin filament formation and focal adhesion molecule localization, and reduced cell migration activity and invasion ability. Our results reveal the coordinative effects of MIR-regulated physiological responses in concentrated networks, demonstrating the potential implementation of infrared radiation in breast cancer therapy.

  6. Artificial neural networks as classification and diagnostic tools for lymph node-negative breast cancers

    Energy Technology Data Exchange (ETDEWEB)

    Eswari J, Satya; Chandrakar, Neha [National Institute of Technology Raipur, Raipur (India)

    2016-04-15

    Artificial neural networks (ANNs) can be used to develop a technique to classify lymph node negative breast cancer that is prone to distant metastases based on gene expression signatures. The neural network used is a multilayered feed forward network that employs back propagation algorithm. Once trained with DNA microarraybased gene expression profiles of genes that were predictive of distant metastasis recurrence of lymph node negative breast cancer, the ANNs became capable of correctly classifying all samples and recognizing the genes most appropriate to the classification. To test the ability of the trained ANN models in recognizing lymph node negative breast cancer, we analyzed additional idle samples that were not used beforehand for the training procedure and obtained the correctly classified result in the validation set. For more substantial result, bootstrapping of training and testing dataset was performed as external validation. This study illustrates the potential application of ANN for breast tumor diagnosis and the identification of candidate targets in patients for therapy.

  7. Social network characteristics and cervical cancer screening among Quechua women in Andean Peru.

    Science.gov (United States)

    Luque, John S; Opoku, Samuel; Ferris, Daron G; Guevara Condorhuaman, Wendy S

    2016-02-24

    Peru has high cervical cancer incidence and mortality rates compared to other Andean countries. Therefore, partnerships between governmental and international organizations have targeted rural areas of Peru to receive cervical cancer screening via outreach campaigns. Previous studies have found a relationship between a person's social networks and cancer screening behaviors. Screening outreach campaigns conducted by the nonprofit organization CerviCusco created an opportunity for a social network study to examine cervical cancer screening history and social network characteristics in a rural indigenous community that participated in these campaigns in 2012 and 2013. The aim of this study was to explore social network characteristics in this community related to receipt of cervical cancer screening following the campaigns. An egocentric social network questionnaire was used to collect cross-sectional network data on community participants. Each survey participant (ego) was asked to name six other women they knew (alters) and identify the nature of their relationship or tie (family, friend, neighbor, other), residential closeness (within 5 km), length of time known, frequency of communication, topics of conversation, and whether they lent money to the person, provided childcare or helped with transportation. In addition, each participant was asked to report the nature of the relationship between all alters identified (e.g., friend, family, or neighbor). Bivariate and multivariate analyses were used to explore the relationship between Pap test receipt at the CerviCusco outreach screening campaigns and social network characteristics. Bivariate results found significant differences in percentage of alter composition for neighbors and family, and for mean number of years known, mean density, and mean degree centrality between women who had received a Pap test (n = 19) compared to those who had not (n = 50) (p's < 0.05). The final logistic regression model was

  8. Network of microRNAs-mRNAs Interactions in Pancreatic Cancer

    Science.gov (United States)

    Naderi, Elnaz; Mostafaei, Mehdi; Pourshams, Akram

    2014-01-01

    Background. MicroRNAs are small RNA molecules that regulate the expression of certain genes through interaction with mRNA targets and are mainly involved in human cancer. This study was conducted to make the network of miRNAs-mRNAs interactions in pancreatic cancer as the fourth leading cause of cancer death. Methods. 56 miRNAs that were exclusively expressed and 1176 genes that were downregulated or silenced in pancreas cancer were extracted from beforehand investigations. MiRNA–mRNA interactions data analysis and related networks were explored using MAGIA tool and Cytoscape 3 software. Functional annotations of candidate genes in pancreatic cancer were identified by DAVID annotation tool. Results. This network is made of 217 nodes for mRNA, 15 nodes for miRNA, and 241 edges that show 241 regulations between 15 miRNAs and 217 target genes. The miR-24 was the most significantly powerful miRNA that regulated series of important genes. ACVR2B, GFRA1, and MTHFR were significant target genes were that downregulated. Conclusion. Although the collected previous data seems to be a treasure trove, there was no study simultaneous to analysis of miRNAs and mRNAs interaction. Network of miRNA-mRNA interactions will help to corroborate experimental remarks and could be used to refine miRNA target predictions for developing new therapeutic approaches. PMID:24895587

  9. Network of microRNAs-mRNAs Interactions in Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    Elnaz Naderi

    2014-01-01

    Full Text Available Background. MicroRNAs are small RNA molecules that regulate the expression of certain genes through interaction with mRNA targets and are mainly involved in human cancer. This study was conducted to make the network of miRNAs-mRNAs interactions in pancreatic cancer as the fourth leading cause of cancer death. Methods. 56 miRNAs that were exclusively expressed and 1176 genes that were downregulated or silenced in pancreas cancer were extracted from beforehand investigations. MiRNA–mRNA interactions data analysis and related networks were explored using MAGIA tool and Cytoscape 3 software. Functional annotations of candidate genes in pancreatic cancer were identified by DAVID annotation tool. Results. This network is made of 217 nodes for mRNA, 15 nodes for miRNA, and 241 edges that show 241 regulations between 15 miRNAs and 217 target genes. The miR-24 was the most significantly powerful miRNA that regulated series of important genes. ACVR2B, GFRA1, and MTHFR were significant target genes were that downregulated. Conclusion. Although the collected previous data seems to be a treasure trove, there was no study simultaneous to analysis of miRNAs and mRNAs interaction. Network of miRNA-mRNA interactions will help to corroborate experimental remarks and could be used to refine miRNA target predictions for developing new therapeutic approaches.

  10. The National Cancer Institute's Physical Sciences - Oncology Network

    Science.gov (United States)

    Espey, Michael Graham

    In 2009, the NCI launched the Physical Sciences - Oncology Centers (PS-OC) initiative with 12 Centers (U54) funded through 2014. The current phase of the Program includes U54 funded Centers with the added feature of soliciting new Physical Science - Oncology Projects (PS-OP) U01 grant applications through 2017; see NCI PAR-15-021. The PS-OPs, individually and along with other PS-OPs and the Physical Sciences-Oncology Centers (PS-OCs), comprise the Physical Sciences-Oncology Network (PS-ON). The foundation of the Physical Sciences-Oncology initiative is a high-risk, high-reward program that promotes a `physical sciences perspective' of cancer and fosters the convergence of physical science and cancer research by forming transdisciplinary teams of physical scientists (e.g., physicists, mathematicians, chemists, engineers, computer scientists) and cancer researchers (e.g., cancer biologists, oncologists, pathologists) who work closely together to advance our understanding of cancer. The collaborative PS-ON structure catalyzes transformative science through increased exchange of people, ideas, and approaches. PS-ON resources are leveraged to fund Trans-Network pilot projects to enable synergy and cross-testing of experimental and/or theoretical concepts. This session will include a brief PS-ON overview followed by a strategic discussion with the APS community to exchange perspectives on the progression of trans-disciplinary physical sciences in cancer research.

  11. Design The Cervical Cancer Detector Use The Artificial Neural Network

    International Nuclear Information System (INIS)

    Af'idah, Dwi Intan; Widianto, Eko Didik; Setyawan, Budi

    2013-01-01

    Cancer is one of the contagious diseases that become a public health issue, both in the world and in Indonesia. In the world, 12% of all deaths caused by cancer and is the second killer after cardiovascular disease. Early detection using the IVA is a practical and inexpensive (only requiring acetic acid). However, the accuracy of the method is quite low, as it can not detect the stage of the cancer. While other methods have a better sensitivity than the IVA method, is a method of PAP smear. However, this method is relatively expensive, and requires an experienced pathologist-cytologist. According to the case above, Considered important to make the cancer cervics detector that is used to detect the abnormality and cervical cancer stage and consists of a digital microscope, as well as a computer application based on artificial neural network. The use of cervical cancer detector software and hardware are integrated each other. After the specifications met, the steps to design the cervical cancer detection are: Modifying a conventional microscope by adding a lens, image recording, and the lights, Programming the tools, designing computer applications, Programming features abnormality detection and staging of cancer.

  12. Network analysis of cancer PSB 2014 Poster

    OpenAIRE

    McDermott, Jason

    2014-01-01

    Cancer is, in general, a complex disease; it operates on pathways and systems, not solely on the individual components of those systems (genes or proteins). We have gathered global proteomic and phosphoproteomic data from a set of tumors with existing genomic data (sequencing, methylation, miRNA and mRNA expression) associated with a range of survival phenotypes. We report on our recent progress in analyzing proteomic, phosphoproteomic, and accompanying genomic data in terms of pathways that ...

  13. Offline Social Relationships and Online Cancer Communication: Effects of Social and Family Support on Online Social Network Building.

    Science.gov (United States)

    Namkoong, Kang; Shah, Dhavan V; Gustafson, David H

    2017-11-01

    This study investigates how social support and family relationship perceptions influence breast cancer patients' online communication networks in a computer-mediated social support (CMSS) group. To examine social interactions in the CMSS group, we identified two types of online social networks: open and targeted communication networks. The open communication network reflects group communication behaviors (i.e., one-to-many or "broadcast" communication) in which the intended audience is not specified; in contrast, the targeted communication network reflects interpersonal discourses (i.e., one-to-one or directed communication) in which the audience for the message is specified. The communication networks were constructed by tracking CMSS group usage data of 237 breast cancer patients who participated in one of two National Cancer Institute-funded randomized clinical trials. Eligible subjects were within 2 months of a diagnosis of primary breast cancer or recurrence at the time of recruitment. Findings reveal that breast cancer patients who perceived less availability of offline social support had a larger social network size in the open communication network. In contrast, those who perceived less family cohesion had a larger targeted communication network in the CMSS group, meaning they were inclined to use the CMSS group for developing interpersonal relationships.

  14. Identifying colon cancer risk modules with better classification performance based on human signaling network.

    Science.gov (United States)

    Qu, Xiaoli; Xie, Ruiqiang; Chen, Lina; Feng, Chenchen; Zhou, Yanyan; Li, Wan; Huang, Hao; Jia, Xu; Lv, Junjie; He, Yuehan; Du, Youwen; Li, Weiguo; Shi, Yuchen; He, Weiming

    2014-10-01

    Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. Copyright © 2013. Published by Elsevier Inc.

  15. Large-Scale Analysis of Network Bistability for Human Cancers

    Science.gov (United States)

    Shiraishi, Tetsuya; Matsuyama, Shinako; Kitano, Hiroaki

    2010-01-01

    Protein–protein interaction and gene regulatory networks are likely to be locked in a state corresponding to a disease by the behavior of one or more bistable circuits exhibiting switch-like behavior. Sets of genes could be over-expressed or repressed when anomalies due to disease appear, and the circuits responsible for this over- or under-expression might persist for as long as the disease state continues. This paper shows how a large-scale analysis of network bistability for various human cancers can identify genes that can potentially serve as drug targets or diagnosis biomarkers. PMID:20628618

  16. Stacking denoising auto-encoders in a deep network to segment the brainstem on MRI in brain cancer patients: A clinical study.

    Science.gov (United States)

    Dolz, Jose; Betrouni, Nacim; Quidet, Mathilde; Kharroubi, Dris; Leroy, Henri A; Reyns, Nicolas; Massoptier, Laurent; Vermandel, Maximilien

    2016-09-01

    Delineation of organs at risk (OARs) is a crucial step in surgical and treatment planning in brain cancer, where precise OARs volume delineation is required. However, this task is still often manually performed, which is time-consuming and prone to observer variability. To tackle these issues a deep learning approach based on stacking denoising auto-encoders has been proposed to segment the brainstem on magnetic resonance images in brain cancer context. Additionally to classical features used in machine learning to segment brain structures, two new features are suggested. Four experts participated in this study by segmenting the brainstem on 9 patients who underwent radiosurgery. Analysis of variance on shape and volume similarity metrics indicated that there were significant differences (p<0.05) between the groups of manual annotations and automatic segmentations. Experimental evaluation also showed an overlapping higher than 90% with respect to the ground truth. These results are comparable, and often higher, to those of the state of the art segmentation methods but with a considerably reduction of the segmentation time. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Deregulation of an imprinted gene network in prostate cancer.

    Science.gov (United States)

    Ribarska, Teodora; Goering, Wolfgang; Droop, Johanna; Bastian, Klaus-Marius; Ingenwerth, Marc; Schulz, Wolfgang A

    2014-05-01

    Multiple epigenetic alterations contribute to prostate cancer progression by deregulating gene expression. Epigenetic mechanisms, especially differential DNA methylation at imprinting control regions (termed DMRs), normally ensure the exclusive expression of imprinted genes from one specific parental allele. We therefore wondered to which extent imprinted genes become deregulated in prostate cancer and, if so, whether deregulation is due to altered DNA methylation at DMRs. Therefore, we selected presumptive deregulated imprinted genes from a previously conducted in silico analysis and from the literature and analyzed their expression in prostate cancer tissues by qRT-PCR. We found significantly diminished expression of PLAGL1/ZAC1, MEG3, NDN, CDKN1C, IGF2, and H19, while LIT1 was significantly overexpressed. The PPP1R9A gene, which is imprinted in selected tissues only, was strongly overexpressed, but was expressed biallelically in benign and cancerous prostatic tissues. Expression of many of these genes was strongly correlated, suggesting co-regulation, as in an imprinted gene network (IGN) reported in mice. Deregulation of the network genes also correlated with EZH2 and HOXC6 overexpression. Pyrosequencing analysis of all relevant DMRs revealed generally stable DNA methylation between benign and cancerous prostatic tissues, but frequent hypo- and hyper-methylation was observed at the H19 DMR in both benign and cancerous tissues. Re-expression of the ZAC1 transcription factor induced H19, CDKN1C and IGF2, supporting its function as a nodal regulator of the IGN. Our results indicate that a group of imprinted genes are coordinately deregulated in prostate cancers, independently of DNA methylation changes.

  18. Estimation of the proteomic cancer co-expression sub networks by using association estimators.

    Directory of Open Access Journals (Sweden)

    Cihat Erdoğan

    Full Text Available In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA. Correlation and mutual information (MI based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators' performance, a multi-layer data integration platform on gene-disease associations (DisGeNET and the Molecular Signatures Database (MSigDB was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink and 64% for Schurmann-Grassberger (SG association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists.

  19. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    Science.gov (United States)

    Park, Chihyun; Ahn, Jaegyoon; Kim, Hyunjin; Park, Sanghyun

    2014-01-01

    The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  20. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    Directory of Open Access Journals (Sweden)

    Chihyun Park

    Full Text Available BACKGROUND: The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. RESULTS: In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. CONCLUSIONS: The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  1. Social Networking Site Usage Among Childhood Cancer Survivors - A Potential Tool for Research Recruitment?

    Science.gov (United States)

    Seltzer, Erica D.; Stolley, Melinda R.; Mensah, Edward K.; Sharp, Lisa K.

    2014-01-01

    Purpose The recent and rapid growth of social networking site (SNS) use presents a unique public health opportunity to develop effective strategies for the recruitment of hard-to-reach participants for cancer research studies. This survey investigated childhood cancer survivors’ reported use of SNS such as facebook or MySpace and their perceptions of using SNS, for recruitment into survivorship research. Methods Sixty White, Black and Hispanic, adult childhood cancer survivors (range 18 – 48 years of age) that were randomly selected from a larger childhood cancer study, the Chicago Healthy Living Study (CHLS), participated in this pilot survey. Telephone surveys were conducted to understand current SNS activity and attitudes towards using SNS as a cancer research recruitment tool. Results Seventy percent of participants reported SNS usage of which 80% were at least weekly users and 79 % reported positive attitudes towards the use of SNS as a recruitment tool for survivorship research. Conclusions and implications for cancer survivors The results of this pilot study revealed that SNS use was high and regular among the childhood cancer survivors sampled. Most had positive attitudes towards using SNS for recruitment of research. The results of this pilot survey suggest that SNS may offer an alternative approach for recruitment of childhood cancer survivors into research. PMID:24532046

  2. The cancer cell map initiative: defining the hallmark networks of cancer.

    Science.gov (United States)

    Krogan, Nevan J; Lippman, Scott; Agard, David A; Ashworth, Alan; Ideker, Trey

    2015-05-21

    Progress in DNA sequencing has revealed the startling complexity of cancer genomes, which typically carry thousands of somatic mutations. However, it remains unclear which are the key driver mutations or dependencies in a given cancer and how these influence pathogenesis and response to therapy. Although tumors of similar types and clinical outcomes can have patterns of mutations that are strikingly different, it is becoming apparent that these mutations recurrently hijack the same hallmark molecular pathways and networks. For this reason, it is likely that successful interpretation of cancer genomes will require comprehensive knowledge of the molecular networks under selective pressure in oncogenesis. Here we announce the creation of a new effort, The Cancer Cell Map Initiative (CCMI), aimed at systematically detailing these complex interactions among cancer genes and how they differ between diseased and healthy states. We discuss recent progress that enables creation of these cancer cell maps across a range of tumor types and how they can be used to target networks disrupted in individual patients, significantly accelerating the development of precision medicine. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Proactive recruitment of cancer patients’ social networks into a smoking cessation trial

    Science.gov (United States)

    Bastian, Lori A.; Fish, Laura J.; Peterson, Bercedis L.; Biddle, Andrea K.; Garst, Jennifer; Lyna, Pauline; Molner, Stephanie; Bepler, Gerold; Kelley, Mike; Keefe, Francis J.; McBride, Colleen M.

    2011-01-01

    Background This report describes the characteristics associated with successful enrollment of smokers in the social networks (i.e., family and close friends) of patients with lung cancer into a smoking cessation intervention. Methods Lung cancer patients from four clinical sites were asked to complete a survey enumerating their family members and close friends who smoke, and provide permission to contact these potential participants. Family members and close friends identified as smokers were interviewed and offered participation in a smoking cessation intervention. Repeated measures logistic regression model examined characteristics associated with enrollment. Results A total of 1,062 eligible lung cancer patients were identified and 516 patients consented and completed the survey. These patients identified 1,325 potentially eligible family and close friends. Of these, 496 consented and enrolled in the smoking cessation program. Network enrollment was highest among patients who were white and had late-stage disease. Social network members enrolled were most likely to be female, a birth family, immediate family, or close friend, and live in close geographic proximity to the patient. Conclusions Proactive recruitment of smokers in the social networks of lung cancer patients is challenging. In this study, the majority of family members and friends declined to participate. Enlisting immediate female family members and friends, who live close to the patient as agents to proactively recruit other network members into smoking cessation trials could be used to extend reach of cessation interventions to patients’ social networks. Moreover, further consideration should be given to the appropriate timing of approaching network smokers to consider cessation. PMID:21382509

  4. Social ties and risk for cancer - a prospective cohort study

    DEFF Research Database (Denmark)

    Bergelt, Corinna; Prescott, Eva; Grønbaek, Morten

    2009-01-01

    consisted of 8 548 Danes who had been examined in 1991-1994 within the Copenhagen City Heart Study. The median length of follow-up was 9.3 years (range, 0-11.2 years). Social ties were measured from answers to a questionnaire on social networks. Regression analyses for cancers at the most frequent sites......BACKGROUND: Poor social support and small social networks have been associated with increased risks for conditions such as coronary heart disease as well as with overall mortality. We investigated the association between social ties and risk for cancer. MATERIAL AND METHODS: The study sample...... (breast, lung, prostate and colon and rectum) were conducted with the Cox proportional hazards model, with adjustment for a number of well-known risk factors for cancer. RESULTS: While we found no significant association between social ties and risk for cancer in men, women with high social network scores...

  5. Social ties and risk for cancer - a prospective cohort study

    DEFF Research Database (Denmark)

    Bergelt, C.; Prescott, E.; Gronbaek, M.

    2009-01-01

    consisted of 8 548 Danes who had been examined in 1991-1994 within the Copenhagen City Heart Study. The median length of follow-up was 9.3 years (range, 0-11.2 years). Social ties were measured from answers to a questionnaire on social networks. Regression analyses for cancers at the most frequent sites......Background. Poor social support and small social networks have been associated with increased risks for conditions such as coronary heart disease as well as with overall mortality. We investigated the association between social ties and risk for cancer. Material and methods. The study sample...... (breast, lung, prostate and colon and rectum) were conducted with the Cox proportional hazards model, with adjustment for a number of well-known risk factors for cancer. Results. While we found no significant association between social ties and risk for cancer in men, women with high social network scores...

  6. Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes.

    Science.gov (United States)

    Chen, Juan; Xu, Juan; Li, Yongsheng; Zhang, Jinwen; Chen, Hong; Lu, Jianping; Wang, Zishan; Zhao, Xueying; Xu, Kang; Li, Yixue; Li, Xia; Zhang, Yan

    2017-02-07

    Although competing endogenous RNAs (ceRNAs) have been implicated in many solid tumors, their roles in breast cancer subtypes are not well understood. We therefore generated a ceRNA network for each subtype based on the significance of both, positive co-expression and the shared miRNAs, in the corresponding subtype miRNA dys-regulatory network, which was constructed based on negative regulations between differentially expressed miRNAs and targets. All four subtype ceRNA networks exhibited scale-free architecture and showed that the common ceRNAs were at the core of the networks. Furthermore, the common ceRNA hubs had greater connectivity than the subtype-specific hubs. Functional analysis of the common subtype ceRNA hubs highlighted factors involved in proliferation, MAPK signaling pathways and tube morphogenesis. Subtype-specific ceRNA hubs highlighted unique subtype-specific pathways, like the estrogen response and inflammatory pathways in the luminal subtypes or the factors involved in the coagulation process that participates in the basal-like subtype. Ultimately, we identified 29 critical subtype-specific ceRNA hubs that characterized the different breast cancer subtypes. Our study thus provides new insight into the common and specific subtype ceRNA interactions that define the different categories of breast cancer and enhances our understanding of the pathology underlying the different breast cancer subtypes, which can have prognostic and therapeutic implications in the future.

  7. Cooperation among cancer cells as public goods games on Voronoi networks.

    Science.gov (United States)

    Archetti, Marco

    2016-05-07

    Cancer cells produce growth factors that diffuse and sustain tumour proliferation, a form of cooperation that can be studied using mathematical models of public goods in the framework of evolutionary game theory. Cell populations, however, form heterogeneous networks that cannot be described by regular lattices or scale-free networks, the types of graphs generally used in the study of cooperation. To describe the dynamics of growth factor production in populations of cancer cells, I study public goods games on Voronoi networks, using a range of non-linear benefits that account for the known properties of growth factors, and different types of diffusion gradients. The results are surprisingly similar to those obtained on regular graphs and different from results on scale-free networks, revealing that network heterogeneity per se does not promote cooperation when public goods diffuse beyond one-step neighbours. The exact shape of the diffusion gradient is not crucial, however, whereas the type of non-linear benefit is an essential determinant of the dynamics. Public goods games on Voronoi networks can shed light on intra-tumour heterogeneity, the evolution of resistance to therapies that target growth factors, and new types of cell therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Oral cancer: A multicenter study.

    Science.gov (United States)

    Dhanuthai, K; Rojanawatsirivej, S; Thosaporn, W; Kintarak, S; Subarnbhesaj, A; Darling, M; Kryshtalskyj, E; Chiang, C-P; Shin, H-I; Choi, S-Y; Lee, S-S; Aminishakib, P

    2018-01-01

    To determine the prevalence and clinicopathologic features of the oral cancer patients. Biopsy records of the participating institutions were reviewed for oral cancer cases diagnosed from 2005 to 2014. Demographic data and site of the lesions were collected. Sites of the lesion were subdivided into lip, tongue, floor of the mouth, gingiva, alveolar mucosa, palate, buccal/labial mucosa, maxilla and mandible. Oral cancer was subdivided into 7 categories: epithelial tumors, salivary gland tumors, hematologic tumors, bone tumors, mesenchymal tumors, odontogenic tumors, and others. Data were analyzed by descriptive statistics using SPSS software version 17.0. Of the 474,851 accessioned cases, 6,151 cases (1.30%) were diagnosed in the category of oral cancer. The mean age of the patients was 58.37±15.77 years. A total of 4,238 cases (68.90%) were diagnosed in males, whereas 1911 cases (31.07%) were diagnosed in females. The male-to-female ratio was 2.22:1. The sites of predilection for oral cancer were tongue, labial/buccal mucosa, gingiva, palate, and alveolar mucosa, respectively. The three most common oral cancer in the descending order of frequency were squamous cell carcinoma, non-Hodgkin lymphoma and mucoepidermoid carcinoma. Although the prevalence of oral cancer is not high compared to other entities, oral cancer pose significant mortality and morbidity in the patients, especially when discovered late in the course of the disease. This study highlights some anatomical locations where oral cancers are frequently encountered. As a result, clinicians should pay attention to not only teeth, but oral mucosa especially in the high prevalence area as well since early detection of precancerous lesions or cancers in the early stage increase the chance of patient being cured and greatly reduce the mortality and morbidity. This study also shows some differences between pediatric and elderly oral cancer patients as well as between Asian and non-Asian oral cancer patients.

  9. A research about breast cancer detection using different neural networks and K-MICA algorithm

    Directory of Open Access Journals (Sweden)

    A A Kalteh

    2013-01-01

    Full Text Available Breast cancer is the second leading cause of death for women all over the world. The correct diagnosis of breast cancer is one of the major problems in the medical field. From the literature it has been found that different pattern recognition techniques can help them to improve in this domain. This paper presents a novel hybrid intelligent method for detection of breast cancer. The proposed method includes two main modules: Clustering module and the classifier module. In the clustering module, first the input data will be clustered by a new technique. This technique is a suitable combination of the modified imperialist competitive algorithm (MICA and K-means algorithm. Then the Euclidean distance of each pattern is computed from the determined clusters. The classifier module determines the membership of the patterns using the computed distance. In this module, several neural networks, such as the multilayer perceptron, probabilistic neural networks and the radial basis function neural networks are investigated. Using the experimental study, we choose the best classifier in order to recognize the breast cancer. The proposed system is tested on Wisconsin Breast Cancer (WBC database and the simulation results show that the recommended system has high accuracy.

  10. Social networks, social support mechanisms, and quality of life after breast cancer diagnosis.

    Science.gov (United States)

    Kroenke, Candyce H; Kwan, Marilyn L; Neugut, Alfred I; Ergas, Isaac J; Wright, Jaime D; Caan, Bette J; Hershman, Dawn; Kushi, Lawrence H

    2013-06-01

    We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006 to 2011 and provided data on social networks (the presence of a spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible support, emotional/informational support, affection, positive social interaction), and QOL, measured by the FACT-B, approximately 2 months post diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower versus higher than median QOL scores. We further stratified by stage at diagnosis and treatment. In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR = 2.18, 95 % CI: 1.72-2.77), physical well-being (WB) (OR = 1.61, 95 % CI: 1.27-2.03), functional WB (OR = 2.08, 95 % CI: 1.65-2.63), social WB (OR = 3.46, 95 % CI: 2.73-4.39), and emotional WB (OR = 1.67, 95 % CI: 1.33-2.11) scores and higher breast cancer symptoms (OR = 1.48, 95 % CI: 1.18-1.87) compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was "positive social interaction." However, each type of support was important depending on outcome, stage, and treatment status. Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status.

  11. Social networks, social support mechanisms, and quality of life after breast cancer diagnosis

    Science.gov (United States)

    Kroenke, Candyce H; Kwan, Marilyn L.; Neugut, Alfred I.; Ergas, Isaac J.; Wright, Jaime D.; Caan, Bette J.; Hershman, Dawn; Kushi, Lawrence H.

    2013-01-01

    Purpose We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. Methods This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006-2011 and provided data on social networks (presence of spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible, emotional/informational, affection, positive social interaction), and quality of life (QOL), measured by the FACT-B, approximately two months post-diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower vs. higher than median QOL scores. We further stratified by stage at diagnosis and treatment. Results In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR=2.18, 95%CI:1.72-2.77), physical well-being (WB) (OR=1.61, 95%CI:1.27-2.03), functional WB (OR=2.08, 95%CI:1.65-2.63), social WB (OR=3.46, 95%CI:2.73-4.39), and emotional WB (OR=1.67, 95%CI:1.33-2.11) scores and higher breast cancer symptoms (OR=1.48, 95%CI:1.18-1.87), compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was “positive social interaction”. However, each type of support was important depending on outcome, stage, and treatment status. Conclusions Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status. PMID:23657404

  12. Network Approach in Political Communication Studies

    Directory of Open Access Journals (Sweden)

    Нина Васильевна Опанасенко

    2013-12-01

    Full Text Available The article is devoted to issues of network approach application in political communication studies. The author considers communication in online and offline areas and gives the definition of rhizome, its characteristics, identifies links between rhizome and network approach. The author also analyses conditions and possibilities of the network approach in modern political communication. Both positive and negative features of the network approach are emphasized.

  13. Social networking site usage among childhood cancer survivors--a potential tool for research recruitment?

    Science.gov (United States)

    Seltzer, Erica D; Stolley, Melinda R; Mensah, Edward K; Sharp, Lisa K

    2014-09-01

    The recent and rapid growth of social networking site (SNS) use presents a unique public health opportunity to develop effective strategies for the recruitment of hard-to-reach participants for cancer research studies. This survey investigated childhood cancer survivors' reported use of SNS such as Facebook or MySpace and their perceptions of using SNS, for recruitment into survivorship research. Sixty White, Black, and Hispanic adult childhood cancer survivors (range 18-48 years of age) that were randomly selected from a larger childhood cancer study, the Chicago Healthy Living Study, participated in this pilot survey. Telephone surveys were conducted to understand current SNS activity and attitudes towards using SNS as a cancer research recruitment tool. Seventy percent of participants reported SNS usage of which 80 % were at least weekly users and 79 % reported positive attitudes towards the use of SNS as a recruitment tool for survivorship research. The results of this pilot study revealed that SNS use was high and regular among the childhood cancer survivors sampled. Most had positive attitudes towards using SNS for recruitment of research. The results of this pilot survey suggest that SNS may offer an alternative approach for recruitment of childhood cancer survivors into research.

  14. The redox biology network in cancer pathophysiology and therapeutics

    Directory of Open Access Journals (Sweden)

    Gina Manda

    2015-08-01

    Full Text Available The review pinpoints operational concepts related to the redox biology network applied to the pathophysiology and therapeutics of solid tumors. A sophisticated network of intrinsic and extrinsic cues, integrated in the tumor niche, drives tumorigenesis and tumor progression. Critical mutations and distorted redox signaling pathways orchestrate pathologic events inside cancer cells, resulting in resistance to stress and death signals, aberrant proliferation and efficient repair mechanisms. Additionally, the complex inter-cellular crosstalk within the tumor niche, mediated by cytokines, redox-sensitive danger signals (HMGB1 and exosomes, under the pressure of multiple stresses (oxidative, inflammatory, metabolic, greatly contributes to the malignant phenotype. The tumor-associated inflammatory stress and its suppressive action on the anti-tumor immune response are highlighted. We further emphasize that ROS may act either as supporter or enemy of cancer cells, depending on the context. Oxidative stress-based therapies, such as radiotherapy and photodynamic therapy, take advantage of the cytotoxic face of ROS for killing tumor cells by a non-physiologically sudden, localized and intense oxidative burst. The type of tumor cell death elicited by these therapies is discussed. Therapy outcome depends on the differential sensitivity to oxidative stress of particular tumor cells, such as cancer stem cells, and therefore co-therapies that transiently down-regulate their intrinsic antioxidant system hold great promise. We draw attention on the consequences of the damage signals delivered by oxidative stress-injured cells to neighboring and distant cells, and emphasize the benefits of therapeutically triggered immunologic cell death in metastatic cancer. An integrative approach should be applied when designing therapeutic strategies in cancer, taking into consideration the mutational, metabolic, inflammatory and oxidative status of tumor cells, cellular

  15. Classification of breast cancer histology images using Convolutional Neural Networks.

    Directory of Open Access Journals (Sweden)

    Teresa Araújo

    Full Text Available Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods designed for a specific problem based on field-knowledge. To overcome the many difficulties of the feature-based approaches, deep learning methods are becoming important alternatives. A method for the classification of hematoxylin and eosin stained breast biopsy images using Convolutional Neural Networks (CNNs is proposed. Images are classified in four classes, normal tissue, benign lesion, in situ carcinoma and invasive carcinoma, and in two classes, carcinoma and non-carcinoma. The architecture of the network is designed to retrieve information at different scales, including both nuclei and overall tissue organization. This design allows the extension of the proposed system to whole-slide histology images. The features extracted by the CNN are also used for training a Support Vector Machine classifier. Accuracies of 77.8% for four class and 83.3% for carcinoma/non-carcinoma are achieved. The sensitivity of our method for cancer cases is 95.6%.

  16. Bayesian networks for clinical decision support in lung cancer care.

    Directory of Open Access Journals (Sweden)

    M Berkan Sesen

    Full Text Available Survival prediction and treatment selection in lung cancer care are characterised by high levels of uncertainty. Bayesian Networks (BNs, which naturally reason with uncertain domain knowledge, can be applied to aid lung cancer experts by providing personalised survival estimates and treatment selection recommendations. Based on the English Lung Cancer Database (LUCADA, we evaluate the feasibility of BNs for these two tasks, while comparing the performances of various causal discovery approaches to uncover the most feasible network structure from expert knowledge and data. We show first that the BN structure elicited from clinicians achieves a disappointing area under the ROC curve of 0.75 (± 0.03, whereas a structure learned by the CAMML hybrid causal discovery algorithm, which adheres with the temporal restrictions, achieves 0.81 (± 0.03. Second, our causal intervention results reveal that BN treatment recommendations, based on prescribing the treatment plan that maximises survival, can only predict the recorded treatment plan 29% of the time. However, this percentage rises to 76% when partial matches are included.

  17. MicroRNA functional network in pancreatic cancer: From biology to ...

    Indian Academy of Sciences (India)

    [Wang J and Sen S 2011 MicroRNA functional network in pancreatic cancer: From biology to biomarkers of disease. ... growth factor type I receptor; INSR, insulin receptor; IPA, Ingenuity Pathway Analysis; IPMN, ..... Prostate cancer signalling.

  18. A Network Pharmacology Approach to Uncover the Multiple Mechanisms of Hedyotis diffusa Willd. on Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Xinkui Liu

    2018-01-01

    Full Text Available Background. As one of the most frequently diagnosed cancer diseases globally, colorectal cancer (CRC remains an important cause of cancer-related death. Although the traditional Chinese herb Hedyotis diffusa Willd. (HDW has been proven to be effective for treating CRC in clinical practice, its definite mechanisms have not been completely deciphered. Objective. The aim of our research is to systematically explore the multiple mechanisms of HDW on CRC. Methods. This study adopted the network pharmacology approach, which was mainly composed of active component gathering, target prediction, CRC gene collection, network analysis, and gene enrichment analysis. Results. The network analysis showed that 10 targets might be the therapeutic targets of HDW on CRC, namely, HRAS, PIK3CA, KRAS, TP53, APC, BRAF, GSK3B, CDK2, AKT1, and RAF1. The gene enrichment analysis implied that HDW probably benefits patients with CRC by modulating pathways related to cancers, infectious diseases, endocrine system, immune system, nervous system, signal transduction, cellular community, and cell motility. Conclusions. This study partially verified and predicted the pharmacological and molecular mechanism of HDW against CRC from a holistic perspective, which will also lay a foundation for the further experimental research and clinical rational application of HDW.

  19. Toward standardizing and reporting colorectal cancer screening indicators on an international level: The International Colorectal Cancer Screening Network

    NARCIS (Netherlands)

    Benson, Victoria S.; Atkin, Wendy S.; Green, Jane; Nadel, Marion R.; Patnick, Julietta; Smith, Robert A.; Villain, Patricia; Patnick, J.; Atkin, W. S.; Altenhofen, L.; Ancelle-Park, R.; Benson, V. S.; Green, J.; Levin, T. R.; Moss, S. M.; Nadel, M.; Ransohoff, D.; Segnan, N.; Smith, R. A.; Villain, P.; Weller, D.; Koukari, A.; Young, G.; López-Kostner, F.; Antoljak, N.; Suchánek, S.; Zavoral, M.; Holten, I.; Malila, N.; Salines, E.; Brenner, G.; Herszényi, L.; Tulassay, Z.; Rennert, G.; Senore, C.; Zappa, M.; Zorzi, M.; Saito, H.; Leja, M.; Dekker, E.; Jansen, J.; Hol, L.; Kuipers, E.; Kaminski, M. F.; Regula, J.; Sfarti, C.; Trifan, A.; Tang, C.-L.; Hrcka, R.; Binefa, G.; Espinàs, J. A.; Peris, M.; Chen, T. H.; Steele, R.; Pou, G.; Bisges, D.; Dwyer, D.; Groves, C.; Courteau, S.; Kramer, R.; Siegenthaler, K.; Lane, D.; Herrera, C.; Rogers, J.; Rojewski, M.; Wolf, Holly; Sung, J. J.; Ling, K.; Bryant, H.; Rabeneck, L.; Dale, J.; Sware, L.; Yang, H.; Viguier, J.; Von Karsa, L.; Kupcinskas, L.; Deutekom, M.; Törnberg, S.; Austoker, J.; Beral, V.; Monk, C.; Valori, R.; Watson, J.; Kobrin, S.; Pignone, M.; Taplin, S.

    2012-01-01

    The International Colorectal Cancer Screening Network was established in 2003 to promote best practice in the delivery of organized colorectal cancer screening programs. To facilitate evaluation of such programs, we defined a set of universally applicable colorectal cancer screening measures and

  20. Oral cancer: A multicenter study

    Science.gov (United States)

    Rojanawatsirivej, Somsri; Thosaporn, Watcharaporn; Kintarak, Sompid; Subarnbhesaj, Ajiravudh; Darling, Mark; Kryshtalskyj, Eugene; Chiang, Chun-Pin; Shin, Hong-In; Choi, So-Young; Lee, Sang-shin; Shakib, Pouyan-Amini

    2018-01-01

    Background To determine the prevalence and clinicopathologic features of the oral cancer patients. Material and Methods Biopsy records of the participating institutions were reviewed for oral cancer cases diagnosed from 2005 to 2014. Demographic data and site of the lesions were collected. Sites of the lesion were subdivided into lip, tongue, floor of the mouth, gingiva, alveolar mucosa, palate, buccal/labial mucosa, maxilla and mandible. Oral cancer was subdivided into 7 categories: epithelial tumors, salivary gland tumors, hematologic tumors, bone tumors, mesenchymal tumors, odontogenic tumors, and others. Data were analyzed by descriptive statistics using SPSS software version 17.0. Results Of the 474,851 accessioned cases, 6,151 cases (1.30%) were diagnosed in the category of oral cancer. The mean age of the patients was 58.37±15.77 years. A total of 4,238 cases (68.90%) were diagnosed in males, whereas 1911 cases (31.07%) were diagnosed in females. The male-to-female ratio was 2.22:1. The sites of predilection for oral cancer were tongue, labial/buccal mucosa, gingiva, palate, and alveolar mucosa, respectively. The three most common oral cancer in the descending order of frequency were squamous cell carcinoma, non-Hodgkin lymphoma and mucoepidermoid carcinoma. Conclusions Although the prevalence of oral cancer is not high compared to other entities, oral cancer pose significant mortality and morbidity in the patients, especially when discovered late in the course of the disease. This study highlights some anatomical locations where oral cancers are frequently encountered. As a result, clinicians should pay attention to not only teeth, but oral mucosa especially in the high prevalence area as well since early detection of precancerous lesions or cancers in the early stage increase the chance of patient being cured and greatly reduce the mortality and morbidity. This study also shows some differences between pediatric and elderly oral cancer patients as well as

  1. Randomized Trial of a Social Networking Intervention for Cancer-Related Distress.

    Science.gov (United States)

    Owen, Jason E; O'Carroll Bantum, Erin; Pagano, Ian S; Stanton, Annette

    2017-10-01

    Web and mobile technologies appear to hold promise for delivering evidence-informed and evidence-based intervention to cancer survivors and others living with trauma and other psychological concerns. Health-space.net was developed as a comprehensive online social networking and coping skills training program for cancer survivors living with distress. The purpose of this study was to evaluate the effects of a 12-week social networking intervention on distress, depression, anxiety, vigor, and fatigue in cancer survivors reporting high levels of cancer-related distress. We recruited 347 participants from a local cancer registry and internet, and all were randomized to either a 12-week waiting list control group or to immediate access to the intervention. Intervention participants received secure access to the study website, which provided extensive social networking capabilities and coping skills training exercises facilitated by a professional facilitator. Across time, the prevalence of clinically significant depression symptoms declined from 67 to 34 % in both conditions. The health-space.net intervention had greater declines in fatigue than the waitlist control group, but the intervention did not improve outcomes for depression, trauma-related anxiety symptoms, or overall mood disturbance. For those with more severe levels of anxiety at baseline, greater engagement with the intervention was associated with higher levels of symptom reduction over time. The intervention resulted in small but significant effects on fatigue but not other primary or secondary outcomes. Results suggest that this social networking intervention may be most effective for those who have distress that is not associated with high levels of anxiety symptoms or very poor overall psychological functioning. The trial was registered with the ClinicalTrials.gov database ( ClinicalTrials.gov #NCT01976949).

  2. Rough set soft computing cancer classification and network: one stone, two birds.

    Science.gov (United States)

    Zhang, Yue

    2010-07-15

    Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.

  3. Wireless Sensor Network Safety Study

    OpenAIRE

    M.Shankar; Dr.M.Sridar; Dr.M.Rajani

    2012-01-01

    Few security mechanisms in wireless sensor networks (WSNs) have been implemented, and even fewer have been applied in real deployments. The limited resources of each sensor node makes security in WSNs hard, as the tradeoff between security and practicality must be carefully considered. These complex systems include in their design different types of information and communication technology systems, such as wireless (mesh) sensor networks, to carry out control processes in real time. This fact...

  4. The meaning and validation of social support networks for close family of persons with advanced cancer.

    Science.gov (United States)

    Sjolander, Catarina; Ahlstrom, Gerd

    2012-09-17

    To strengthen the mental well-being of close family of persons newly diagnosed as having cancer, it is necessary to acquire a greater understanding of their experiences of social support networks, so as to better assess what resources are available to them from such networks and what professional measures are required. The main aim of the present study was to explore the meaning of these networks for close family of adult persons in the early stage of treatment for advanced lung or gastrointestinal cancer. An additional aim was to validate the study's empirical findings by means of the Finfgeld-Connett conceptual model for social support. The intention was to investigate whether these findings were in accordance with previous research in nursing. Seventeen family members with a relative who 8-14 weeks earlier had been diagnosed as having lung or gastrointestinal cancer were interviewed. The data were subjected to qualitative latent content analysis and validated by means of identifying antecedents and critical attributes. The meaning or main attribute of the social support network was expressed by the theme Confirmation through togetherness, based on six subthemes covering emotional and, to a lesser extent, instrumental support. Confirmation through togetherness derived principally from information, understanding, encouragement, involvement and spiritual community. Three subthemes were identified as the antecedents to social support: Need of support, Desire for a deeper relationship with relatives, Network to turn to. Social support involves reciprocal exchange of verbal and non-verbal information provided mainly by lay persons. The study provides knowledge of the antecedents and attributes of social support networks, particularly from the perspective of close family of adult persons with advanced lung or gastrointestinal cancer. There is a need for measurement instruments that could encourage nurses and other health-care professionals to focus on family members

  5. The role of organizational affiliations and research networks in the diffusion of breast cancer treatment innovation.

    Science.gov (United States)

    Carpenter, William R; Reeder-Hayes, Katherine; Bainbridge, John; Meyer, Anne-Marie; Amos, Keith D; Weiner, Bryan J; Godley, Paul A

    2011-02-01

    The National Institutes of Health (NIH) sees provider-based research networks and other organizational linkages between academic researchers and community practitioners as promising vehicles for accelerating the translation of research into practice. This study examines whether organizational research affiliations and teaching affiliations are associated with accelerated diffusion of sentinel lymph node biopsy (SLNB), an innovation in the treatment of early-stage breast cancer. Surveillance Epidemiology and End Results-Medicare data were used to examine the diffusion of SLNB for treatment of early-stage breast cancer among women aged 65 years and older diagnosed between 2000 and 2002, shortly after Medicare approved and began reimbursing for the procedure. In this population, patients treated at an organization affiliated with a research network--the American College of Surgeons Oncology Group (ACOSOG) or other National Cancer Institute (NCI) cooperative groups--were more likely to receive the innovative treatment (SLNB) than patients treated at unaffiliated organizations (odds ratio: 2.70, 95% confidence interval: 1.77-4.12; odds ratio: 1.84, 95% confidence interval: 1.26-2.69, respectively). Neither hospital teaching status nor surgical volume was significantly associated with differences in SLNB use. Patients who receive cancer treatment at organizations affiliated with cancer research networks have an enhanced probability of receiving SLNB, an innovative procedure that offers the promise of improved patient outcomes. Study findings support the NIH Roadmap and programs such as the NCI's Community Clinical Oncology Program, as they seek to accelerate the translation of research into practice by simultaneously accelerating and broadening cancer research in the community.

  6. An integrative -omics approach to identify functional sub-networks in human colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Rod K Nibbe

    2010-01-01

    Full Text Available Emerging evidence indicates that gene products implicated in human cancers often cluster together in "hot spots" in protein-protein interaction (PPI networks. Additionally, small sub-networks within PPI networks that demonstrate synergistic differential expression with respect to tumorigenic phenotypes were recently shown to be more accurate classifiers of disease progression when compared to single targets identified by traditional approaches. However, many of these studies rely exclusively on mRNA expression data, a useful but limited measure of cellular activity. Proteomic profiling experiments provide information at the post-translational level, yet they generally screen only a limited fraction of the proteome. Here, we demonstrate that integration of these complementary data sources with a "proteomics-first" approach can enhance the discovery of candidate sub-networks in cancer that are well-suited for mechanistic validation in disease. We propose that small changes in the mRNA expression of multiple genes in the neighborhood of a protein-hub can be synergistically associated with significant changes in the activity of that protein and its network neighbors. Further, we hypothesize that proteomic targets with significant fold change between phenotype and control may be used to "seed" a search for small PPI sub-networks that are functionally associated with these targets. To test this hypothesis, we select proteomic targets having significant expression changes in human colorectal cancer (CRC from two independent 2-D gel-based screens. Then, we use random walk based models of network crosstalk and develop novel reference models to identify sub-networks that are statistically significant in terms of their functional association with these proteomic targets. Subsequently, using an information-theoretic measure, we evaluate synergistic changes in the activity of identified sub-networks based on genome-wide screens of mRNA expression in CRC

  7. Noise Analysis studies with neural networks

    International Nuclear Information System (INIS)

    Seker, S.; Ciftcioglu, O.

    1996-01-01

    Noise analysis studies with neural network are aimed. Stochastic signals at the input of the network are used to obtain an algorithmic multivariate stochastic signal modeling. To this end, lattice modeling of a stochastic signal is performed to obtain backward residual noise sources which are uncorrelated among themselves. There are applied together with an additional input to the network to obtain an algorithmic model which is used for signal detection for early failure in plant monitoring. The additional input provides the information to the network to minimize the difference between the signal and the network's one-step-ahead prediction. A stochastic algorithm is used for training where the errors reflecting the measurement error during the training are also modelled so that fast and consistent convergence of network's weights is obtained. The lattice structure coupled to neural network investigated with measured signals from an actual power plant. (authors)

  8. An empirical study of an agglomeration network

    International Nuclear Information System (INIS)

    Zhang, Yichao; Zhang, Zhaochun; Guan, Jihong

    2007-01-01

    Recently, researchers have reported many models mimicking real network evolution growth, among which some are based on network aggregation growth. However, until now, relatively few experiments have been reported. Accordingly, in this paper, photomicrographs of real materials (the agglomeration in the filtrate of slurry formed by a GaP-nanoparticle conglomerate dispersed in water) are analyzed within the framework of complex network theory. By data mapping from photomicrographs we generate undirected networks and as a definition of degree we adopt the number of pixel's nearest neighbors while adjacent pixels define a connection or an edge. We study the topological structure of these networks including degree distribution, clustering coefficient and average path length. In addition, we discuss the self-similarity and synchronizability of the networks. We find that the synchronizability of high-concentration agglomeration is better than that of low-concentration agglomeration; we also find that agglomeration networks possess good self-similar features

  9. Statistical Power in Longitudinal Network Studies

    NARCIS (Netherlands)

    Stadtfeld, Christoph; Snijders, Tom A. B.; Steglich, Christian; van Duijn, Marijtje

    2018-01-01

    Longitudinal social network studies may easily suffer from a lack of statistical power. This is the case in particular for studies that simultaneously investigate change of network ties and change of nodal attributes. Such selection and influence studies have become increasingly popular due to the

  10. The meaning and validation of social support networks for close family of persons with advanced cancer

    Directory of Open Access Journals (Sweden)

    Sjolander Catarina

    2012-09-01

    Full Text Available Abstract Background To strengthen the mental well-being of close family of persons newly diagnosed as having cancer, it is necessary to acquire a greater understanding of their experiences of social support networks, so as to better assess what resources are available to them from such networks and what professional measures are required. The main aim of the present study was to explore the meaning of these networks for close family of adult persons in the early stage of treatment for advanced lung or gastrointestinal cancer. An additional aim was to validate the study’s empirical findings by means of the Finfgeld-Connett conceptual model for social support. The intention was to investigate whether these findings were in accordance with previous research in nursing. Methods Seventeen family members with a relative who 8–14 weeks earlier had been diagnosed as having lung or gastrointestinal cancer were interviewed. The data were subjected to qualitative latent content analysis and validated by means of identifying antecedents and critical attributes. Results The meaning or main attribute of the social support network was expressed by the theme Confirmation through togetherness, based on six subthemes covering emotional and, to a lesser extent, instrumental support. Confirmation through togetherness derived principally from information, understanding, encouragement, involvement and spiritual community. Three subthemes were identified as the antecedents to social support: Need of support, Desire for a deeper relationship with relatives, Network to turn to. Social support involves reciprocal exchange of verbal and non-verbal information provided mainly by lay persons. Conclusions The study provides knowledge of the antecedents and attributes of social support networks, particularly from the perspective of close family of adult persons with advanced lung or gastrointestinal cancer. There is a need for measurement instruments that could

  11. Cancer mortality studied by Dounreay

    International Nuclear Information System (INIS)

    Wood, R.; Smith, N.D.

    1986-01-01

    A report is given of a cancer mortality study in Caithness, Sutherland, Orkney and Shetland between 1958 and 1982. For Caithness and Sutherland, the numbers of male deaths from all kinds of cancer was significantly less than the numbers expected from figures for Scotland as a whole; for females no difference was observed; the parish of Latheron showed an excess of leukaemia cases. For Orkney and Shetland, the total number of cancer deaths for both sexes was significantly less than for Scotland as a whole. In Shetland, there was an excess of lymphatic leukaemia in Northmaven based on four deaths observed. In Orkney, one parish showed an excess of lymphatic and haematopoietic cancers. (UK)

  12. Identification of Gene Biomarkers for Distinguishing Small-Cell Lung Cancer from Non-Small-Cell Lung Cancer Using a Network-Based Approach

    Directory of Open Access Journals (Sweden)

    Fei Long

    2015-01-01

    Full Text Available Lung cancer consists of two main subtypes: small-cell lung cancer (SCLC and non-small-cell lung cancer (NSCLC that are classified according to their physiological phenotypes. In this study, we have developed a network-based approach to identify molecular biomarkers that can distinguish SCLC from NSCLC. By identifying positive and negative coexpression gene pairs in normal lung tissues, SCLC, or NSCLC samples and using functional association information from the STRING network, we first construct a lung cancer-specific gene association network. From the network, we obtain gene modules in which genes are highly functionally associated with each other and are either positively or negatively coexpressed in the three conditions. Then, we identify gene modules that not only are differentially expressed between cancer and normal samples, but also show distinctive expression patterns between SCLC and NSCLC. Finally, we select genes inside those modules with discriminating coexpression patterns between the two lung cancer subtypes and predict them as candidate biomarkers that are of diagnostic use.

  13. Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data

    OpenAIRE

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor, Maureen

    2014-01-01

    We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer risks for a healthy individual are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial i...

  14. Social network characteristics and cervical cancer screening among Quechua women in Andean Peru

    Directory of Open Access Journals (Sweden)

    John S. Luque

    2016-02-01

    Full Text Available Abstract Background Peru has high cervical cancer incidence and mortality rates compared to other Andean countries. Therefore, partnerships between governmental and international organizations have targeted rural areas of Peru to receive cervical cancer screening via outreach campaigns. Previous studies have found a relationship between a person’s social networks and cancer screening behaviors. Screening outreach campaigns conducted by the nonprofit organization CerviCusco created an opportunity for a social network study to examine cervical cancer screening history and social network characteristics in a rural indigenous community that participated in these campaigns in 2012 and 2013. The aim of this study was to explore social network characteristics in this community related to receipt of cervical cancer screening following the campaigns. Methods An egocentric social network questionnaire was used to collect cross-sectional network data on community participants. Each survey participant (ego was asked to name six other women they knew (alters and identify the nature of their relationship or tie (family, friend, neighbor, other, residential closeness (within 5 km, length of time known, frequency of communication, topics of conversation, and whether they lent money to the person, provided childcare or helped with transportation. In addition, each participant was asked to report the nature of the relationship between all alters identified (e.g., friend, family, or neighbor. Bivariate and multivariate analyses were used to explore the relationship between Pap test receipt at the CerviCusco outreach screening campaigns and social network characteristics. Results Bivariate results found significant differences in percentage of alter composition for neighbors and family, and for mean number of years known, mean density, and mean degree centrality between women who had received a Pap test (n = 19 compared to those who had not (n = 50 (p

  15. Predicting Genes Involved in Human Cancer Using Network Contextual Information

    Directory of Open Access Journals (Sweden)

    Rahmani Hossein

    2012-03-01

    Full Text Available Protein-Protein Interaction (PPI networks have been widely used for the task of predicting proteins involved in cancer. Previous research has shown that functional information about the protein for which a prediction is made, proximity to specific other proteins in the PPI network, as well as local network structure are informative features in this respect. In this work, we introduce two new types of input features, reflecting additional information: (1 Functional Context: the functions of proteins interacting with the target protein (rather than the protein itself; and (2 Structural Context: the relative position of the target protein with respect to specific other proteins selected according to a novel ANOVA (analysis of variance based measure. We also introduce a selection strategy to pinpoint the most informative features. Results show that the proposed feature types and feature selection strategy yield informative features. A standard machine learning method (Naive Bayes that uses the features proposed here outperforms the current state-of-the-art methods by more than 5% with respect to F-measure. In addition, manual inspection confirms the biological relevance of the top-ranked features.

  16. CCNA Cisco Certified Network Associate Study Guide

    CERN Document Server

    Lammle, Todd

    2011-01-01

    Learn from the Best - Cisco Networking Authority Todd LammleWritten by Cisco networking authority Todd Lammle, this comprehensive guide has been completely updated to reflect the latest CCNA 640-802 exam. Todd's straightforward style provides lively examples, hands on and written labs, easy-to-understand analogies, and real-world scenarios that will not only help you prepare for the exam, but also give you a solid foundation as a Cisco networking professional.This Study Guide teaches you how toDescribe how a network worksConfigure, verify and troubleshoot a switch with VLANs and interswitch co

  17. Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer

    Science.gov (United States)

    CHEN, CHEN; SHEN, HONG; ZHANG, LI-GUO; LIU, JIAN; CAO, XIAO-GE; YAO, AN-LIANG; KANG, SHAO-SAN; GAO, WEI-XING; HAN, HUI; CAO, FENG-HONG; LI, ZHI-GUO

    2016-01-01

    Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa. PMID:27121963

  18. Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells.

    Directory of Open Access Journals (Sweden)

    Aurélien Naldi

    2017-03-01

    Full Text Available The ability to build in-depth cell signaling networks from vast experimental data is a key objective of computational biology. The spleen tyrosine kinase (Syk protein, a well-characterized key player in immune cell signaling, was surprisingly first shown by our group to exhibit an onco-suppressive function in mammary epithelial cells and corroborated by many other studies, but the molecular mechanisms of this function remain largely unsolved. Based on existing proteomic data, we report here the generation of an interaction-based network of signaling pathways controlled by Syk in breast cancer cells. Pathway enrichment of the Syk targets previously identified by quantitative phospho-proteomics indicated that Syk is engaged in cell adhesion, motility, growth and death. Using the components and interactions of these pathways, we bootstrapped the reconstruction of a comprehensive network covering Syk signaling in breast cancer cells. To generate in silico hypotheses on Syk signaling propagation, we developed a method allowing to rank paths between Syk and its targets. We first annotated the network according to experimental datasets. We then combined shortest path computation with random walk processes to estimate the importance of individual interactions and selected biologically relevant pathways in the network. Molecular and cell biology experiments allowed to distinguish candidate mechanisms that underlie the impact of Syk on the regulation of cortactin and ezrin, both involved in actin-mediated cell adhesion and motility. The Syk network was further completed with the results of our biological validation experiments. The resulting Syk signaling sub-networks can be explored via an online visualization platform.

  19. Disparities in Adherence to National Comprehensive Cancer Network Treatment Guidelines and Survival for Stage IB-IIA Cervical Cancer in California.

    Science.gov (United States)

    Pfaendler, Krista S; Chang, Jenny; Ziogas, Argyrios; Bristow, Robert E; Penner, Kristine R

    2018-05-01

    To evaluate the association of sociodemographic and hospital characteristics with adherence to National Comprehensive Cancer Network treatment guidelines for stage IB-IIA cervical cancer and to analyze the relationship between adherent care and survival. This is a retrospective population-based cohort study of patients with stage IB-IIA invasive cervical cancer reported to the California Cancer Registry from January 1, 1995, through December 31, 2009. Adherence to National Comprehensive Cancer Network guideline care was defined by year- and stage-appropriate surgical procedures, radiation, and chemotherapy. Multivariate logistic regression, Kaplan-Meier estimate, and Cox proportional hazard models were used to examine associations between patient, tumor, and treatment characteristics and National Comprehensive Cancer Network guideline adherence and cervical cancer-specific 5-year survival. A total of 6,063 patients were identified. Forty-seven percent received National Comprehensive Cancer Network guideline-adherent care, and 18.8% were treated in high-volume centers (20 or more patients/year). On multivariate analysis, lowest socioeconomic status (adjusted odds ratio [OR] 0.69, 95% CI 0.57-0.84), low-middle socioeconomic status (adjusted OR 0.76, 95% CI 0.64-0.92), and Charlson-Deyo comorbidity score 1 or higher (adjusted OR 0.78, 95% CI 0.69-0.89) were patient characteristics associated with receipt of nonguideline care. Receiving adherent care was less common in low-volume centers (45.9%) than in high-volume centers (50.9%) (effect size 0.90, 95% CI 0.84-0.96). Death from cervical cancer was more common in the nonadherent group (13.3%) than in the adherent group (8.6%) (effect size 1.55, 95% CI 1.34-1.80). Black race (adjusted hazard ratio 1.56, 95% CI 1.08-2.27), Medicaid payer status (adjusted hazard ratio 1.47, 95% CI 1.15-1.87), and Charlson-Deyo comorbidity score 1 or higher (adjusted hazard ratio 2.07, 95% CI 1.68-2.56) were all associated with increased

  20. The Asian American Network for Cancer Awareness, Research, and Training’s Role in Cancer Awareness, Research, and Training

    Science.gov (United States)

    Chen, Moon S.

    2006-01-01

    Purpose The purpose of this paper is to describe the content for the Asian American Network for Cancer Awareness Research and Training (AANCART) with respect to Asian American demographic characteristics and their cancer burden, highlights of accomplishments in various AANCART regions, aspirations for AANCART, and an interim assessment of AANCART’s activities to date. Methods The author compiled literature and other data references to describe the context for Asian American demographic characteristics and their cancer burden. As the AANCART Principal Investigator, he collected data from internal AANCART reports to depict highlights of accomplishments in various AANCART regions and offer evidence that AANCART’s first two specific aims have been attained. Principal Findings With respect to our first specific aim, we have built an infrastructure for cancer awareness, research and training operationally at a Network-wide basis through program directors for biostatistics, community, clinical, and research and in our four original AANCART regions: New York, Seattle, San Francisco, and Los Angeles. With respect to our second specific aim, we have established partnerships as exemplified by working collaboratively with New York’s Charles B. Wang Community Health Center in securing external funding with them for a tobacco control initiative and nationally with the American Cancer Society. With respect to our third specific aim, we have been fortunate to assist at least eight junior investigators in receiving NCI-funded pilot studies. The most notable change was the transfer of AANCART’s national headquarters from Columbus, Ohio to Sacramento, California along with potentially an increased diversification of Asian American ethnic groups as well as an expansion to Hawaii and Houston. Conclusion As of the end of year 2 of AANCART, AANCART’s two specific aims have been achieved. We are focusing on our third specific aim. PMID:15352772

  1. Breast Cancer Diagnosis using Artificial Neural Networks with Extreme Learning Techniques

    OpenAIRE

    Chandra Prasetyo Utomo; Aan Kardiana; Rika Yuliwulandari

    2014-01-01

    Breast cancer is the second cause of dead among women. Early detection followed by appropriate cancer treatment can reduce the deadly risk. Medical professionals can make mistakes while identifying a disease. The help of technology such as data mining and machine learning can substantially improve the diagnosis accuracy. Artificial Neural Networks (ANN) has been widely used in intelligent breast cancer diagnosis. However, the standard Gradient-Based Back Propagation Artificial Neural Networks...

  2. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

    Directory of Open Access Journals (Sweden)

    Yeh Cheng-Yu

    2009-12-01

    Full Text Available Abstract Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2 regulated by RUNX1 and STAT3 is correlated to the pathological stage

  3. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

    Science.gov (United States)

    Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

    2009-12-21

    Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

  4. Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer.

    Directory of Open Access Journals (Sweden)

    Matthew Ruffalo

    2015-12-01

    Full Text Available Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at different levels of cellular activity. Namely, we hypothesize that genes that play a role in cancer development and progression may be implicated by neither frequent mutation nor differential expression, and that network-based integration of mutation and differential expression data can reveal these "silent players". For this purpose, we utilize network-propagation algorithms to simulate the information flow in the cell at a sample-specific resolution. We then use the propagated mutation and expression signals to identify genes that are not necessarily mutated or differentially expressed genes, but have an essential role in tumor development and patient outcome. We test the proposed method on breast cancer and glioblastoma multiforme data obtained from TCGA. Our results show that the proposed method can identify important proteins that are not readily revealed by molecular data, providing insights beyond what can be gleaned by analyzing different types of molecular data in isolation.

  5. Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

    Science.gov (United States)

    Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

    2015-06-01

    To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. RNA binding protein RNPC1 inhibits breast cancer cells metastasis via activating STARD13-correlated ceRNA network.

    Science.gov (United States)

    Zhang, Zhiting; Guo, Qianqian; Zhang, Shufang; Xiang, Chenxi; Guo, Xinwei; Zhang, Feng; Gao, Lanlan; Ni, Haiwei; Xi, Tao; Zheng, Lufeng

    2018-05-07

    RNA binding proteins (RBPs) are pivotal post-transcriptional regulators. RNPC1, an RBP, acts as a tumor suppressor through binding and regulating the expression of target genes in cancer cells. This study disclosed that RNPC1 expression was positively correlated with breast cancer patients' relapse free and overall survival, and RNPC1suppressed breast cancer cells metastasis. Mechanistically, RNPC1 promoting a competing endogenous network (ceRNA) crosstalk between STARD13, CDH5, HOXD10, and HOXD1 (STARD13-correlated ceRNA network) that we previously confirmed in breast cancer cells through stabilizing the transcripts and thus facilitating the expression of these four genes in breast cancer cells. Furthermore, RNPC1 overexpression restrained the promotion of STARD13, CDH5, HOXD10, and HOXD1 knockdown on cell metastasis. Notably, RNPC1 expression was positively correlated with CDH5, HOXD1 and HOXD10 expression in breast cancer tissues, and attenuated adriamycin resistance. Taken together, these results identified that RNPC1 could inhibit breast cancer cells metastasis via promoting STARD13-correlated ceRNA network.

  7. Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models

    Science.gov (United States)

    Nilsaz-Dezfouli, Hamid; Abu-Bakar, Mohd Rizam; Arasan, Jayanthi; Adam, Mohd Bakri; Pourhoseingholi, Mohamad Amin

    2017-01-01

    In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been a long-standing topic of interest. Current statistical methods for survival analysis offer the possibility of modelling cancer survivability but require unrealistic assumptions about the survival time distribution or proportionality of hazard. Therefore, attention must be paid in developing nonlinear models with less restrictive assumptions. Artificial neural network (ANN) models are primarily useful in prediction when nonlinear approaches are required to sift through the plethora of available information. The applications of ANN models for prognostic and diagnostic classification in medicine have attracted a lot of interest. The applications of ANN models in modelling the survival of patients with gastric cancer have been discussed in some studies without completely considering the censored data. This study proposes an ANN model for predicting gastric cancer survivability, considering the censored data. Five separate single time-point ANN models were developed to predict the outcome of patients after 1, 2, 3, 4, and 5 years. The performance of ANN model in predicting the probabilities of death is consistently high for all time points according to the accuracy and the area under the receiver operating characteristic curve. PMID:28469384

  8. Breast cancer publication network: profile of co-authorship and co-organization.

    Science.gov (United States)

    Biglu, Mohammad-Hossein; Abotalebi, Parvaneh; Ghavami, Mostafa

    2016-01-01

    Introduction: Breast cancer is one of the highest reasons of deaths for people in the world. The objective of current study is to analyze and visualize the trend of global scientific activities in the field of breast cancer during a period of 10 years through 2006-2015. Methods: The current study was performed by utilizing the scientometrics analysis and mapping the co-authorship and co-organization networks. The Web of Science Core Collection (WoS-CC)database was used to extract all papers indexed as a topic of breast cancer through 2006 to 2015. Research productivity was measured through analysis several parameters, including: the number and time course of publications, the journal and language of publications, the frequency and type of publications, as well as top 20 active sub-categories together with country contribution. The extracted data were transferred into the Excel charts and plotted as diagrams. The Science of Science (Sci2) and CiteSpace softwares were used as tools for mapping the co-authorship and co-organization networks of the published papers. Results: Analysis of data indicated that the number of publications in the field of breast cancer has linearly increased and correlated with the time-course of the study. The number of publication indexed in WoS-CC in 2015 was two times greater than that of 2006, which reached from 15 229 documents in 2006 to 30 667 documents in 2015. English Language accounted for 98% of total publications as the most dominant language. The vast majority of publications' type was in the form of original journal articles (64.7%). Based on Bradford scatterings law, the journal of "Cancer Research" was the most productive journal among the core journals, while the USA, China, and England were the most prolific countries in the field. The co-organization network indicated the dominant role of Harvard University in the field. Conclusion: The integrity of network indicated that scientists in the field of breast cancer

  9. Comparative indicators for cancer network management in England: Availability, characteristics and presentation

    Directory of Open Access Journals (Sweden)

    Coleman Michel P

    2008-02-01

    Full Text Available Abstract Background In 2000, the national cancer plan for England created 34 cancer networks, new organisational structures to coordinate services across populations varying between a half and three million people. We investigated the availability of data sets reflecting measures of structure, process and outcome that could be used to support network management. Methods We investigated the properties of national data sets relating to four common cancers – breast, colorectal, lung and prostate. We reviewed the availability and completeness of these data sets, identified leading items within each set and put them into tables of the 34 cancer networks. We also investigated methods of presentation. Results The Acute Hospitals Portfolio and the Cancer Standards Peer Review recorded structural characteristics at hospital and cancer service level. Process measures included Hospital Episode Statistics, recording admissions, and Hospital Waiting-List data. Patient outcome measures included the National Survey of Patient Satisfaction for cancer, and cancer survival, drawn from cancer registration. Data were drawn together to provide an exemplar indicator set a single network, and methods of graphical presentation were considered. Conclusion While not as yet used together in practice, comparative indicators are available within the National Health Service in England for use in performance assessment by cancer networks.

  10. Cancer cervix?: a retrospective study

    International Nuclear Information System (INIS)

    Hirapara, Pushpendra H.; Patidar, Arvindkumar; Walke, Rahul; Jakhar, Shankar Lal; Sharma, Neeti; Kumar, H.S.; Jain, Sandeep; Kalwar, Ashok; Bardia, M.R.

    2012-01-01

    Anemia is very commonly seen in most of the malignancies including cancer cervix. Anemia has long been reported to adversely affect the efficacy of radiation treatment in cervical cancer. At our center, carcinoma cervix accounts for approximately 8-10% of all malignancies. The objective of this study is to see the impact of anemia in the treatment of cancer cervix. In the present study, we collected data of treatment results of FIGO stage II and III cancer cervix patients retrospectively treated in years of 2009-10. We have tried to assess the outcome of results in patients whom haemoglobin (Hb) level < 10 gm/dl and e''10 gm/dl. Out of 200 patients of disease with baseline Hb less than 10 gm/dl, 80(40%) patients had residual disease after 4 weeks of completion of treatment. Out of 168 patients with baseline Hb more than 10 gm/dl, 42(25%) had residual disease (p-0.0012 i.e highly significant). Our study shows that there is a good disease control at local site in patients with higher pretreatment Hb level. Effect of pretreatment Hb on treatment outcome in terms of overall survival, disease free survival, and local relapse free survival along with effect on corrective measures should be studied in detail. (author)

  11. Comprehensive characterization of lncRNA-mRNA related ceRNA network across 12 major cancers

    Science.gov (United States)

    Feng, Li; Li, Feng; Sun, Zeguo; Wu, Tan; Shi, Xinrui; Li, Jing; Li, Xia

    2016-01-01

    Recent studies indicate that long noncoding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to indirectly regulate mRNAs through shared microRNAs, which represents a novel layer of RNA crosstalk and plays critical roles in the development of tumor. However, the global regulation landscape and characterization of these lncRNA related ceRNA crosstalk in cancers is still largely unknown. Here, we systematically characterized the lncRNA related ceRNA interactions across 12 major cancers and the normal physiological states by integrating multidimensional molecule profiles of more than 5000 samples. Our study suggest the large difference of ceRNA regulation between normal and tumor states and the higher similarity across similar tissue origin of tumors. The ceRNA related molecules have more conserved features in tumor networks and they play critical roles in both the normal and tumorigenesis processes. Besides, lncRNAs in the pan-cancer ceRNA network may be potential biomarkers of tumor. By exploring hub lncRNAs, we found that these conserved key lncRNAs dominate variable tumor hallmark processes across pan-cancers. Network dynamic analysis highlights the critical roles of ceRNA regulation in tumorigenesis. By analyzing conserved ceRNA interactions, we found that miRNA mediate ceRNA regulation showed different patterns across pan-cancer; while analyzing the cancer specific ceRNA interactions reveal that lncRNAs synergistically regulated tumor driver genes of cancer hallmarks. Finally, we found that ceRNA modules have the potential to predict patient survival. Overall, our study systematically dissected the lncRNA related ceRNA networks in pan-cancer that shed new light on understanding the molecular mechanism of tumorigenesis. PMID:27580177

  12. Transcription Factor Networks derived from Breast Cancer Stem Cells control the immune response in the Basal subtype

    DEFF Research Database (Denmark)

    da Silveira, W A; Palma, P V B; Sicchieri, R D

    2017-01-01

    Breast cancer is the most common cancer in women worldwide and metastatic dissemination is the principal factor related to death by this disease. Breast cancer stem cells (bCSC) are thought to be responsible for metastasis and chemoresistance. In this study, based on whole transcriptome analysis...... of these networks in patient tumours is predictive of engraftment success. Our findings point out a potential molecular mechanism underlying the balance between immune surveillance and EMT activation in breast cancer. This molecular mechanism may be useful to the development of new target therapies....... and IKZF3 transcription factors which correspond to immune response modulators. Immune response network expression is correlated with pathological response to chemotherapy, and in the Basal subtype is related to better recurrence-free survival. In patient-derived xenografts, the expression...

  13. Network analysis of microRNAs and their regulation in human ovarian cancer

    KAUST Repository

    Schmeier, Sebastian

    2011-11-03

    Background: MicroRNAs (miRNAs) are small non-coding RNA molecules that repress the translation of messenger RNAs (mRNAs) or degrade mRNAs. These functions of miRNAs allow them to control key cellular processes such as development, differentiation and apoptosis, and they have also been implicated in several cancers such as leukaemia, lung, pancreatic and ovarian cancer (OC). Unfortunately, the specific machinery of miRNA regulation, involving transcription factors (TFs) and transcription co-factors (TcoFs), is not well understood. In the present study we focus on computationally deciphering the underlying network of miRNAs, their targets, and their control mechanisms that have an influence on OC development.Results: We analysed experimentally verified data from multiple sources that describe miRNA influence on diseases, miRNA targeting of mRNAs, and on protein-protein interactions, and combined this data with ab initio transcription factor binding site predictions within miRNA promoter regions. From these analyses, we derived a network that describes the influence of miRNAs and their regulation in human OC. We developed a methodology to analyse the network in order to find the nodes that have the largest potential of influencing the network\\'s behaviour (network hubs). We further show the potentially most influential miRNAs, TFs and TcoFs, showing subnetworks illustrating the involved mechanisms as well as regulatory miRNA network motifs in OC. We find an enrichment of miRNA targeted OC genes in the highly relevant pathways cell cycle regulation and apoptosis.Conclusions: We combined several sources of interaction and association data to analyse and place miRNAs within regulatory pathways that influence human OC. These results represent the first comprehensive miRNA regulatory network analysis for human OC. This suggests that miRNAs and their regulation may play a major role in OC and that further directed research in this area is of utmost importance to enhance

  14. [Clinical research activity of the French cancer cooperative network: Overview and perspectives].

    Science.gov (United States)

    Dubois, Claire; Morin, Franck; Moro-Sibilot, Denis; Langlais, Alexandra; Seitz, Jean-François; Girault, Cécile; Salles, Gilles; Haioun, Corinne; Deschaseaux, Pascal; Casassus, Philippe; Mathiot, Claire; Pujade-Lauraine, Éric; Votan, Bénédicte; Louvet, Christophe; Delpeut, Christine; Bardet, Étienne; Vintonenko, Nadejda; Hoang Xuan, Khê; Vo, Maryline; Michon, Jean; Milleron, Bernard

    The French Cancer Plan 2014-2019 stresses the importance of strengthening collaboration between all stakeholders involved in the fight against cancer, including cancer cooperative groups and intergroups. This survey aimed to describe the basics characteristics and clinical research activity among the Cancer Cooperative Groups (Groupes coopérateurs en oncologie). The second objective was to identify facilitators and barriers to their research activity. A questionnaire was sent to all the clinicians involved in 2014 as investigators in a clinical trial sponsored by one of the ten members of the Cancer Cooperative Groups network. The questions were related to their profile, research activity and the infrastructure existing within their healthcare center to support clinical research and related compliance activities. In total, 366 investigators responded to our survey. The academic clinical trials sponsored by the Cancer Cooperative Groups represented an important part of the research activity of the investigators in France in 2014. These academic groups contributed to the opening of many research sites throughout all regions in France. Factors associated with a higher participation of investigators (more than 10 patients enrolled in a trial over a year) include the existing support of healthcare professionals (more than 2 clinical research associate (CRA) OR=11.16 [3.82-32.6] compared to none) and the practice of their research activity in a University Hospital Center (CHU) rather than a Hospital Center (CH) (OR=2.15 [1.20-3.83]). This study highlighted factors that can strengthen investigator clinical research activities and subsequently improve patient access to evidence-based new cancer therapies in France. Copyright © 2017 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

  15. Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

    NARCIS (Netherlands)

    Schaub, Franz X.; Dhankani, Varsha; Berger, Ashton C.; Trivedi, Mihir; Richardson, Anne B.; Shaw, Reid; Zhao, Wei; Zhang, Xiaoyang; Ventura, Andrea; Liu, Yuexin; Ayer, Donald E.; Hurlin, Peter J.; Cherniack, Andrew D.; Eisenman, Robert N.; Bernard, Brady; Grandori, Carla; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Angulo Gonzalez, Ana Maria; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Mora Pinero, Edna M.; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz

    2018-01-01

    Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic

  16. Convolutional neural networks for prostate cancer recurrence prediction

    Science.gov (United States)

    Kumar, Neeraj; Verma, Ruchika; Arora, Ashish; Kumar, Abhay; Gupta, Sanchit; Sethi, Amit; Gann, Peter H.

    2017-03-01

    Accurate prediction of the treatment outcome is important for cancer treatment planning. We present an approach to predict prostate cancer (PCa) recurrence after radical prostatectomy using tissue images. We used a cohort whose case vs. control (recurrent vs. non-recurrent) status had been determined using post-treatment follow up. Further, to aid the development of novel biomarkers of PCa recurrence, cases and controls were paired based on matching of other predictive clinical variables such as Gleason grade, stage, age, and race. For this cohort, tissue resection microarray with up to four cores per patient was available. The proposed approach is based on deep learning, and its novelty lies in the use of two separate convolutional neural networks (CNNs) - one to detect individual nuclei even in the crowded areas, and the other to classify them. To detect nuclear centers in an image, the first CNN predicts distance transform of the underlying (but unknown) multi-nuclear map from the input HE image. The second CNN classifies the patches centered at nuclear centers into those belonging to cases or controls. Voting across patches extracted from image(s) of a patient yields the probability of recurrence for the patient. The proposed approach gave 0.81 AUC for a sample of 30 recurrent cases and 30 non-recurrent controls, after being trained on an independent set of 80 case-controls pairs. If validated further, such an approach might help in choosing between a combination of treatment options such as active surveillance, radical prostatectomy, radiation, and hormone therapy. It can also generalize to the prediction of treatment outcomes in other cancers.

  17. Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

    Science.gov (United States)

    Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

    2015-10-01

    Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.

  18. The UK-SEA-ME Psychosocial-Cultural Cancer Research Network: setting the stage for applied qualitative research on cancer health behaviour in southeast Asia and the Middle East.

    Science.gov (United States)

    Lim, Jennifer N W

    2011-01-01

    Psychosocial and cultural factors influencing cancer health behaviour have not been systematically investigated outside the western culture, and qualitative research is the best approach for this type of social research. The research methods employed to study health problems in Asia predominantly are quantitative techniques. The set up of the first psychosocial cancer research network in Asia marks the beginning of a collaboration to promote and spearhead applied qualitative healthcare research in cancer in the UK, Southeast Asia and the Middle East. This paper sets out the rationale, objectives and mission for the UK-SEA-ME Psychosocial-Cultural Cancer Research Network. The UK-SEA-ME network is made up of collaborators from the University of Leeds (UK), the University of Malaya (Malaysia), the National University of Singapore (Singapore) and the University of United Arab Emirates (UAE). The network promotes applied qualitative research to investigate the psychosocial and cultural factors influencing delayed and late presentation and diagnosis for cancer (breast cancer) in partner countries, as well as advocating the use of the mixed-methods research approach. The network also offers knowledge transfer for capacity building within network universities. The mission of the network is to improve public awareness about the importance of early management and prevention of cancer through research in Asia.

  19. Understanding the social and community support networks of American Indian women cancer survivors.

    Science.gov (United States)

    Burnette, Catherine E; Liddell, Jessica; Roh, Soonhee; Lee, Yeon-Shim; Lee, Hee Yun

    2018-04-02

    Cancer is the leading cause of death among American Indian and Alaska Native (AI/AN) women, and although cancer disparities among AI women are alarming, there is little research focused on the topic of social support and cancer treatment and outcomes. A community advisory board was used to develop and administer the project, and a qualitative descriptive study methodology was used. This research was conducted in partnership with two community-based hospitals in the Northern Plains. The sample included 43 AI female cancer survivors who were interviewed with a semi-structured interview guide. The data were analyzed using content analysis. Emergent themes revealed that AI cancer survivors' non-familial support systems included friends (n = 12), support groups (n = 6), churches (n = 10), co-workers (n = 5), communities (n = 4), support from health practitioners (n = 3) and additional forms of support. Results indicate that survivors' networks are diverse, and support broad prevention programs that reach out to churches, community groups, and online forums. These sources of supports can be enhanced through sustainable community-based infrastructures.

  20. A sparse regulatory network of copy-number driven gene expression reveals putative breast cancer oncogenes.

    Science.gov (United States)

    Yuan, Yinyin; Curtis, Christina; Caldas, Carlos; Markowetz, Florian

    2012-01-01

    Copy number aberrations are recognized to be important in cancer as they may localize to regions harboring oncogenes or tumor suppressors. Such genomic alterations mediate phenotypic changes through their impact on expression. Both cis- and transacting alterations are important since they may help to elucidate putative cancer genes. However, amidst numerous passenger genes, trans-effects are less well studied due to the computational difficulty in detecting weak and sparse signals in the data, and yet may influence multiple genes on a global scale. We propose an integrative approach to learn a sparse interaction network of DNA copy-number regions with their downstream transcriptional targets in breast cancer. With respect to goodness of fit on both simulated and real data, the performance of sparse network inference is no worse than other state-of-the-art models but with the advantage of simultaneous feature selection and efficiency. The DNA-RNA interaction network helps to distinguish copy-number driven expression alterations from those that are copy-number independent. Further, our approach yields a quantitative copy-number dependency score, which distinguishes cis- versus trans-effects. When applied to a breast cancer data set, numerous expression profiles were impacted by cis-acting copy-number alterations, including several known oncogenes such as GRB7, ERBB2, and LSM1. Several trans-acting alterations were also identified, impacting genes such as ADAM2 and BAGE, which warrant further investigation. An R package named lol is available from www.markowetzlab.org/software/lol.html.

  1. Integrative modelling of the influence of MAPK network on cancer cell fate decision.

    Directory of Open Access Journals (Sweden)

    Luca Grieco

    2013-10-01

    Full Text Available The Mitogen-Activated Protein Kinase (MAPK network consists of tightly interconnected signalling pathways involved in diverse cellular processes, such as cell cycle, survival, apoptosis and differentiation. Although several studies reported the involvement of these signalling cascades in cancer deregulations, the precise mechanisms underlying their influence on the balance between cell proliferation and cell death (cell fate decision in pathological circumstances remain elusive. Based on an extensive analysis of published data, we have built a comprehensive and generic reaction map for the MAPK signalling network, using CellDesigner software. In order to explore the MAPK responses to different stimuli and better understand their contributions to cell fate decision, we have considered the most crucial components and interactions and encoded them into a logical model, using the software GINsim. Our logical model analysis particularly focuses on urinary bladder cancer, where MAPK network deregulations have often been associated with specific phenotypes. To cope with the combinatorial explosion of the number of states, we have applied novel algorithms for model reduction and for the compression of state transition graphs, both implemented into the software GINsim. The results of systematic simulations for different signal combinations and network perturbations were found globally coherent with published data. In silico experiments further enabled us to delineate the roles of specific components, cross-talks and regulatory feedbacks in cell fate decision. Finally, tentative proliferative or anti-proliferative mechanisms can be connected with established bladder cancer deregulations, namely Epidermal Growth Factor Receptor (EGFR over-expression and Fibroblast Growth Factor Receptor 3 (FGFR3 activating mutations.

  2. Changes in Brain Structural Networks and Cognitive Functions in Testicular Cancer Patients Receiving Cisplatin-Based Chemotherapy

    NARCIS (Netherlands)

    Amidi, Ali; Hosseini, S. M.Hadi; Leemans, Alexander; Kesler, Shelli R.; Agerbæk, Mads; Wu, Lisa M.; Zachariae, Robert

    2017-01-01

    Background: Cisplatin-based chemotherapy may have neurotoxic effects within the central nervous system. The aims of this study were 1) to longitudinally investigate the impact of cisplatin-based chemotherapy on whole-brain networks in testicular cancer patients undergoing treatment and 2) to explore

  3. Social network analysis of study environment

    Directory of Open Access Journals (Sweden)

    Blaženka Divjak

    2010-06-01

    Full Text Available Student working environment influences student learning and achievement level. In this respect social aspects of students’ formal and non-formal learning play special role in learning environment. The main research problem of this paper is to find out if students' academic performance influences their position in different students' social networks. Further, there is a need to identify other predictors of this position. In the process of problem solving we use the Social Network Analysis (SNA that is based on the data we collected from the students at the Faculty of Organization and Informatics, University of Zagreb. There are two data samples: in the basic sample N=27 and in the extended sample N=52. We collected data on social-demographic position, academic performance, learning and motivation styles, student status (full-time/part-time, attitudes towards individual and teamwork as well as informal cooperation. Afterwards five different networks (exchange of learning materials, teamwork, informal communication, basic and aggregated social network were constructed. These networks were analyzed with different metrics and the most important were betweenness, closeness and degree centrality. The main result is, firstly, that the position in a social network cannot be forecast only by academic success and, secondly, that part-time students tend to form separate groups that are poorly connected with full-time students. In general, position of a student in social networks in study environment can influence student learning as well as her/his future employability and therefore it is worthwhile to be investigated.

  4. Distribution Network Design--literature study based

    OpenAIRE

    LI, ANG

    2012-01-01

    The focus of this research is companies' outbound distribution network design in supply chain management. Within the present competitive market, it is a fundamental importance for companies to achieve high level business performance with an effective supply chain. Outbound distribution network design as an important part in supply chain management, to a large extent decides whether companies can fulfill customers' requirement or not. Therefore, such a study is important for manufacturers and ...

  5. Network analysis of microRNAs and their regulation in human ovarian cancer

    KAUST Repository

    Schmeier, Sebastian; Schaefer, Ulf; Essack, Magbubah; Bajic, Vladimir B.

    2011-01-01

    Background: MicroRNAs (miRNAs) are small non-coding RNA molecules that repress the translation of messenger RNAs (mRNAs) or degrade mRNAs. These functions of miRNAs allow them to control key cellular processes such as development, differentiation and apoptosis, and they have also been implicated in several cancers such as leukaemia, lung, pancreatic and ovarian cancer (OC). Unfortunately, the specific machinery of miRNA regulation, involving transcription factors (TFs) and transcription co-factors (TcoFs), is not well understood. In the present study we focus on computationally deciphering the underlying network of miRNAs, their targets, and their control mechanisms that have an influence on OC development.Results: We analysed experimentally verified data from multiple sources that describe miRNA influence on diseases, miRNA targeting of mRNAs, and on protein-protein interactions, and combined this data with ab initio transcription factor binding site predictions within miRNA promoter regions. From these analyses, we derived a network that describes the influence of miRNAs and their regulation in human OC. We developed a methodology to analyse the network in order to find the nodes that have the largest potential of influencing the network's behaviour (network hubs). We further show the potentially most influential miRNAs, TFs and TcoFs, showing subnetworks illustrating the involved mechanisms as well as regulatory miRNA network motifs in OC. We find an enrichment of miRNA targeted OC genes in the highly relevant pathways cell cycle regulation and apoptosis.Conclusions: We combined several sources of interaction and association data to analyse and place miRNAs within regulatory pathways that influence human OC. These results represent the first comprehensive miRNA regulatory network analysis for human OC. This suggests that miRNAs and their regulation may play a major role in OC and that further directed research in this area is of utmost importance to enhance our

  6. German second-opinion network for testicular cancer: sealing the leaky pipe between evidence and clinical practice.

    Science.gov (United States)

    Zengerling, Friedemann; Hartmann, Michael; Heidenreich, Axel; Krege, Susanne; Albers, Peter; Karl, Alexander; Weissbach, Lothar; Wagner, Walter; Bedke, Jens; Retz, Margitta; Schmelz, Hans U; Kliesch, Sabine; Kuczyk, Markus; Winter, Eva; Pottek, Tobias; Dieckmann, Klaus-Peter; Schrader, Andres Jan; Schrader, Mark

    2014-06-01

    In 2006, the German Testicular Cancer Study Group initiated an extensive evidence-based national second-opinion network to improve the care of testicular cancer patients. The primary aims were to reflect the current state of testicular cancer treatment in Germany and to analyze the project's effect on the quality of care delivered to testicular cancer patients. A freely available internet-based platform was developed for the exchange of data between the urologists seeking advice and the 31 second-opinion givers. After providing all data relevant to the primary treatment decision, urologists received a second opinion on their therapy plan within testicular cancer patient in Germany were submitted to second-opinion centers. Second-opinion centers can help to improve the implementation of evidence into clinical practice.

  7. Construction and analysis of lncRNA-lncRNA synergistic networks to reveal clinically relevant lncRNAs in cancer.

    Science.gov (United States)

    Li, Yongsheng; Chen, Juan; Zhang, Jinwen; Wang, Zishan; Shao, Tingting; Jiang, Chunjie; Xu, Juan; Li, Xia

    2015-09-22

    Long non-coding RNAs (lncRNAs) play key roles in diverse biological processes. Moreover, the development and progression of cancer often involves the combined actions of several lncRNAs. Here we propose a multi-step method for constructing lncRNA-lncRNA functional synergistic networks (LFSNs) through co-regulation of functional modules having three features: common coexpressed genes of lncRNA pairs, enrichment in the same functional category and close proximity within protein interaction networks. Applied to three cancers, we constructed cancer-specific LFSNs and found that they exhibit a scale free and modular architecture. In addition, cancer-associated lncRNAs tend to be hubs and are enriched within modules. Although there is little synergistic pairing of lncRNAs across cancers, lncRNA pairs involved in the same cancer hallmarks by regulating same or different biological processes. Finally, we identify prognostic biomarkers within cancer lncRNA expression datasets using modules derived from LFSNs. In summary, this proof-of-principle study indicates synergistic lncRNA pairs can be identified through integrative analysis of genome-wide expression data sets and functional information.

  8. Topic Modeling of Smoking- and Cessation-Related Posts to the American Cancer Society's Cancer Survivor Network (CSN): Implications for Cessation Treatment for Cancer Survivors Who Smoke.

    Science.gov (United States)

    Westmaas, J Lee; McDonald, Bennett R; Portier, Kenneth M

    2017-08-01

    Smoking is a risk factor in at least 18 cancers, and approximately two-thirds of cancer survivors continue smoking following diagnosis. Text mining of survivors' online posts related to smoking and quitting could inform strategies to reduce smoking in this vulnerable population. We identified posts containing smoking/cessation-related keywords from the Cancer Survivors Network (CSN), an online cancer survivor community of 166 000 members and over 468 000 posts since inception. Unsupervised topic model analysis of posts since 2000 using Latent Dirichlet Allocation extracted 70 latent topics which two subject experts inspected for themes based on representative terms. Posterior analysis assessed the distribution of topics within posts, and the range of themes discussed across posts. Less than 1% of posts (n = 3998) contained smoking/cessation-related terms, and covered topics related to cancer diagnoses, treatments, and coping. The most frequent smoking-related topics were quit smoking methods (5.4% of posts), and the environment for quitters (2.9% of posts), such as the stigma associated with being a smoker diagnosed with cancer and lack of empathy experienced compared to nonsmokers. Smoking as a risk factor for one's diagnosis was a primary topic in only 1.7% of smoking/cessation-related posts. The low frequency of smoking/cessation-related posts may be due to expected criticism/stigma for smoking but may also suggests a need for health care providers to address smoking and assist with quitting in the diagnostic and treatment process. Topic model analysis revealed potential barriers that should be addressed in devising clinical or population-level interventions for cancer survivors who smoke. Although smoking is a major risk factor for cancer, little is known about cancer patients' or survivors' views or concerns about smoking and quitting. This study used text mining of posts to an online community of cancer patients and survivors to investigate contexts in which

  9. Adherence to treatment guidelines for primary sarcomas affects patient survival: a side study of the European CONnective TIssue CAncer NETwork (CONTICANET).

    Science.gov (United States)

    Rossi, C R; Vecchiato, A; Mastrangelo, G; Montesco, M C; Russano, F; Mocellin, S; Pasquali, S; Scarzello, G; Basso, U; Frasson, A; Pilati, P; Nitti, D; Lurkin, A; Ray-Coquard, I

    2013-06-01

    The impact of adherence to clinical practice guidelines (CPGs) for loco-regional treatment (i.e. surgery and radiotherapy) and chemotherapy on local disease control and survival in sarcoma patients was investigated in a European study conducted in an Italian region (Veneto). The completeness of the adherence to the Italian CPGs for sarcomas treatment was assessed by comparing the patient's charts and the CPGs. Propensity score-adjusted multivariate survival analysis was used to assess the impact of CPGs adherence on patient clinical outcomes. A total of 151 patients were included. Adherence to CPGs for loco-regional therapy and chemotherapy was observed in 106 out of 147 (70.2%) and 129 out of 139 (85.4%) patients, respectively. Non-adherence to CPGs for loco-regional treatment was independently associated with AJCC stage III disease [odds ratio (OR) 1.77, P = 0.011] and tumor-positive excision margin (OR 3.55, P = 0.003). Patients not treated according to the CPGs were at a higher risk of local recurrence [hazard ratio (HR) 5.4, P < 0.001] and had a shorter sarcoma-specific survival (HR 4.05, P < 0.001), independently of tumor stage. Incomplete adherence to CPGs for loco-regional treatment of sarcomas was associated with worse prognosis in patients with non-metastatic tumors.

  10. A neural network approach to breast cancer diagnosis as a constraint satisfaction problem

    International Nuclear Information System (INIS)

    Tourassi, Georgia D.; Markey, Mia K.; Lo, Joseph Y.; Floyd, Carey E. Jr.

    2001-01-01

    A constraint satisfaction neural network (CSNN) approach is proposed for breast cancer diagnosis using mammographic and patient history findings. Initially, the diagnostic decision to biopsy was formulated as a constraint satisfaction problem. Then, an associative memory type neural network was applied to solve the problem. The proposed network has a flexible, nonhierarchical architecture that allows it to operate not only as a predictive tool but also as an analysis tool for knowledge discovery of association rules. The CSNN was developed and evaluated using a database of 500 nonpalpable breast lesions with definitive histopathological diagnosis. The CSNN diagnostic performance was evaluated using receiver operating characteristic analysis (ROC). The results of the study showed that the CSNN ROC area index was 0.84±0.02. The CSNN predictive performance is competitive with that achieved by experienced radiologists and backpropagation artificial neural networks (BP-ANNs) presented before. Furthermore, the study illustrates how CSNN can be used as a knowledge discovery tool overcoming some of the well-known limitations of BP-ANNs

  11. Classification of breast cancer cytological specimen using convolutional neural network

    Science.gov (United States)

    Żejmo, Michał; Kowal, Marek; Korbicz, Józef; Monczak, Roman

    2017-01-01

    The paper presents a deep learning approach for automatic classification of breast tumors based on fine needle cytology. The main aim of the system is to distinguish benign from malignant cases based on microscopic images. Experiment was carried out on cytological samples derived from 50 patients (25 benign cases + 25 malignant cases) diagnosed in Regional Hospital in Zielona Góra. To classify microscopic images, we used convolutional neural networks (CNN) of two types: GoogLeNet and AlexNet. Due to the very large size of images of cytological specimen (on average 200000 × 100000 pixels), they were divided into smaller patches of size 256 × 256 pixels. Breast cancer classification usually is based on morphometric features of nuclei. Therefore, training and validation patches were selected using Support Vector Machine (SVM) so that suitable amount of cell material was depicted. Neural classifiers were tuned using GPU accelerated implementation of gradient descent algorithm. Training error was defined as a cross-entropy classification loss. Classification accuracy was defined as the percentage ratio of successfully classified validation patches to the total number of validation patches. The best accuracy rate of 83% was obtained by GoogLeNet model. We observed that more misclassified patches belong to malignant cases.

  12. The emerging potential for network analysis to inform precision cancer medicine.

    Science.gov (United States)

    Ozturk, Kivilcim; Dow, Michelle; Carlin, Daniel E; Bejar, Rafael; Carter, Hannah

    2018-06-14

    Precision cancer medicine promises to tailor clinical decisions to patients using genomic information. Indeed, successes of drugs targeting genetic alterations in tumors, such as imatinib that targets BCR-ABL in chronic myelogenous leukemia, have demonstrated the power of this approach. However biological systems are complex, and patients may differ not only by the specific genetic alterations in their tumor, but by more subtle interactions among such alterations. Systems biology and more specifically, network analysis, provides a framework for advancing precision medicine beyond clinical actionability of individual mutations. Here we discuss applications of network analysis to study tumor biology, early methods for N-of-1 tumor genome analysis and the path for such tools to the clinic. Copyright © 2018. Published by Elsevier Ltd.

  13. Variation in Definitive Therapy for Localized Non-Small Cell Lung Cancer Among National Comprehensive Cancer Network Institutions

    Energy Technology Data Exchange (ETDEWEB)

    Valle, Luca F. [Geisel School of Medicine at Dartmouth College, Dartmouth College, Hanover, New Hampshire (United States); Jagsi, Reshma [Department of Radiation Oncology, University of Michigan Comprehensive Cancer Center, Ann Arbor, Michigan (United States); Bobiak, Sarah N.; Zornosa, Carrie [National Comprehensive Cancer Network, Fort Washington, Pennsylvania (United States); D' Amico, Thomas A. [Department of Surgery, Division of Thoracic Surgery, Duke Cancer Institute, Durham, North Carolina (United States); Pisters, Katherine M. [Department of Thoracic/Head and Neck Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Dexter, Elisabeth U. [Department of Thoracic Surgery, Roswell Park Cancer Institute, Buffalo, New York (United States); Niland, Joyce C. [Department of Information Sciences, City of Hope Comprehensive Cancer Center, Duarte, California (United States); Hayman, James A. [Department of Radiation Oncology, University of Michigan Comprehensive Cancer Center, Ann Arbor, Michigan (United States); Kapadia, Nirav S., E-mail: Nirav.S.Kapadia@hitchcock.org [Department of Radiation Oncology, Dartmouth-Hitchcock Norris Cotton Cancer Center, Lebanon, New Hampshire (United States); Dartmouth Institute for Health Policy and Clinical Practice, Lebanon, New Hampshire (United States)

    2016-02-01

    Purpose: This study determined practice patterns in the staging and treatment of patients with stage I non-small cell lung cancer (NSCLC) among National Comprehensive Cancer Network (NCCN) member institutions. Secondary aims were to determine trends in the use of definitive therapy, predictors of treatment type, and acute adverse events associated with primary modalities of treatment. Methods and Materials: Data from the National Comprehensive Cancer Network Oncology Outcomes Database from 2007 to 2011 for US patients with stage I NSCLC were used. Main outcome measures included patterns of care, predictors of treatment, acute morbidity, and acute mortality. Results: Seventy-nine percent of patients received surgery, 16% received definitive radiation therapy (RT), and 3% were not treated. Seventy-four percent of the RT patients received stereotactic body RT (SBRT), and the remainder received nonstereotactic RT (NSRT). Among participating NCCN member institutions, the number of surgeries-to-RT course ratios varied between 1.6 and 34.7 (P<.01), and the SBRT-to-NSRT ratio varied between 0 and 13 (P=.01). Significant variations were also observed in staging practices, with brain imaging 0.33 (0.25-0.43) times as likely and mediastinoscopy 31.26 (21.84-44.76) times more likely for surgical patients than for RT patients. Toxicity rates for surgical and for SBRT patients were similar, although the rates were double for NSRT patients. Conclusions: The variations in treatment observed among NCCN institutions reflects the lack of level I evidence directing the use of surgery or SBRT for stage I NSCLC. In this setting, research of patient and physician preferences may help to guide future decision making.

  14. Variation in Definitive Therapy for Localized Non-Small Cell Lung Cancer Among National Comprehensive Cancer Network Institutions

    International Nuclear Information System (INIS)

    Valle, Luca F.; Jagsi, Reshma; Bobiak, Sarah N.; Zornosa, Carrie; D'Amico, Thomas A.; Pisters, Katherine M.; Dexter, Elisabeth U.; Niland, Joyce C.; Hayman, James A.; Kapadia, Nirav S.

    2016-01-01

    Purpose: This study determined practice patterns in the staging and treatment of patients with stage I non-small cell lung cancer (NSCLC) among National Comprehensive Cancer Network (NCCN) member institutions. Secondary aims were to determine trends in the use of definitive therapy, predictors of treatment type, and acute adverse events associated with primary modalities of treatment. Methods and Materials: Data from the National Comprehensive Cancer Network Oncology Outcomes Database from 2007 to 2011 for US patients with stage I NSCLC were used. Main outcome measures included patterns of care, predictors of treatment, acute morbidity, and acute mortality. Results: Seventy-nine percent of patients received surgery, 16% received definitive radiation therapy (RT), and 3% were not treated. Seventy-four percent of the RT patients received stereotactic body RT (SBRT), and the remainder received nonstereotactic RT (NSRT). Among participating NCCN member institutions, the number of surgeries-to-RT course ratios varied between 1.6 and 34.7 (P<.01), and the SBRT-to-NSRT ratio varied between 0 and 13 (P=.01). Significant variations were also observed in staging practices, with brain imaging 0.33 (0.25-0.43) times as likely and mediastinoscopy 31.26 (21.84-44.76) times more likely for surgical patients than for RT patients. Toxicity rates for surgical and for SBRT patients were similar, although the rates were double for NSRT patients. Conclusions: The variations in treatment observed among NCCN institutions reflects the lack of level I evidence directing the use of surgery or SBRT for stage I NSCLC. In this setting, research of patient and physician preferences may help to guide future decision making.

  15. Endogenous Molecular-Cellular Network Cancer Theory: A Systems Biology Approach.

    Science.gov (United States)

    Wang, Gaowei; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

    2018-01-01

    In light of ever apparent limitation of the current dominant cancer mutation theory, a quantitative hypothesis for cancer genesis and progression, endogenous molecular-cellular network hypothesis has been proposed from the systems biology perspective, now for more than 10 years. It was intended to include both the genetic and epigenetic causes to understand cancer. Its development enters the stage of meaningful interaction with experimental and clinical data and the limitation of the traditional cancer mutation theory becomes more evident. Under this endogenous network hypothesis, we established a core working network of hepatocellular carcinoma (HCC) according to the hypothesis and quantified the working network by a nonlinear dynamical system. We showed that the two stable states of the working network reproduce the main known features of normal liver and HCC at both the modular and molecular levels. Using endogenous network hypothesis and validated working network, we explored genetic mutation pattern in cancer and potential strategies to cure or relieve HCC from a totally new perspective. Patterns of genetic mutations have been traditionally analyzed by posteriori statistical association approaches in light of traditional cancer mutation theory. One may wonder the possibility of a priori determination of any mutation regularity. Here, we found that based on the endogenous network theory the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. Normal hepatocyte and cancerous hepatocyte stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable

  16. Hereditary association between testicular cancer and familial ovarian cancer: A Familial Ovarian Cancer Registry study.

    Science.gov (United States)

    Etter, John Lewis; Eng, Kevin; Cannioto, Rikki; Kaur, Jasmine; Almohanna, Hani; Alqassim, Emad; Szender, J Brian; Joseph, Janine M; Lele, Shashikant; Odunsi, Kunle; Moysich, Kirsten B

    2018-04-01

    Although family history of testicular cancer is well-established as a risk factor for testicular cancer, it is unknown whether family history of ovarian cancer is associated with risk of testicular cancer. Using data from the Familial Ovarian Cancer Registry on 2636 families with multiple cases of ovarian cancer, we systematically compared relative frequencies of ovarian cancer among relatives of men with testicular and non-testicular cancers. Thirty-one families with cases of both ovarian and testicular cancer were identified. We observed that, among men with cancer, those with testicular cancer were more likely to have a mother with ovarian cancer than those with non-testicular cancers (OR = 3.32, p = 0.004). Zero paternal grandmothers of men with testicular cancer had ovarian cancer. These observations provide compelling preliminary evidence for a familial association between ovarian and testicular cancers Future studies should be designed to further investigate this association and evaluate X-linkage. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Automatic classification of ovarian cancer types from cytological images using deep convolutional neural networks.

    Science.gov (United States)

    Wu, Miao; Yan, Chuanbo; Liu, Huiqiang; Liu, Qian

    2018-06-29

    Ovarian cancer is one of the most common gynecologic malignancies. Accurate classification of ovarian cancer types (serous carcinoma, mucous carcinoma, endometrioid carcinoma, transparent cell carcinoma) is an essential part in the different diagnosis. Computer-aided diagnosis (CADx) can provide useful advice for pathologists to determine the diagnosis correctly. In our study, we employed a Deep Convolutional Neural Networks (DCNN) based on AlexNet to automatically classify the different types of ovarian cancers from cytological images. The DCNN consists of five convolutional layers, three max pooling layers, and two full reconnect layers. Then we trained the model by two group input data separately, one was original image data and the other one was augmented image data including image enhancement and image rotation. The testing results are obtained by the method of 10-fold cross-validation, showing that the accuracy of classification models has been improved from 72.76 to 78.20% by using augmented images as training data. The developed scheme was useful for classifying ovarian cancers from cytological images. © 2018 The Author(s).

  18. TCGA study identifies genomic features of cervical cancer

    Science.gov (United States)

    Investigators with The Cancer Genome Atlas (TCGA) Research Network have identified novel genomic and molecular characteristics of cervical cancer that will aid in subclassification of the disease and may help target therapies that are most appropriate for each patient.

  19. Hypoxia induces a phase transition within a kinase signaling network in cancer cells.

    Science.gov (United States)

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B; Shin, Young Shik; Mischel, Paul S; Levine, R D; Heath, James R

    2013-04-09

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)--a critical component of hypoxic signaling and a compelling cancer drug target--is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier's principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles.

  20. Hypoxia induces a phase transition within a kinase signaling network in cancer cells

    Science.gov (United States)

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B.; Shin, Young Shik; Mischel, Paul S.; Levine, R. D.; Heath, James R.

    2013-01-01

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)—a critical component of hypoxic signaling and a compelling cancer drug target—is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier’s principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles. PMID:23530221

  1. Networking and Information Technology Workforce Study: Final Report

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — This report presents the results of a study of the global Networking and Information Technology NIT workforce undertaken for the Networking and Information...

  2. Chemotherapeutic prevention studies of prostate cancer

    DEFF Research Database (Denmark)

    Djavan, Bob; Zlotta, Alexandre; Schulman, Claude

    2004-01-01

    Despite advances in the detection and management of prostate cancer, this disease remains a major cause of morbidity and mortality in men. Increasing attention has focused on the role of chemoprevention for prostate cancer, ie the administration of agents that inhibit 1 or more steps in the natural...... history of prostate carcinogenesis. We review prostate cancer chemoprevention studies in Europe....

  3. Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

    Science.gov (United States)

    Roffman, David; Hart, Gregory; Girardi, Michael; Ko, Christine J; Deng, Jun

    2018-01-26

    Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The objective of this study was to develop and validate a multi-parameterized artificial neural network based on available personal health information for early detection of NMSC with high sensitivity and specificity, even in the absence of known UVR exposure and family history. The 1997-2015 NHIS adult survey data used to train and validate our neural network (NN) comprised of 2,056 NMSC and 460,574 non-cancer cases. We extracted 13 parameters for our NN: gender, age, BMI, diabetic status, smoking status, emphysema, asthma, race, Hispanic ethnicity, hypertension, heart diseases, vigorous exercise habits, and history of stroke. This study yielded an area under the ROC curve of 0.81 and 0.81 for training and validation, respectively. Our results (training sensitivity 88.5% and specificity 62.2%, validation sensitivity 86.2% and specificity 62.7%) were comparable to a previous study of basal and squamous cell carcinoma prediction that also included UVR exposure and family history information. These results indicate that our NN is robust enough to make predictions, suggesting that we have identified novel associations and potential predictive parameters of NMSC.

  4. Transduction motif analysis of gastric cancer based on a human signaling network

    Energy Technology Data Exchange (ETDEWEB)

    Liu, G.; Li, D.Z.; Jiang, C.S.; Wang, W. [Fuzhou General Hospital of Nanjing Command, Department of Gastroenterology, Fuzhou, China, Department of Gastroenterology, Fuzhou General Hospital of Nanjing Command, Fuzhou (China)

    2014-04-04

    To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR, MAPK14, BCL2L1, KRT18, PTPN6, CASP3, TGFBR2, AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.

  5. Genome network medicine: innovation to overcome huge challenges in cancer therapy.

    Science.gov (United States)

    Roukos, Dimitrios H

    2014-01-01

    The post-ENCODE era shapes now a new biomedical research direction for understanding transcriptional and signaling networks driving gene expression and core cellular processes such as cell fate, survival, and apoptosis. Over the past half century, the Francis Crick 'central dogma' of single n gene/protein-phenotype (trait/disease) has defined biology, human physiology, disease, diagnostics, and drugs discovery. However, the ENCODE project and several other genomic studies using high-throughput sequencing technologies, computational strategies, and imaging techniques to visualize regulatory networks, provide evidence that transcriptional process and gene expression are regulated by highly complex dynamic molecular and signaling networks. This Focus article describes the linear experimentation-based limitations of diagnostics and therapeutics to cure advanced cancer and the need to move on from reductionist to network-based approaches. With evident a wide genomic heterogeneity, the power and challenges of next-generation sequencing (NGS) technologies to identify a patient's personal mutational landscape for tailoring the best target drugs in the individual patient are discussed. However, the available drugs are not capable of targeting aberrant signaling networks and research on functional transcriptional heterogeneity and functional genome organization is poorly understood. Therefore, the future clinical genome network medicine aiming at overcoming multiple problems in the new fields of regulatory DNA mapping, noncoding RNA, enhancer RNAs, and dynamic complexity of transcriptional circuitry are also discussed expecting in new innovation technology and strong appreciation of clinical data and evidence-based medicine. The problematic and potential solutions in the discovery of next-generation, molecular, and signaling circuitry-based biomarkers and drugs are explored. © 2013 Wiley Periodicals, Inc.

  6. Studies on a network of complex neurons

    Science.gov (United States)

    Chakravarthy, Srinivasa V.; Ghosh, Joydeep

    1993-09-01

    In the last decade, much effort has been directed towards understanding the role of chaos in the brain. Work with rabbits reveals that in the resting state the electrical activity on the surface of the olfactory bulb is chaotic. But, when the animal is involved in a recognition task, the activity shifts to a specific pattern corresponding to the odor that is being recognized. Unstable, quasiperiodic behavior can be found in a class of conservative, deterministic physical systems called the Hamiltonian systems. In this paper, we formulate a complex version of Hopfield's network of real parameters and show that a variation on this model is a conservative system. Conditions under which the complex network can be used as a Content Addressable memory are studied. We also examine the effect of singularities of the complex sigmoid function on the network dynamics. The network exhibits unpredictable behavior at the singularities due to the failure of a uniqueness condition for the solution of the dynamic equations. On incorporating a weight adaptation rule, the structure of the resulting complex network equations is shown to have an interesting similarity with Kosko's Adaptive Bidirectional Associative Memory.

  7. Provider-based research networks and diffusion of surgical technologies among patients with early-stage kidney cancer.

    Science.gov (United States)

    Tan, Hung-Jui; Meyer, Anne-Marie; Kuo, Tzy-Mey; Smith, Angela B; Wheeler, Stephanie B; Carpenter, William R; Nielsen, Matthew E

    2015-03-15

    Provider-based research networks such as the National Cancer Institute's Community Clinical Oncology Program (CCOP) have been shown to facilitate the translation of evidence-based cancer care into clinical practice. This study compared the utilization of laparoscopy and partial nephrectomy among patients with early-stage kidney cancer according to their exposure to CCOP-affiliated providers. With linked Surveillance, Epidemiology, and End Results-Medicare data, patients with T1aN0M0 kidney cancer who had been treated with nephrectomy from 2000 to 2007 were identified. For each patient, the receipt of care from a CCOP physician or hospital and treatment with laparoscopy or partial nephrectomy were determined. Adjusted for patient characteristics (eg, age, sex, and marital status) and other organizational features (eg, community hospital and National Cancer Institute-designated cancer center), multivariate logistic regression was used to estimate the association between each surgical innovation and CCOP affiliation. During the study interval, 1578 patients (26.8%) were treated by a provider with a CCOP affiliation. Trends in the utilization of laparoscopy and partial nephrectomy remained similar between affiliated and nonaffiliated providers (P ≥ .05). With adjustments for patient characteristics, organizational features, and clustering, no association was noted between CCOP affiliation and the use of laparoscopy (odds ratio [OR], 1.11; 95% confidence interval [CI], 0.81-1.53) or partial nephrectomy (OR, 1.04; 95% CI, 0.82-1.32) despite the more frequent receipt of these treatments in academic settings (P kidney cancer, indicating perhaps a more limited scope to provider-based research networks as they pertain to translational efforts in cancer care. © 2014 American Cancer Society.

  8. Case studies of attacks on communication networks

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Sin Bok; Han, Eon Suk [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1996-06-15

    Recently, as the computer hardware and communications are developed, the data exchange through inter-networking has been highlighted and the data is being recognized as a great asset. Most of the organizations, businesses and enterprises are open to the external world-computer communication networks, attention must be focused on the securities of the information infrastructure. A government organization has been developing 'Circuits Analyzers', and 'Hacker-Tracking Program' and is struggling to track down sneakers. In this report, we analyze the contents of the cases where the communication network has been invaded, from the past up until now in Korea. This report also contains the result of a study on E-mail security, for the protection of KAERI Integrated Management Information System under which utilizes the CALS concepts and web services. (Author)

  9. Case studies of attacks on communication networks

    International Nuclear Information System (INIS)

    Kang, Sin Bok; Han, Eon Suk

    1996-06-01

    Recently, as the computer hardware and communications are developed, the data exchange through inter-networking has been highlighted and the data is being recognized as a great asset. Most of the organizations, businesses and enterprises are open to the external world-computer communication networks, attention must be focused on the securities of the information infrastructure. A government organization has been developing 'Circuits Analyzers', and 'Hacker-Tracking Program' and is struggling to track down sneakers. In this report, we analyze the contents of the cases where the communication network has been invaded, from the past up until now in Korea. This report also contains the result of a study on E-mail security, for the protection of KAERI Integrated Management Information System under which utilizes the CALS concepts and web services. (Author)

  10. Establishment of the Fox Chase Network Breast Cancer Risk Registry

    National Research Council Canada - National Science Library

    Daly, Mary

    1997-01-01

    .... The development of the Fox Chase Cancer Center Breast Cancer Risk Registry was proposed to facilitate research in the epidemiologic and genetic predictors of disease and will permit evaluation...

  11. Combining Pathway Identification and Breast Cancer Survival Prediction via Screening-Network Methods

    Directory of Open Access Journals (Sweden)

    Antonella Iuliano

    2018-06-01

    Full Text Available Breast cancer is one of the most common invasive tumors causing high mortality among women. It is characterized by high heterogeneity regarding its biological and clinical characteristics. Several high-throughput assays have been used to collect genome-wide information for many patients in large collaborative studies. This knowledge has improved our understanding of its biology and led to new methods of diagnosing and treating the disease. In particular, system biology has become a valid approach to obtain better insights into breast cancer biological mechanisms. A crucial component of current research lies in identifying novel biomarkers that can be predictive for breast cancer patient prognosis on the basis of the molecular signature of the tumor sample. However, the high dimension and low sample size of data greatly increase the difficulty of cancer survival analysis demanding for the development of ad-hoc statistical methods. In this work, we propose novel screening-network methods that predict patient survival outcome by screening key survival-related genes and we assess the capability of the proposed approaches using METABRIC dataset. In particular, we first identify a subset of genes by using variable screening techniques on gene expression data. Then, we perform Cox regression analysis by incorporating network information associated with the selected subset of genes. The novelty of this work consists in the improved prediction of survival responses due to the different types of screenings (i.e., a biomedical-driven, data-driven and a combination of the two before building the network-penalized model. Indeed, the combination of the two screening approaches allows us to use the available biological knowledge on breast cancer and complement it with additional information emerging from the data used for the analysis. Moreover, we also illustrate how to extend the proposed approaches to integrate an additional omic layer, such as copy number

  12. Brain network alterations and vulnerability to simulated neurodegeneration in breast cancer.

    Science.gov (United States)

    Kesler, Shelli R; Watson, Christa L; Blayney, Douglas W

    2015-08-01

    Breast cancer and its treatments are associated with mild cognitive impairment and brain changes that could indicate an altered or accelerated brain aging process. We applied diffusion tensor imaging and graph theory to measure white matter organization and connectivity in 34 breast cancer survivors compared with 36 matched healthy female controls. We also investigated how brain networks (connectomes) in each group responded to simulated neurodegeneration based on network attack analysis. Compared with controls, the breast cancer group demonstrated significantly lower fractional anisotropy, altered small-world connectome properties, lower brain network tolerance to systematic region (node), and connection (edge) attacks and significant cognitive impairment. Lower tolerance to network attack was associated with cognitive impairment in the breast cancer group. These findings provide further evidence of diffuse white matter pathology after breast cancer and extend the literature in this area with unique data demonstrating increased vulnerability of the post-breast cancer brain network to future neurodegenerative processes. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Boolean network model for cancer pathways: predicting carcinogenesis and targeted therapy outcomes.

    Directory of Open Access Journals (Sweden)

    Herman F Fumiã

    Full Text Available A Boolean dynamical system integrating the main signaling pathways involved in cancer is constructed based on the currently known protein-protein interaction network. This system exhibits stationary protein activation patterns--attractors--dependent on the cell's microenvironment. These dynamical attractors were determined through simulations and their stabilities against mutations were tested. In a higher hierarchical level, it was possible to group the network attractors into distinct cell phenotypes and determine driver mutations that promote phenotypic transitions. We find that driver nodes are not necessarily central in the network topology, but at least they are direct regulators of central components towards which converge or through which crosstalk distinct cancer signaling pathways. The predicted drivers are in agreement with those pointed out by diverse census of cancer genes recently performed for several human cancers. Furthermore, our results demonstrate that cell phenotypes can evolve towards full malignancy through distinct sequences of accumulated mutations. In particular, the network model supports routes of carcinogenesis known for some tumor types. Finally, the Boolean network model is employed to evaluate the outcome of molecularly targeted cancer therapies. The major find is that monotherapies were additive in their effects and that the association of targeted drugs is necessary for cancer eradication.

  14. Identifying the Gene Signatures from Gene-Pathway Bipartite Network Guarantees the Robust Model Performance on Predicting the Cancer Prognosis

    Directory of Open Access Journals (Sweden)

    Li He

    2014-01-01

    Full Text Available For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.

  15. Characterization of the Usage of the Serine Metabolic Network in Human Cancer

    Directory of Open Access Journals (Sweden)

    Mahya Mehrmohamadi

    2014-11-01

    Full Text Available The serine, glycine, one-carbon (SGOC metabolic network is implicated in cancer pathogenesis, but its general functions are unknown. We carried out a computational reconstruction of the SGOC network and then characterized its expression across thousands of cancer tissues. Pathways including methylation and redox metabolism exhibited heterogeneous expression indicating a strong context dependency of their usage in tumors. From an analysis of coexpression, simultaneous up- or downregulation of nucleotide synthesis, NADPH, and glutathione synthesis was found to be a common occurrence in all cancers. Finally, we developed a method to trace the metabolic fate of serine using stable isotopes, high-resolution mass spectrometry, and a mathematical model. Although the expression of single genes didn’t appear indicative of flux, the collective expression of several genes in a given pathway allowed for successful flux prediction. Altogether, these findings identify expansive and heterogeneous functions for the SGOC metabolic network in human cancer.

  16. A prospective audit of early stoma complications in colorectal cancer treatment throughout the Greater Manchester and Cheshire colorectal cancer network.

    Science.gov (United States)

    Parmar, K L; Zammit, M; Smith, A; Kenyon, D; Lees, N P

    2011-08-01

    The study aimed to identify the incidence of early stoma problems after surgery for colorectal cancer to identify predisposing factors and to assess the effect on discharge from hospital and the greater need for community stoma care. A prospective study of 192 patients was carried out over a six-month period in the 13 units of the Greater Manchester and Cheshire Cancer Network. Stoma problems were categorized into fistula, leakage, pancaking, necrosis, retraction, separation, stenosis, skin problems, parastomal hernia, suboptimal stoma site and need for resiting or refashioning. Differences in incidence between units (anonymized) were analysed, and the effect of stoma complications on length of hospital stay and the need for additional community stoma care was determined. One hundred and ninety-two patients with stomas were included, of which 52 (27.1%) were identified as being problematic (range 0-66.7% between units). Significant risk factors included stoma type (colostomy) (P stoma length (P = 0.006), higher BMI (P = 0.043), emergency surgery (P = 0.002) and lack of preoperative site marking (P stomas were associated with longer hospital stay (P care (P Stoma type, stoma length, body mass index, emergency surgery and lack of preoperative marking were significant risk factors. Overall complication rates compare favourably with other studies. © 2011 The Authors. Colorectal Disease © 2011 The Association of Coloproctology of Great Britain and Ireland.

  17. Clinicopathological study of asymptomatic gastric cancer and symptomatic gastric cancer

    International Nuclear Information System (INIS)

    Sato, Toshiteru

    2008-01-01

    Gastric cancer can be classified into two categories based on the absence or presence of symptoms at diagnosis. Differences in clinicopathological features and prognoses between asymptomatic gastric cancer (ACG) and symptomatic gastric cancer (SGC) can be used to inform diagnosis strategies and ultimately improve survival rates. All cases of gastric cancer (239 AGC, 323 SGC) diagnosed in our hospital between 1997 and 1999 were used in this study. ACG patients showed significantly higher frequency of males, cases of early cancer, cases found by a mass screening program, cases treated by endoscopic resection, cases treated by curative operation, cases of type 0 macroscopic finding, cases of histologically-differentiated type, and stage I cases. By contrast, SGC patients showed significantly higher numbers of cases treated by chemotherapy alone or best support care, cases of type 2, 3, and 4 macroscopic findings, cases occupying the whole stomach, and cases of stage II, III, IV. Statistically significant differences were also found for the 5-year survival rate (83.3% in AGC, 41.2% in SGC), the incidence of early cancer (90.1% in AGC, 83.7% in SGC), and for advanced cancer (38.7% in AGC, 22.7% in SGC). The higher incidence of advanced cases in SGC than in AGC (40.0% vs. 13.0%), coupled with the low 5-year survival rate of advanced SGC (22.7%), provides strong evidence of the importance of diagnosing gastric cancer during its asymptomatic period. (author)

  18. Development of the Moffitt Cancer Network as a Telemedicine and Teleconferencing Educational Tool for Health Care Providers

    National Research Council Canada - National Science Library

    Krischer, Jeffrey

    2002-01-01

    The Moffitt Cancer Network's (MCN) goal is to provide up-to-date oncology related information, resources, and education to oncology health care providers and researchers for the prevention and cure of cancer...

  19. Epidemiologic study of uterine cancer, Hiroshima

    Energy Technology Data Exchange (ETDEWEB)

    Ishimaru, Toranosuke

    1965-12-10

    As a cause of death in females, cancer of the uterus is one of the important cancers in Japan. In 1962 it was responsible for 15.5% of all the deaths due to cancer in women and ranked next to the proportion attributed to cancer of the stomach. The JNIH-ABCC Life Span Study of A-bomb survivors also shows that cancer of the stomach and uterus were the major causes of cancer deaths in the female population. The present study, which was carried out in 1963, was begun in the hope of elucidating some of the relationships of the factors other than radiation possibly associated with the incidence of cancer of the uterus in the Life Span Study (ST 100) sample in Horoshima. Environmental factors considered to play a role in the development of uterine cancer were studied by interview with a close relative of the subject. The data did not clearly support the findings reported elsewhere that residential history, occupational history, history of marital status, smoking and alcohol drinking habits, and socioeconomic factors were associated with the incidence of cancer of the uterus. A brief analysis was also conducted for the accuracy of death certificates. The results suggest that an epidemiologic study should be conducted on morbidity data derived from pathologic findings and a revised plan is desirable to elucidate the factors associated with the incidence of cancer of the uterus using the various recent experimental findings as references. 124 references, 15 tables.

  20. Social networks and cooperation: a bibliometric study

    Directory of Open Access Journals (Sweden)

    Ana Paula Lopes

    2013-05-01

    Full Text Available The social network analysis involves social and behavioral science. The decentralization of productive activities, such as the formation of "network organizations" as a result of downsizing of large corporate structures of the past, marked by outsoucing and formation of alliances, shows the importance of this theme. The main objective of this paper is to analyze the theory of cooperation and social networks over a period of 24 years. For this, was performed a bibliometric study with content analysis. The database chosen for the initial sample search was ISI Web of Science. The search topics were “social network” and “cooperation”. Were analyzed 97 articles and their references, through networks of citations. The main identified research groups dealing with issues related to trust, strategic alliances, natural cooperation, game theory, social capital, intensity of interaction, reciprocity and innovation. It was found that the publications occurred in a large number of journals, which indicates that the theme is multidisciplinary, and only five journals published at least three articles. Although the first publication has occurred in 1987, was from 2006 that the publications effectively increased. The areas most related to the theme of the research were performance, evolution, management, graphics, model and game theory.

  1. Photoelastic studies of some polybutadiene networks

    Energy Technology Data Exchange (ETDEWEB)

    Mark, J E; Llorente, M A [Cincinnati Univ., OH (USA). Dept. of Chemistry

    1981-06-01

    Two butadiene polymers were used in this investigation, one with 98.5% cis-1,4 units and the other with an approximately equibinary mixture of cis and trans units. Elastomeric networks prepared from these polymers were studied in elongation, in both the swollen and unswollen states over the temperature range -30 to 95/sup 0/C. There is evidence for crystallization in these networks, particularly as manifested by marked increases in birefringence at relatively low elongation and at temperatures as high as 40/sup 0/C. As expected, the birefringence and related quantities were found to be more sensitive to crystallization than the force, with the optical-configuration parameter and the stress-optical coefficient showing the greatest sensitivity. In the case of the cis-trans copolymer, the crystallization involves trans sequences, which are of relatively high melting point, and thus occurs at a temperature higher than for the lower melting cis sequences in the high-cis networks. The results which were free from the effects of network crystallization were used to calculate values of the temperature coefficient of the unperturbed dimensions of the chains, and values of the optical-configuration parameter. These configuration-dependent properties were found to be in satisfactory agreement with previously published theoretical results based on a rotational isomeric state model of these chain molecules.

  2. A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients.

    Directory of Open Access Journals (Sweden)

    Mingguang Shi

    Full Text Available Several studies have reported gene expression signatures that predict recurrence risk in stage II and III colorectal cancer (CRC patients with minimal gene membership overlap and undefined biological relevance. The goal of this study was to investigate biological themes underlying these signatures, to infer genes of potential mechanistic importance to the CRC recurrence phenotype and to test whether accurate prognostic models can be developed using mechanistically important genes.We investigated eight published CRC gene expression signatures and found no functional convergence in Gene Ontology enrichment analysis. Using a random walk-based approach, we integrated these signatures and publicly available somatic mutation data on a protein-protein interaction network and inferred 487 genes that were plausible candidate molecular underpinnings for the CRC recurrence phenotype. We named the list of 487 genes a NEM signature because it integrated information from Network, Expression, and Mutation. The signature showed significant enrichment in four biological processes closely related to cancer pathophysiology and provided good coverage of known oncogenes, tumor suppressors, and CRC-related signaling pathways. A NEM signature-based Survival Support Vector Machine prognostic model was trained using a microarray gene expression dataset and tested on an independent dataset. The model-based scores showed a 75.7% concordance with the real survival data and separated patients into two groups with significantly different relapse-free survival (p = 0.002. Similar results were obtained with reversed training and testing datasets (p = 0.007. Furthermore, adjuvant chemotherapy was significantly associated with prolonged survival of the high-risk patients (p = 0.006, but not beneficial to the low-risk patients (p = 0.491.The NEM signature not only reflects CRC biology but also informs patient prognosis and treatment response. Thus, the network

  3. Study of Tools for Network Discovery and Network Mapping

    Science.gov (United States)

    2003-11-01

    connected to the switch. iv. Accessibility of historical data and event data In general, network discovery tools keep a history of the collected...has the following software dependencies: - Java Virtual machine 76 - Perl modules - RRD Tool - TomCat - PostgreSQL STRENGTHS AND...systems - provide a simple view of the current network status - generate alarms on status change - generate history of status change VISUAL MAP

  4. Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

    Science.gov (United States)

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

    2015-02-01

    Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have

  5. Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.

    Directory of Open Access Journals (Sweden)

    Taosheng Xu

    Full Text Available Identifying cancer subtypes is an important component of the personalised medicine framework. An increasing number of computational methods have been developed to identify cancer subtypes. However, existing methods rarely use information from gene regulatory networks to facilitate the subtype identification. It is widely accepted that gene regulatory networks play crucial roles in understanding the mechanisms of diseases. Different cancer subtypes are likely caused by different regulatory mechanisms. Therefore, there are great opportunities for developing methods that can utilise network information in identifying cancer subtypes.In this paper, we propose a method, weighted similarity network fusion (WSNF, to utilise the information in the complex miRNA-TF-mRNA regulatory network in identifying cancer subtypes. We firstly build the regulatory network where the nodes represent the features, i.e. the microRNAs (miRNAs, transcription factors (TFs and messenger RNAs (mRNAs and the edges indicate the interactions between the features. The interactions are retrieved from various interatomic databases. We then use the network information and the expression data of the miRNAs, TFs and mRNAs to calculate the weight of the features, representing the level of importance of the features. The feature weight is then integrated into a network fusion approach to cluster the samples (patients and thus to identify cancer subtypes. We applied our method to the TCGA breast invasive carcinoma (BRCA and glioblastoma multiforme (GBM datasets. The experimental results show that WSNF performs better than the other commonly used computational methods, and the information from miRNA-TF-mRNA regulatory network contributes to the performance improvement. The WSNF method successfully identified five breast cancer subtypes and three GBM subtypes which show significantly different survival patterns. We observed that the expression patterns of the features in some mi

  6. Targeted agents for patients with advanced/metastatic pancreatic cancer: A protocol for systematic review and network meta-analysis.

    Science.gov (United States)

    Di, Baoshan; Pan, Bei; Ge, Long; Ma, Jichun; Wu, Yiting; Guo, Tiankang

    2018-03-01

    Pancreatic cancer (PC) is a devastating malignant tumor. Although surgical resection may offer a good prognosis and prolong survival, approximately 80% patients with PC are always diagnosed as unresectable tumor. National Comprehensive Cancer Network's (NCCN) recommended gemcitabine-based chemotherapy as efficient treatment. While, according to recent studies, targeted agents might be a better available option for advanced or metastatic pancreatic cancer patients. The aim of this systematic review and network meta-analysis will be to examine the differences of different targeted interventions for advanced/metastatic PC patients. We will conduct this systematic review and network meta-analysis using Bayesian method and according to Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P) statement. To identify relevant studies, 6 electronic databases including PubMed, EMBASE, the Cochrane Central Register of Controlled Trials (CENTRAL), Web of science, CNKI (Chinese National Knowledge Infrastructure), and CBM (Chinese Biological Medical Database) will be searched. The risk of bias in included randomized controlled trials (RCTs) will be assessed using the Cochrane Handbook version 5.1.0. And we will use GRADE approach to assess the quality of evidence from network meta-analysis. Data will be analyzed using R 3.4.1 software. To the best of our knowledge, this systematic review and network meta-analysis will firstly use both direct and indirect evidence to compare the differences of different targeted agents and targeted agents plus chemotherapy for advanced/metastatic pancreatic cancer patients. This is a protocol of systematic review and meta-analysis, so the ethical approval and patient consent are not required. We will disseminate the results of this review by submitting to a peer-reviewed journal.

  7. Parameter optimization for constructing competing endogenous RNA regulatory network in glioblastoma multiforme and other cancers.

    Science.gov (United States)

    Chiu, Yu-Chiao; Hsiao, Tzu-Hung; Chen, Yidong; Chuang, Eric Y

    2015-01-01

    In addition to direct targeting and repressing mRNAs, recent studies reported that microRNAs (miRNAs) can bridge up an alternative layer of post-transcriptional gene regulatory networks. The competing endogenous RNA (ceRNA) regulation depicts the scenario where pairs of genes (ceRNAs) sharing, fully or partially, common binding miRNAs (miRNA program) can establish coexpression through competition for a limited pool of the miRNA program. While the dynamics of ceRNA regulation among cellular conditions have been verified based on in silico and in vitro experiments, comprehensive investigation into the strength of ceRNA regulation in human datasets remains largely unexplored. Furthermore, pan-cancer analysis of ceRNA regulation, to our knowledge, has not been systematically investigated. In the present study we explored optimal conditions for ceRNA regulation, investigated functions governed by ceRNA regulation, and evaluated pan-cancer effects. We started by investigating how essential factors, such as the size of miRNA programs, the number of miRNA program binding sites, and expression levels of miRNA programs and ceRNAs affect the ceRNA regulation capacity in tumors derived from glioblastoma multiforme patients captured by The Cancer Genome Atlas (TCGA). We demonstrated that increased numbers of common targeting miRNAs as well as the abundance of binding sites enhance ceRNA regulation and strengthen coexpression of ceRNA pairs. Also, our investigation revealed that the strength of ceRNA regulation is dependent on expression levels of both miRNA programs and ceRNAs. Through functional annotation analysis, our results indicated that ceRNA regulation is highly associated with essential cellular functions and diseases including cancer. Furthermore, the highly intertwined ceRNA regulatory relationship enables constitutive and effective intra-function regulation of genes in diverse types of cancer. Using gene and microRNA expression datasets from TCGA, we successfully

  8. EARLY DIAGNOSIS OF SKIN CANCER USING ARTIFICIAL NEURAL NETWORKS

    OpenAIRE

    Birajdar Yogesh; Rengaprabhu P

    2017-01-01

    The proposed work is to present an approach to easily detect the skin cancer and classify into benign and malignant classes differentiating with the wounds. The skin cancer occurs for many people in some regions of the countries like Australia & New Zealand where the sunlight is difficult to reach during winters. Thus the deficiency of Vitamin D causes skin cancer for the people dwelling in such regions. Self-assessment is being encouraged in such cities to detect the skin cancers in early st...

  9. Enhancing deep convolutional neural network scheme for breast cancer diagnosis with unlabeled data.

    Science.gov (United States)

    Sun, Wenqing; Tseng, Tzu-Liang Bill; Zhang, Jianying; Qian, Wei

    2017-04-01

    In this study we developed a graph based semi-supervised learning (SSL) scheme using deep convolutional neural network (CNN) for breast cancer diagnosis. CNN usually needs a large amount of labeled data for training and fine tuning the parameters, and our proposed scheme only requires a small portion of labeled data in training set. Four modules were included in the diagnosis system: data weighing, feature selection, dividing co-training data labeling, and CNN. 3158 region of interests (ROIs) with each containing a mass extracted from 1874 pairs of mammogram images were used for this study. Among them 100 ROIs were treated as labeled data while the rest were treated as unlabeled. The area under the curve (AUC) observed in our study was 0.8818, and the accuracy of CNN is 0.8243 using the mixed labeled and unlabeled data. Copyright © 2016. Published by Elsevier Ltd.

  10. Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival.

    Science.gov (United States)

    Megchelenbrink, Wout; Katzir, Rotem; Lu, Xiaowen; Ruppin, Eytan; Notebaart, Richard A

    2015-09-29

    Synthetic dosage lethality (SDL) denotes a genetic interaction between two genes whereby the underexpression of gene A combined with the overexpression of gene B is lethal. SDLs offer a promising way to kill cancer cells by inhibiting the activity of SDL partners of activated oncogenes in tumors, which are often difficult to target directly. As experimental genome-wide SDL screens are still scarce, here we introduce a network-level computational modeling framework that quantitatively predicts human SDLs in metabolism. For each enzyme pair (A, B) we systematically knock out the flux through A combined with a stepwise flux increase through B and search for pairs that reduce cellular growth more than when either enzyme is perturbed individually. The predictive signal of the emerging network of 12,000 SDLs is demonstrated in five different ways. (i) It can be successfully used to predict gene essentiality in shRNA cancer cell line screens. Moving to clinical tumors, we show that (ii) SDLs are significantly underrepresented in tumors. Furthermore, breast cancer tumors with SDLs active (iii) have smaller sizes and (iv) result in increased patient survival, indicating that activation of SDLs increases cancer vulnerability. Finally, (v) patient survival improves when multiple SDLs are present, pointing to a cumulative effect. This study lays the basis for quantitative identification of cancer SDLs in a model-based mechanistic manner. The approach presented can be used to identify SDLs in species and cell types in which "omics" data necessary for data-driven identification are missing.

  11. Constructing disease-specific gene networks using pair-wise relevance metric: Application to colon cancer identifies interleukin 8, desmin and enolase 1 as the central elements

    Directory of Open Access Journals (Sweden)

    Jiang Wei

    2008-08-01

    Full Text Available Abstract Background With the advance of large-scale omics technologies, it is now feasible to reversely engineer the underlying genetic networks that describe the complex interplays of molecular elements that lead to complex diseases. Current networking approaches are mainly focusing on building genetic networks at large without probing the interaction mechanisms specific to a physiological or disease condition. The aim of this study was thus to develop such a novel networking approach based on the relevance concept, which is ideal to reveal integrative effects of multiple genes in the underlying genetic circuit for complex diseases. Results The approach started with identification of multiple disease pathways, called a gene forest, in which the genes extracted from the decision forest constructed by supervised learning of the genome-wide transcriptional profiles for patients and normal samples. Based on the newly identified disease mechanisms, a novel pair-wise relevance metric, adjusted frequency value, was used to define the degree of genetic relationship between two molecular determinants. We applied the proposed method to analyze a publicly available microarray dataset for colon cancer. The results demonstrated that the colon cancer-specific gene network captured the most important genetic interactions in several cellular processes, such as proliferation, apoptosis, differentiation, mitogenesis and immunity, which are known to be pivotal for tumourigenesis. Further analysis of the topological architecture of the network identified three known hub cancer genes [interleukin 8 (IL8 (p ≈ 0, desmin (DES (p = 2.71 × 10-6 and enolase 1 (ENO1 (p = 4.19 × 10-5], while two novel hub genes [RNA binding motif protein 9 (RBM9 (p = 1.50 × 10-4 and ribosomal protein L30 (RPL30 (p = 1.50 × 10-4] may define new central elements in the gene network specific to colon cancer. Gene Ontology (GO based analysis of the colon cancer-specific gene network and

  12. Constructing disease-specific gene networks using pair-wise relevance metric: application to colon cancer identifies interleukin 8, desmin and enolase 1 as the central elements.

    Science.gov (United States)

    Jiang, Wei; Li, Xia; Rao, Shaoqi; Wang, Lihong; Du, Lei; Li, Chuanxing; Wu, Chao; Wang, Hongzhi; Wang, Yadong; Yang, Baofeng

    2008-08-10

    With the advance of large-scale omics technologies, it is now feasible to reversely engineer the underlying genetic networks that describe the complex interplays of molecular elements that lead to complex diseases. Current networking approaches are mainly focusing on building genetic networks at large without probing the interaction mechanisms specific to a physiological or disease condition. The aim of this study was thus to develop such a novel networking approach based on the relevance concept, which is ideal to reveal integrative effects of multiple genes in the underlying genetic circuit for complex diseases. The approach started with identification of multiple disease pathways, called a gene forest, in which the genes extracted from the decision forest constructed by supervised learning of the genome-wide transcriptional profiles for patients and normal samples. Based on the newly identified disease mechanisms, a novel pair-wise relevance metric, adjusted frequency value, was used to define the degree of genetic relationship between two molecular determinants. We applied the proposed method to analyze a publicly available microarray dataset for colon cancer. The results demonstrated that the colon cancer-specific gene network captured the most important genetic interactions in several cellular processes, such as proliferation, apoptosis, differentiation, mitogenesis and immunity, which are known to be pivotal for tumourigenesis. Further analysis of the topological architecture of the network identified three known hub cancer genes [interleukin 8 (IL8) (p approximately 0), desmin (DES) (p = 2.71 x 10(-6)) and enolase 1 (ENO1) (p = 4.19 x 10(-5))], while two novel hub genes [RNA binding motif protein 9 (RBM9) (p = 1.50 x 10(-4)) and ribosomal protein L30 (RPL30) (p = 1.50 x 10(-4))] may define new central elements in the gene network specific to colon cancer. Gene Ontology (GO) based analysis of the colon cancer-specific gene network and the sub-network that

  13. Artificial neural networks for processing fluorescence spectroscopy data in skin cancer diagnostics

    International Nuclear Information System (INIS)

    Lenhardt, L; Zeković, I; Dramićanin, T; Dramićanin, M D

    2013-01-01

    Over the years various optical spectroscopic techniques have been widely used as diagnostic tools in the discrimination of many types of malignant diseases. Recently, synchronous fluorescent spectroscopy (SFS) coupled with chemometrics has been applied in cancer diagnostics. The SFS method involves simultaneous scanning of both emission and excitation wavelengths while keeping the interval of wavelengths (constant-wavelength mode) or frequencies (constant-energy mode) between them constant. This method is fast, relatively inexpensive, sensitive and non-invasive. Total synchronous fluorescence spectra of normal skin, nevus and melanoma samples were used as input for training of artificial neural networks. Two different types of artificial neural networks were trained, the self-organizing map and the feed-forward neural network. Histopathology results of investigated skin samples were used as the gold standard for network output. Based on the obtained classification success rate of neural networks, we concluded that both networks provided high sensitivity with classification errors between 2 and 4%. (paper)

  14. Mapping the networks of cancer research in Portugal: first results

    Energy Technology Data Exchange (ETDEWEB)

    Bras, O.R.; Cointet, J.P.; Nunes, J.A.; David, L.; Cambrosio, A.

    2016-07-01

    Social studies of cancer research at the international level have contributed to a better understanding of the developmental dynamics – both organizational and epistemic – of this field (Keating & Cambrosio, 2012). In contrast, despite its robust development, oncology research in Portugal has been the subject of only few studies. Most of them have a strong focus on the first half of the 20th century (Raposo, 2004; Costa, 2010, 2012a; 2012b), while a few focus on more contemporary events (Nunes, 2001). Consequently, we do not have a clear picture of recent trends in oncology research in Portugal, and how it integrates into the international landscape. This hinders public accountability of oncology research while also limiting the analysis of how this research relates to health care delivery, health outcomes, and health policy formulations. This paper presents the first results of an ongoing research project on the organizational and epistemic development of oncology research in Portugal, covering the period from the end of the 20th century to 2015. Among other issues, we intend to explore the extent to which oncology research in Portugal mirrors the international dynamics at a smaller scale, and the extent to which it presents features of its own. The study draws upon computer-based analysis of publications using the platform CorText (http://www.cortext.net/) of IFRIS (Institut Francilien Recherche, Innovation, Société), along with interviews with Portuguese oncologists and related practitioners. (Author)

  15. Singapore Cancer Network (SCAN) Guidelines for Systemic Therapy of Pancreatic Adenocarcinoma.

    Science.gov (United States)

    2015-10-01

    The SCAN pancreatic cancer workgroup aimed to develop Singapore Cancer Network (SCAN) clinical practice guidelines for systemic therapy for pancreatic adenocarcinoma in Singapore. The workgroup utilised a modified ADAPTE process to calibrate high quality international evidence-based clinical practice guidelines to our local setting. Five international guidelines were evaluated- those developed by the National Cancer Comprehensive Network (2014), the European Society of Medical Oncology (2012), Cancer Care Ontario (2013), the Japan Pancreas Society (2013) and the British Society of Gastroenterology, Pancreatic Society of Great Britain and Ireland, and the Association of Upper Gastrointestinal Surgeons of Great Britain and Ireland (2005). Recommendations on the management of resected, borderline resectable, locally advanced and metastatic pancreatic adenocarcinoma were developed. These adapted guidelines form the SCAN Guidelines for systemic therapy for pancreatic adenocarcinoma in Singapore.

  16. A statistical framework for evaluating neural networks to predict recurrent events in breast cancer

    Science.gov (United States)

    Gorunescu, Florin; Gorunescu, Marina; El-Darzi, Elia; Gorunescu, Smaranda

    2010-07-01

    Breast cancer is the second leading cause of cancer deaths in women today. Sometimes, breast cancer can return after primary treatment. A medical diagnosis of recurrent cancer is often a more challenging task than the initial one. In this paper, we investigate the potential contribution of neural networks (NNs) to support health professionals in diagnosing such events. The NN algorithms are tested and applied to two different datasets. An extensive statistical analysis has been performed to verify our experiments. The results show that a simple network structure for both the multi-layer perceptron and radial basis function can produce equally good results, not all attributes are needed to train these algorithms and, finally, the classification performances of all algorithms are statistically robust. Moreover, we have shown that the best performing algorithm will strongly depend on the features of the datasets, and hence, there is not necessarily a single best classifier.

  17. I Keep my Problems to Myself: Negative Social Network Orientation, Social Resources, and Health-Related Quality of Life in Cancer Survivors

    Science.gov (United States)

    Symes, Yael; Campo, Rebecca A.; Wu, Lisa M.; Austin, Jane

    2016-01-01

    Background Cancer survivors treated with hematopoietic stem cell transplant rely on their social network for successful recovery. However, some survivors have negative attitudes about using social resources (negative social network orientation) that are critical for their recovery. Purpose We examined the association between survivors’ social network orientation and health-related quality of life (HRQoL) and whether it was mediated by social resources (network size, perceived support, and negative and positive support-related social exchanges). Methods In a longitudinal study, 255 survivors completed validated measures of social network orientation, HRQoL, and social resources. Hypotheses were tested using path analysis. Results More negative social network orientation predicted worse HRQoL (p social exchanges. Conclusions Survivors with negative social network orientation may have poorer HRQoL in part due to deficits in several key social resources. Findings highlight a subgroup at risk for poor transplant outcomes and can guide intervention development. PMID:26693932

  18. Mobile-ip Aeronautical Network Simulation Study

    Science.gov (United States)

    Ivancic, William D.; Tran, Diepchi T.

    2001-01-01

    NASA is interested in applying mobile Internet protocol (mobile-ip) technologies to its space and aeronautics programs. In particular, mobile-ip will play a major role in the Advanced Aeronautic Transportation Technology (AATT), the Weather Information Communication (WINCOMM), and the Small Aircraft Transportation System (SATS) aeronautics programs. This report presents the results of a simulation study of mobile-ip for an aeronautical network. The study was performed to determine the performance of the transmission control protocol (TCP) in a mobile-ip environment and to gain an understanding of how long delays, handoffs, and noisy channels affect mobile-ip performance.

  19. Artificial neural network applications in ionospheric studies

    Directory of Open Access Journals (Sweden)

    L. R. Cander

    1998-06-01

    Full Text Available The ionosphere of Earth exhibits considerable spatial changes and has large temporal variability of various timescales related to the mechanisms of creation, decay and transport of space ionospheric plasma. Many techniques for modelling electron density profiles through entire ionosphere have been developed in order to solve the "age-old problem" of ionospheric physics which has not yet been fully solved. A new way to address this problem is by applying artificial intelligence methodologies to current large amounts of solar-terrestrial and ionospheric data. It is the aim of this paper to show by the most recent examples that modern development of numerical models for ionospheric monthly median long-term prediction and daily hourly short-term forecasting may proceed successfully applying the artificial neural networks. The performance of these techniques is illustrated with different artificial neural networks developed to model and predict the temporal and spatial variations of ionospheric critical frequency, f0F2 and Total Electron Content (TEC. Comparisons between results obtained by the proposed approaches and measured f0F2 and TEC data provide prospects for future applications of the artificial neural networks in ionospheric studies.

  20. A network of networks model to study phase synchronization using structural connection matrix of human brain

    Science.gov (United States)

    Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.

    2018-04-01

    The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.

  1. Consuming Social Networks: A Study on BeeTalk Network

    Directory of Open Access Journals (Sweden)

    Jamal Mohammadi

    Full Text Available BeeTalk is one of the most common social networks that have attracted many users during these years. As a whole, social networks are parts of everyday life nowadays and, especially among the new generation, have caused some basic alterations in the field of identity-formation, sense-making and the form and content of communication. This article is a research about BeeTalk users, their virtual interactions and experiences, and the feelings, pleasures, meanings and attitudes that they obtain through participating in the virtual world. This is a qualitative research. The sample is selected by way of theoretical sampling among the students of University of Kurdistan. Direct observation and semistructured interviews are used to gathering data, which are interpreted through grounded theory. The findings show that some contexts like “searching real interests in a non-real world” and “the representation of users’ voices in virtual space” have provided the space for participating in BeeTalk, and an intervening factor called “instant availability” has intensified this participation. Users’ participation in this social network has changed their social interaction in the real world and formed some new types of communication among them such as “representation of faked identities”, “experiencing ceremonial space” and “artificial literacy”. Moreover, this participation has some consequences like “virtual addiction” and “virtual collectivism” in users’ everyday life that effects their ways of providing meaning and identity in their social lives. It can be said that the result of user’s activity in this network is to begin a kind of simulated relation that has basic differences with relations in the real world. The experience of relation in this network lacks nobility, enrichment and animation, rather it is instant, artificial and without any potential to vitalization.

  2. Usage of Probabilistic and General Regression Neural Network for Early Detection and Prevention of Oral Cancer

    OpenAIRE

    Sharma, Neha; Om, Hari

    2015-01-01

    In India, the oral cancers are usually presented in advanced stage of malignancy. It is critical to ascertain the diagnosis in order to initiate most advantageous treatment of the suspicious lesions. The main hurdle in appropriate treatment and control of oral cancer is identification and risk assessment of early disease in the community in a cost-effective fashion. The objective of this research is to design a data mining model using probabilistic neural network and general regression neural...

  3. Bayesian network modelling on data from fine needle aspiration cytology examination for breast cancer diagnosis

    OpenAIRE

    Ding, Xuemei; Cao, Yi; Zhai, Jia; Maguire, Liam; Li, Yuhua; Yang, Hongqin; Wang, Yuhua; Zeng, Jinshu; Liu, Shuo

    2017-01-01

    The paper employed Bayesian network (BN) modelling approach to discover causal dependencies among different data features of Breast Cancer Wisconsin Dataset (BCWD) derived from openly sourced UCI repository. K2 learning algorithm and k-fold cross validation were used to construct and optimize BN structure. Compared to Na‹ve Bayes (NB), the obtained BN presented better performance for breast cancer diagnosis based on fine needle aspiration cytology (FNAC) examination. It also showed that, amon...

  4. Assessing needs and assets for building a regional network infrastructure to reduce cancer related health disparities.

    Science.gov (United States)

    Wells, Kristen J; Lima, Diana S; Meade, Cathy D; Muñoz-Antonia, Teresita; Scarinci, Isabel; McGuire, Allison; Gwede, Clement K; Pledger, W Jack; Partridge, Edward; Lipscomb, Joseph; Matthews, Roland; Matta, Jaime; Flores, Idhaliz; Weiner, Roy; Turner, Timothy; Miele, Lucio; Wiese, Thomas E; Fouad, Mona; Moreno, Carlos S; Lacey, Michelle; Christie, Debra W; Price-Haywood, Eboni G; Quinn, Gwendolyn P; Coppola, Domenico; Sodeke, Stephen O; Green, B Lee; Lichtveld, Maureen Y

    2014-06-01

    Significant cancer health disparities exist in the United States and Puerto Rico. While numerous initiatives have been implemented to reduce cancer disparities, regional coordination of these efforts between institutions is often limited. To address cancer health disparities nation-wide, a series of regional transdisciplinary networks through the Geographic Management Program (GMaP) and the Minority Biospecimen/Biobanking Geographic Management Program (BMaP) were established in six regions across the country. This paper describes the development of the Region 3 GMaP/BMaP network composed of over 100 investigators from nine institutions in five Southeastern states and Puerto Rico to develop a state-of-the-art network for cancer health disparities research and training. We describe a series of partnership activities that led to the formation of the infrastructure for this network, recount the participatory processes utilized to develop and implement a needs and assets assessment and implementation plan, and describe our approach to data collection. Completion, by all nine institutions, of the needs and assets assessment resulted in several beneficial outcomes for Region 3 GMaP/BMaP. This network entails ongoing commitment from the institutions and institutional leaders, continuous participatory and engagement activities, and effective coordination and communication centered on team science goals. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Assessing Needs and Assets for Building a Regional Network Infrastructure to Reduce Cancer Related Health Disparities

    Science.gov (United States)

    Wells, Kristen J.; Lima, Diana S.; Meade, Cathy D.; Muñoz-Antonia, Teresita; Scarinci, Isabel; McGuire, Allison; Gwede, Clement K.; Pledger, W. Jack; Partridge, Edward; Lipscomb, Joseph; Matthews, Roland; Matta, Jaime; Flores, Idhaliz; Weiner, Roy; Turner, Timothy; Miele, Lucio; Wiese, Thomas E.; Fouad, Mona; Moreno, Carlos S.; Lacey, Michelle; Christie, Debra W.; Price-Haywood, Eboni G.; Quinn, Gwendolyn P.; Coppola, Domenico; Sodeke, Stephen O.; Green, B. Lee; Lichtveld, Maureen Y.

    2015-01-01

    Significant cancer health disparities exist in the United States and Puerto Rico. While numerous initiatives have been implemented to reduce cancer disparities, regional coordination of these efforts between institutions is often limited. To address cancer health disparities nationwide, a series of regional transdisciplinary networks through the Geographic Management Program (GMaP) and the Minority Biospecimen/Biobanking Geographic Management Program (BMaP) were established in six regions across the country. This paper describes the development of the Region 3 GMaP/BMaP network composed of over 100 investigators from nine institutions in five Southeastern states and Puerto Rico to develop a state-of-the-art network for cancer health disparities research and training. We describe a series of partnership activities that led to the formation of the infrastructure for this network, recount the participatory processes utilized to develop and implement a needs and assets assessment and implementation plan, and describe our approach to data collection. Completion, by all nine institutions, of the needs and assets assessment resulted in several beneficial outcomes for Region 3 GMaP/BMaP. This network entails ongoing commitment from the institutions and institutional leaders, continuous participatory and engagement activities, and effective coordination and communication centered on team science goals. PMID:24486917

  6. Podoplanin increases the migration of human fibroblasts and affects the endothelial cell network formation: A possible role for cancer-associated fibroblasts in breast cancer progression.

    Directory of Open Access Journals (Sweden)

    Jaroslaw Suchanski

    Full Text Available In our previous studies we showed that in breast cancer podoplanin-positive cancer-associated fibroblasts correlated positively with tumor size, grade of malignancy, lymph node metastasis, lymphovascular invasion and poor patients' outcome. Therefore, the present study was undertaken to assess if podoplanin expressed by fibroblasts can affect malignancy-associated properties of breast cancer cells. Human fibroblastic cell lines (MSU1.1 and Hs 578Bst overexpressing podoplanin and control fibroblasts were co-cultured with breast cancer MDA-MB-231 and MCF7 cells and the impact of podoplanin expressed by fibroblasts on migration and invasiveness of breast cancer cells were studied in vitro. Migratory and invasive properties of breast cancer cells were not affected by the presence of podoplanin on the surface of fibroblasts. However, ectopic expression of podoplanin highly increases the migration of MSU1.1 and Hs 578Bst fibroblasts. The present study also revealed for the first time, that podoplanin expression affects the formation of pseudo tubes by endothelial cells. When human HSkMEC cells were co-cultured with podoplanin-rich fibroblasts the endothelial cell capillary-like network was characterized by significantly lower numbers of nodes and meshes than in co-cultures of endothelial cells with podoplanin-negative fibroblasts. The question remains as to how our experimental data can be correlated with previous clinical data showing an association between the presence of podoplanin-positive cancer-associated fibroblasts and progression of breast cancer. Therefore, we propose that expression of podoplanin by fibroblasts facilitates their movement into the tumor stroma, which creates a favorable microenvironment for tumor progression by increasing the number of cancer-associated fibroblasts, which produce numerous factors affecting proliferation, survival and invasion of cancer cells. In accordance with this, the present study revealed for the first

  7. Podoplanin increases the migration of human fibroblasts and affects the endothelial cell network formation: A possible role for cancer-associated fibroblasts in breast cancer progression.

    Science.gov (United States)

    Suchanski, Jaroslaw; Tejchman, Anna; Zacharski, Maciej; Piotrowska, Aleksandra; Grzegrzolka, Jedrzej; Chodaczek, Grzegorz; Nowinska, Katarzyna; Rys, Janusz; Dziegiel, Piotr; Kieda, Claudine; Ugorski, Maciej

    2017-01-01

    In our previous studies we showed that in breast cancer podoplanin-positive cancer-associated fibroblasts correlated positively with tumor size, grade of malignancy, lymph node metastasis, lymphovascular invasion and poor patients' outcome. Therefore, the present study was undertaken to assess if podoplanin expressed by fibroblasts can affect malignancy-associated properties of breast cancer cells. Human fibroblastic cell lines (MSU1.1 and Hs 578Bst) overexpressing podoplanin and control fibroblasts were co-cultured with breast cancer MDA-MB-231 and MCF7 cells and the impact of podoplanin expressed by fibroblasts on migration and invasiveness of breast cancer cells were studied in vitro. Migratory and invasive properties of breast cancer cells were not affected by the presence of podoplanin on the surface of fibroblasts. However, ectopic expression of podoplanin highly increases the migration of MSU1.1 and Hs 578Bst fibroblasts. The present study also revealed for the first time, that podoplanin expression affects the formation of pseudo tubes by endothelial cells. When human HSkMEC cells were co-cultured with podoplanin-rich fibroblasts the endothelial cell capillary-like network was characterized by significantly lower numbers of nodes and meshes than in co-cultures of endothelial cells with podoplanin-negative fibroblasts. The question remains as to how our experimental data can be correlated with previous clinical data showing an association between the presence of podoplanin-positive cancer-associated fibroblasts and progression of breast cancer. Therefore, we propose that expression of podoplanin by fibroblasts facilitates their movement into the tumor stroma, which creates a favorable microenvironment for tumor progression by increasing the number of cancer-associated fibroblasts, which produce numerous factors affecting proliferation, survival and invasion of cancer cells. In accordance with this, the present study revealed for the first time, that such

  8. A new focus for the International Cancer Screening Network

    Science.gov (United States)

    The ICSN is thinking about how to take advantage of the nearly three decades of work in cancer screening program research and implementation and reach out more actively to low- and middle-income countries considering screening. For that purpose, ICSN is migrating from its historical place under NCI Division of Cancer Control and Population Sciences to assume its new role within the Center for Global Health.

  9. Establishment of the Fox Chase Network Breast Cancer Risk Registry

    Science.gov (United States)

    1996-10-01

    related to caner also are d ed. breast cancer. Participants learn about screening guidelines and prevention options. The Cancer Center Eligibility...ever treated with a series of x-rays to the front of your neck for acne, neck tumor or any other reason? (This does not include routine screening x-rays...hysterectomy (surgical removal of the uterus )? 10] Yes CONTINUE 20 No CONTINUE 80 Don’t know CONTINUE a. If yes, how old were you? (-) years 10. Have

  10. An integrative analysis of cellular contexts, miRNAs and mRNAs reveals network clusters associated with antiestrogen-resistant breast cancer cells

    Directory of Open Access Journals (Sweden)

    Nam Seungyoon

    2012-12-01

    Full Text Available Abstract Background A major goal of the field of systems biology is to translate genome-wide profiling data (e.g., mRNAs, miRNAs into interpretable functional networks. However, employing a systems biology approach to better understand the complexities underlying drug resistance phenotypes in cancer continues to represent a significant challenge to the field. Previously, we derived two drug-resistant breast cancer sublines (tamoxifen- and fulvestrant-resistant cell lines from the MCF7 breast cancer cell line and performed genome-wide mRNA and microRNA profiling to identify differential molecular pathways underlying acquired resistance to these important antiestrogens. In the current study, to further define molecular characteristics of acquired antiestrogen resistance we constructed an “integrative network”. We combined joint miRNA-mRNA expression profiles, cancer contexts, miRNA-target mRNA relationships, and miRNA upstream regulators. In particular, to reduce the probability of false positive connections in the network, experimentally validated, rather than prediction-oriented, databases were utilized to obtain connectivity. Also, to improve biological interpretation, cancer contexts were incorporated into the network connectivity. Results Based on the integrative network, we extracted “substructures” (network clusters representing the drug resistant states (tamoxifen- or fulvestrant-resistance cells compared to drug sensitive state (parental MCF7 cells. We identified un-described network clusters that contribute to antiestrogen resistance consisting of miR-146a, -27a, -145, -21, -155, -15a, -125b, and let-7s, in addition to the previously described miR-221/222. Conclusions By integrating miRNA-related network, gene/miRNA expression and text-mining, the current study provides a computational-based systems biology approach for further investigating the molecular mechanism underlying antiestrogen resistance in breast cancer cells. In

  11. Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

    Science.gov (United States)

    Li, Cheng-Wei; Chen, Bor-Sen

    2016-01-01

    Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.

  12. A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types

    Science.gov (United States)

    Lin, Chen-Ching; Zhao, Junfei; Jia, Peilin; Li, Wen-Hsiung; Zhao, Zhongming

    2015-01-01

    Cancer development and progression result from somatic evolution by an accumulation of genomic alterations. The effects of those alterations on the fitness of somatic cells lead to evolutionary adaptations such as increased cell proliferation, angiogenesis, and altered anticancer drug responses. However, there are few general mathematical models to quantitatively examine how perturbations of a single gene shape subsequent evolution of the cancer genome. In this study, we proposed the gene gravity model to study the evolution of cancer genomes by incorporating the genome-wide transcription and somatic mutation profiles of ~3,000 tumors across 9 cancer types from The Cancer Genome Atlas into a broad gene network. We found that somatic mutations of a cancer driver gene may drive cancer genome evolution by inducing mutations in other genes. This functional consequence is often generated by the combined effect of genetic and epigenetic (e.g., chromatin regulation) alterations. By quantifying cancer genome evolution using the gene gravity model, we identified six putative cancer genes (AHNAK, COL11A1, DDX3X, FAT4, STAG2, and SYNE1). The tumor genomes harboring the nonsynonymous somatic mutations in these genes had a higher mutation density at the genome level compared to the wild-type groups. Furthermore, we provided statistical evidence that hypermutation of cancer driver genes on inactive X chromosomes is a general feature in female cancer genomes. In summary, this study sheds light on the functional consequences and evolutionary characteristics of somatic mutations during tumorigenesis by propelling adaptive cancer genome evolution, which would provide new perspectives for cancer research and therapeutics. PMID:26352260

  13. Quality assurance network: The European pilot study

    International Nuclear Information System (INIS)

    Chavaudra, J.; Derreumaux, S.; Brider, A.

    1996-01-01

    Based on the IAEA/WHO experience in mailed dosimetry, a Quality Assurance (QA) Network, sponsored by the EC committee ''Europe against Cancer'', has been set up in 1991 for all European centres. Besides a survey of radiotherapy infrastructure, the project includes three measurement steps: primarily, a check of beam output and quality in reference conditions with a mailed TLD-procedure, in a second step, the mailed verification of other beam data and dose calculation procedures with multipurpose phantom, and finally in vivo dosimetry at the individual patient levels with mailed dosimeters. The results concerning 162 beams from 85 centres are analysed (58 60 Co beams and 104 X-ray beams). 27 beams present minor deviations (3 to 6%) and 15 beams (4/58 60 Co beams and 11/104 X-ray beams) from 11 centres present major deviations (≥ 6%). The analysis shows that 17/27 minor deviations and all major deviations have been detected in centres which have not benefited from an external check during the last five years; in 14 out of 15 large deviations, the measured dose is smaller than the stated dose. In most centres with major deviation, the physicists did not have the necessary experience and did not calibrate regularly the beams. In 6 centres out of 11 there was no dosimeter or the dosimeter available has not been calibrated recently. In 3 centres, the physicist did not give any explanations. The conclusions concerning the second step (multipurpose phantom), outline the larger magnitude of the deviations for off axis points, oblique surface and the use of wedge filters. (author). 32 refs, 7 figs, 2 tabs

  14. Quality assurance network: The European pilot study

    Energy Technology Data Exchange (ETDEWEB)

    Chavaudra, J; Derreumaux, S; Brider, A [Institut Gustave Roussa, Villejuif (France). Service de Physique; Dutreix, A; Schueren, E van der [University Hospital, Leuven (Belgium)

    1996-08-01

    Based on the IAEA/WHO experience in mailed dosimetry, a Quality Assurance (QA) Network, sponsored by the EC committee ``Europe against Cancer``, has been set up in 1991 for all European centres. Besides a survey of radiotherapy infrastructure, the project includes three measurement steps: primarily, a check of beam output and quality in reference conditions with a mailed TLD-procedure, in a second step, the mailed verification of other beam data and dose calculation procedures with multipurpose phantom, and finally in vivo dosimetry at the individual patient levels with mailed dosimeters. The results concerning 162 beams from 85 centres are analysed (58 {sup 60}Co beams and 104 X-ray beams). 27 beams present minor deviations (3 to 6%) and 15 beams (4/58 {sup 60}Co beams and 11/104 X-ray beams) from 11 centres present major deviations ({>=} 6%). The analysis shows that 17/27 minor deviations and all major deviations have been detected in centres which have not benefited from an external check during the last five years; in 14 out of 15 large deviations, the measured dose is smaller than the stated dose. In most centres with major deviation, the physicists did not have the necessary experience and did not calibrate regularly the beams. In 6 centres out of 11 there was no dosimeter or the dosimeter available has not been calibrated recently. In 3 centres, the physicist did not give any explanations. The conclusions concerning the second step (multipurpose phantom), outline the larger magnitude of the deviations for off axis points, oblique surface and the use of wedge filters. (author). 32 refs, 7 figs, 2 tabs.

  15. The updated network meta-analysis of neoadjuvant therapy for HER2-positive breast cancer.

    Science.gov (United States)

    Nakashoji, Ayako; Hayashida, Tetsu; Yokoe, Takamichi; Maeda, Hinako; Toyota, Tomoka; Kikuchi, Masayuki; Watanuki, Rurina; Nagayama, Aiko; Seki, Tomoko; Takahashi, Maiko; Abe, Takayuki; Kitagawa, Yuko

    2018-01-01

    We previously described a systematic assessment of the neoadjuvant therapies for human epidermal growth factor receptor-2 (HER2) positive breast cancer, using network meta-analysis. Accumulation of new clinical data has compelled us to update the analysis. Randomized trials comparing different anti-HER2 regimens in the neoadjuvant setting were included, and odds ratio for pathologic complete response (pCR) in seven treatment arms were assessed by pooling effect sizes. Direct and indirect comparisons using a Bayesian statistical model were performed. All statistical tests were two-sided. A database search identified 993 articles with 13 studies meeting the eligibility criteria, including three new studies with lapatinib (lpnb). In an indirect comparison, dual anti-HER2 agents with CT achieved a better pCR rate than other arms. The credibility intervals of CT + tzmb + lpnb arm were largely reduced compared to our former report, which we added sufficient clinical evidence by this update. Values of surface under the cumulative ranking (SUCRA) suggested that CT + tzmb + pzmb had the highest probability of being the best treatment arm for pCR, widening the difference between the top two dual-HER2 blockade arms compared to our former report. The overall consistency with our first report enhanced the credibility of the results. Network meta-analysis using new clinical data firmly establish that combining two anti-HER2 agents with CT is most effective against HER2-positive breast cancer in the neoadjuvant setting. New pzmb related trials are required to fully determine the best neoadjuvant dual-HER2 blockade regimen. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Network analysis of ChIP-Seq data reveals key genes in prostate cancer.

    Science.gov (United States)

    Zhang, Yu; Huang, Zhen; Zhu, Zhiqiang; Liu, Jianwei; Zheng, Xin; Zhang, Yuhai

    2014-09-03

    Prostate cancer (PC) is the second most common cancer among men in the United States, and it imposes a considerable threat to human health. A deep understanding of its underlying molecular mechanisms is the premise for developing effective targeted therapies. Recently, deep transcriptional sequencing has been used as an effective genomic assay to obtain insights into diseases and may be helpful in the study of PC. In present study, ChIP-Seq data for PC and normal samples were compared, and differential peaks identified, based upon fold changes (with P-values calculated with t-tests). Annotations of these peaks were performed. Protein-protein interaction (PPI) network analysis was performed with BioGRID and constructed with Cytoscape, following which the highly connected genes were screened. We obtained a total of 5,570 differential peaks, including 3,726 differentially enriched peaks in tumor samples and 1,844 differentially enriched peaks in normal samples. There were eight significant regions of the peaks. The intergenic region possessed the highest score (51%), followed by intronic (31%) and exonic (11%) regions. The analysis revealed the top 35 highly connected genes, which comprised 33 differential genes (such as YWHAQ, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein and θ polypeptide) from ChIP-Seq data and 2 differential genes retrieved from the PPI network: UBA52 (ubiquitin A-52 residue ribosomal protein fusion product (1) and SUMO2 (SMT3 suppressor of mif two 3 homolog (2) . Our findings regarding potential PC-related genes increase the understanding of PC and provides direction for future research.

  17. A Prescription for Internet Access: Appealing to Middle-Aged and Older Racial and Ethnic Minorities Through Social Network Sites to Combat Colorectal Cancer.

    Science.gov (United States)

    Lumpkins, Crystal Y; Mabachi, Natabhona; Lee, Jaehoon; Pacheco, Christina; Greiner, K Allen; Geana, Mugur

    2017-07-01

    The popularity and usage of social media networks or SNS (social networking sites) among American Internet users age 50 and over doubled between 2009 and 2010 and has steadily climbed. Part of this increased access may be the result of older adults who are living with a chronic disease and are reaching out for online support. Colorectal cancer (CRC) risk is among those concerns, particularly among middle-age and older minority populations where disparities exist. This exploratory study investigates information seeking behavior related to cancer factors (e.g. testing for colon cancer, cancer fatalism) and current social media usage among racial and ethnic minority groups (African American and Latinos) and Whites age 50 and older. The secondary data from the 2012 Health Information National Trends Survey (HINTS) was analyzed to compare these populations. Results show that African Americans and Latinos were only slightly more likely to use social network sites to seek out cancer information compared to Whites. However, Whites were more likely to use the Internet to seek health information compared to African Americans and Latinos. In this sample, Whites were also more likely to be informed by a physician about CRC testing (p social media networks, Internet sites) have increased among older Americans and can serve as critical channels for cancer information and education.

  18. Vietnamese American women’s beliefs and perceptions on cervical cancer, cervical cancer screening, and cancer prevention vaccines: A community-based participatory study

    Directory of Open Access Journals (Sweden)

    Connie Kim Yen Nguyen-Truong

    2017-12-01

    Full Text Available Cervical cancer remains commonly diagnosed in Vietnamese American women. Despite efforts to increase cervical cancer screening among Vietnamese American women, participation rates are persistently lower than the national goal. The objective of this study is to explore beliefs of Vietnamese American women about cervical cancer, cervical cancer screening, and cancer prevention vaccines. A qualitative descriptive investigation captured group perceptions about meaning and beliefs of cervical cancer, screening, and cancer prevention vaccines, and participants’ stories using a community-based participatory research approach. Forty Vietnamese American women were recruited from the Portland, Oregon metropolitan area into four focus groups. Using a process of directed content analysis, focus group transcripts were coded for themes. We found that cervical cancer continues to be a difficult topic to discuss, and Vietnamese American women may not bring the topic up themselves to their health care providers. Some women experienced intense emotions of fear or shame of having their cervix examined. Women delayed seeking cervical cancer screening and needed to have early warning signs, which guided them as to when to seek health care. Women focused on cleanliness through vaginal and/or perineal washing as primary prevention for cervical cancer. There were limited awareness and knowledge about cancer prevention vaccines, specifically the human papillomavirus. Some women relied heavily on their informal social networks of family, friends, or community for health knowledge. Fear and misunderstanding dominated the beliefs of Vietnamese American women about cervical cancer screening and prevention. These findings underscored the importance of having culturally-specific findings, which will inform a multicomponent intervention to promote cervical cancer screening and cancer prevention vaccine uptake within this population.

  19. Kinome-wide Decoding of Network-Attacking Mutations Rewiring Cancer Signaling

    DEFF Research Database (Denmark)

    Creixell, Pau; Schoof, Erwin M; Simpson, Craig D.

    2015-01-01

    Cancer cells acquire pathological phenotypes through accumulation of mutations that perturb signaling networks. However, global analysis of these events is currently limited. Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network...... and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome. We discover mutant molecular logic gates, a drift toward phospho-threonine signaling, weakening of phosphorylation motifs, and kinase...

  20. Assessing the effect of quantitative and qualitative predictors on gastric cancer individuals survival using hierarchical artificial neural network models.

    Science.gov (United States)

    Amiri, Zohreh; Mohammad, Kazem; Mahmoudi, Mahmood; Parsaeian, Mahbubeh; Zeraati, Hojjat

    2013-01-01

    There are numerous unanswered questions in the application of artificial neural network models for analysis of survival data. In most studies, independent variables have been studied as qualitative dichotomous variables, and results of using discrete and continuous quantitative, ordinal, or multinomial categorical predictive variables in these models are not well understood in comparison to conventional models. This study was designed and conducted to examine the application of these models in order to determine the survival of gastric cancer patients, in comparison to the Cox proportional hazards model. We studied the postoperative survival of 330 gastric cancer patients who suffered surgery at a surgical unit of the Iran Cancer Institute over a five-year period. Covariates of age, gender, history of substance abuse, cancer site, type of pathology, presence of metastasis, stage, and number of complementary treatments were entered in the models, and survival probabilities were calculated at 6, 12, 18, 24, 36, 48, and 60 months using the Cox proportional hazards and neural network models. We estimated coefficients of the Cox model and the weights in the neural network (with 3, 5, and 7 nodes in the hidden layer) in the training group, and used them to derive predictions in the study group. Predictions with these two methods were compared with those of the Kaplan-Meier product limit estimator as the gold standard. Comparisons were performed with the Friedman and Kruskal-Wallis tests. Survival probabilities at different times were determined using the Cox proportional hazards and a neural network with three nodes in the hidden layer; the ratios of standard errors with these two methods to the Kaplan-Meier method were 1.1593 and 1.0071, respectively, revealed a significant difference between Cox and Kaplan-Meier (P neural network, and the neural network and the standard (Kaplan-Meier), as well as better accuracy for the neural network (with 3 nodes in the hidden layer

  1. Wisconsin’s Environmental Public Health Tracking Network: Information Systems Design for Childhood Cancer Surveillance

    Science.gov (United States)

    Hanrahan, Lawrence P.; Anderson, Henry A.; Busby, Brian; Bekkedal, Marni; Sieger, Thomas; Stephenson, Laura; Knobeloch, Lynda; Werner, Mark; Imm, Pamela; Olson, Joseph

    2004-01-01

    In this article we describe the development of an information system for environmental childhood cancer surveillance. The Wisconsin Cancer Registry annually receives more than 25,000 incident case reports. Approximately 269 cases per year involve children. Over time, there has been considerable community interest in understanding the role the environment plays as a cause of these cancer cases. Wisconsin’s Public Health Information Network (WI-PHIN) is a robust web portal integrating both Health Alert Network and National Electronic Disease Surveillance System components. WI-PHIN is the information technology platform for all public health surveillance programs. Functions include the secure, automated exchange of cancer case data between public health–based and hospital-based cancer registrars; web-based supplemental data entry for environmental exposure confirmation and hypothesis testing; automated data analysis, visualization, and exposure–outcome record linkage; directories of public health and clinical personnel for role-based access control of sensitive surveillance information; public health information dissemination and alerting; and information technology security and critical infrastructure protection. For hypothesis generation, cancer case data are sent electronically to WI-PHIN and populate the integrated data repository. Environmental data are linked and the exposure–disease relationships are explored using statistical tools for ecologic exposure risk assessment. For hypothesis testing, case–control interviews collect exposure histories, including parental employment and residential histories. This information technology approach can thus serve as the basis for building a comprehensive system to assess environmental cancer etiology. PMID:15471739

  2. Do governance choices matter in health care networks?: an exploratory configuration study of health care networks

    Science.gov (United States)

    2013-01-01

    Background Health care networks are widely used and accepted as an organizational form that enables integrated care as well as dealing with complex matters in health care. However, research on the governance of health care networks lags behind. The research aim of our study is to explore the type and importance of governance structure and governance mechanisms for network effectiveness. Methods The study has a multiple case study design and covers 22 health care networks. Using a configuration view, combinations of network governance and other network characteristics were studied on the level of the network. Based on interview and questionnaire data, network characteristics were identified and patterns in the data looked for. Results Neither a dominant (or optimal) governance structure or mechanism nor a perfect fit among governance and other characteristics were revealed, but a number of characteristics that need further study might be related to effective networks such as the role of governmental agencies, legitimacy, and relational, hierarchical, and contractual governance mechanisms as complementary factors. Conclusions Although the results emphasize the situational character of network governance and effectiveness, they give practitioners in the health care sector indications of which factors might be more or less crucial for network effectiveness. PMID:23800334

  3. The Cervix Cancer Research Network (CCRN: Increasing access to cancer clinical trials in low- and middle-income countries

    Directory of Open Access Journals (Sweden)

    Gita eSuneja

    2015-02-01

    Full Text Available Introduction: The burden of cervical cancer is large and growing in developing countries, due in large part to limited access to screening services and lack of human papillomavirus (HPV vaccination. In spite of modern advances in diagnostic and therapeutic modalities, outcomes from cervical cancer have not markedly improved in recent years. Novel clinical trials are urgently needed to improve outcomes from cervical cancer worldwide. Methods: The Cervix Cancer Research Network (CCRN, a subsidiary of the Gynecologic Cancer InterGroup (GCIG, is a multi-national, multi-institutional consortium of physicians and scientists focused on improving cervical cancer outcomes worldwide by making cancer clinical trials available in low-, middle-, and high-income countries. Standard operating procedures for participation in CCRN include a pre-qualifying questionnaire to evaluate clinical activities and research infrastructure, followed by a site visit. Once a site is approved, they may choose to participate in one of four currently accruing clinical trials.Results: To date, 13 different CCRN site visits have been performed. Of these 13 sites visited, 10 have been approved as CCRN sites including Tata Memorial Hospital, India; Bangalore, India; Trivandrum, India; Ramathibodi, Thailand; Siriaj, Thailand; Pramongkutklao, Thailand; Ho Chi Minh, Vietnam; Blokhin Russian Cancer Research Center; the Hertzen Moscow Cancer Research Institute; and the Russian Scientific Center of Roentgenoradiology. The four currently accruing clinical trials are TACO, OUTBACK, INTERLACE, and SHAPE.Discussion: The CCRN has successfully enrolled 10 sites in developing countries to participate in four randomized clinical trials. The primary objectives are to provide novel therapeutics to regions with the greatest need and to improve the validity and generalizability of clinical trial results by enrolling a diverse sample of patients.

  4. Inference of Cancer-specific Gene Regulatory Networks Using Soft Computing Rules

    Directory of Open Access Journals (Sweden)

    Xiaosheng Wang

    2010-03-01

    Full Text Available Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

  5. A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer

    NARCIS (Netherlands)

    C. Staiger (Christine); S. Cadot; R Kooter; M. Dittrich (Marcus); T. Müller (Tobias); G.W. Klau (Gunnar); L.F.A. Wessels (Lodewyk)

    2012-01-01

    htmlabstractRecently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically

  6. Artificial neural network analysis to assess hypernasality in patients treated for oral or oropharyngeal cancer

    NARCIS (Netherlands)

    de Bruijn, Marieke; ten Bosch, Louis; Kuik, Dirk J.; Langendijk, Johannes A.; Leemans, C. Rene; Verdonck-de Leeuw, Irma

    2011-01-01

    Objective. Investigation of applicability of neural network feature analysis of nasalance in speech to assess hypernasality in speech of patients treated for oral or oropharyngeal cancer. Patients and methods. Speech recordings of 51 patients and of 18 control speakers were evaluated regarding

  7. FERAL : Network-based classifier with application to breast cancer outcome prediction

    NARCIS (Netherlands)

    Allahyar, A.; De Ridder, J.

    2015-01-01

    Motivation: Breast cancer outcome prediction based on gene expression profiles is an important strategy for personalize patient care. To improve performance and consistency of discovered markers of the initial molecular classifiers, network-based outcome prediction methods (NOPs) have been proposed.

  8. Inference of cancer-specific gene regulatory networks using soft computing rules.

    Science.gov (United States)

    Wang, Xiaosheng; Gotoh, Osamu

    2010-03-24

    Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

  9. Integration of protein phosphorylation, acetylation, and methylation data sets to outline lung cancer signaling networks.

    Science.gov (United States)

    Grimes, Mark; Hall, Benjamin; Foltz, Lauren; Levy, Tyler; Rikova, Klarisa; Gaiser, Jeremiah; Cook, William; Smirnova, Ekaterina; Wheeler, Travis; Clark, Neil R; Lachmann, Alexander; Zhang, Bin; Hornbeck, Peter; Ma'ayan, Avi; Comb, Michael

    2018-05-22

    Protein posttranslational modifications (PTMs) have typically been studied independently, yet many proteins are modified by more than one PTM type, and cell signaling pathways somehow integrate this information. We coupled immunoprecipitation using PTM-specific antibodies with tandem mass tag (TMT) mass spectrometry to simultaneously examine phosphorylation, methylation, and acetylation in 45 lung cancer cell lines compared to normal lung tissue and to cell lines treated with anticancer drugs. This simultaneous, large-scale, integrative analysis of these PTMs using a cluster-filtered network (CFN) approach revealed that cell signaling pathways were outlined by clustering patterns in PTMs. We used the t-distributed stochastic neighbor embedding (t-SNE) method to identify PTM clusters and then integrated each with known protein-protein interactions (PPIs) to elucidate functional cell signaling pathways. The CFN identified known and previously unknown cell signaling pathways in lung cancer cells that were not present in normal lung epithelial tissue. In various proteins modified by more than one type of PTM, the incidence of those PTMs exhibited inverse relationships, suggesting that molecular exclusive "OR" gates determine a large number of signal transduction events. We also showed that the acetyltransferase EP300 appears to be a hub in the network of pathways involving different PTMs. In addition, the data shed light on the mechanism of action of geldanamycin, an HSP90 inhibitor. Together, the findings reveal that cell signaling pathways mediated by acetylation, methylation, and phosphorylation regulate the cytoskeleton, membrane traffic, and RNA binding protein-mediated control of gene expression. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  10. Surrogate for oropharyngeal cancer HPV status in cancer database studies.

    Science.gov (United States)

    Megwalu, Uchechukwu C; Chen, Michelle M; Ma, Yifei; Divi, Vasu

    2017-12-01

    The utility of cancer databases for oropharyngeal cancer studies is limited by lack of information on human papillomavirus (HPV) status. The purpose of this study was to develop a surrogate that can be used to adjust for the effect of HPV status on survival. The study cohort included 6419 patients diagnosed with oropharyngeal squamous cell carcinoma between 2004 and 2012, identified in the National Cancer Database (NCDB). The HPV surrogate score was developed using a logistic regression model predicting HPV-positive status. The HPV surrogate score was predictive of HPV status (area under the curve [AUC] 0.73; accuracy of 70.4%). Similar to HPV-positive tumors, HPV surrogate positive tumors were associated with improved overall survival (OS; hazard ratio [HR] 0.73; 95% confidence interval [CI] 0.59-0.91; P = .005), after adjusting for important covariates. The HPV surrogate score is useful for adjusting for the effect of HPV status on survival in studies utilizing cancer databases. © 2017 Wiley Periodicals, Inc.

  11. NETWORK SECURITY ATTACKS. ARP POISONING CASE STUDY

    Directory of Open Access Journals (Sweden)

    Luminiţa DEFTA

    2010-12-01

    Full Text Available Arp poisoning is one of the most common attacks in a switched network. A switch is a network device that limits the ability of attackers that use a packet sniffer to gain access to information from internal network traffic. However, using ARP poisoning the traffic between two computers can be intercepted even in a network that uses switches. This method is known as man in the middle attack. With this type of attack the affected stations from a network will have invalid entries in the ARP table. Thus, it will contain only the correspondence between the IP addresses of the stations from the same network and a single MAC address (the station that initiated the attack. In this paper we present step by step the initiation of such an attack in a network with three computers. We will intercept the traffic between two stations using the third one (the attacker.

  12. Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

    Science.gov (United States)

    Singh, Garima; Roy, Jyoti; Rout, Pratiti; Mallick, Bibekanand

    2018-01-01

    PIWI-interacting (piRNAs), ~23-36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western blotting and then identified piRNA transcriptomes in tissues of normal ovary and two most prevalent epithelial ovarian cancer subtypes, serous and endometrioid by small RNA sequencing. We detected 219, 256 and 234 piRNAs in normal ovary, endometrioid and serous ovarian cancer samples respectively. We observed piRNAs are encoded from various genomic regions, among which introns harbor the majority of them. Surprisingly, piRNAs originated from different genomic contexts showed the varied level of conservations across vertebrates. The functional analysis of predicted targets of differentially expressed piRNAs revealed these could modulate key processes and pathways involved in ovarian oncogenesis. Our study provides the first comprehensive piRNA landscape in these samples and a useful resource for further functional studies to decipher new mechanistic views of piRNA-mediated gene regulatory networks affecting ovarian oncogenesis. The RNA-seq data is submitted to GEO database (GSE83794).

  13. Endogenous molecular network reveals two mechanisms of heterogeneity within gastric cancer

    Science.gov (United States)

    Li, Site; Zhu, Xiaomei; Liu, Bingya; Wang, Gaowei; Ao, Ping

    2015-01-01

    Intratumor heterogeneity is a common phenomenon and impedes cancer therapy and research. Gastric cancer (GC) cells have generally been classified into two heterogeneous cellular phenotypes, the gastric and intestinal types, yet the mechanisms of maintaining two phenotypes and controlling phenotypic transition are largely unknown. A qualitative systematic framework, the endogenous molecular network hypothesis, has recently been proposed to understand cancer genesis and progression. Here, a minimal network corresponding to such framework was found for GC and was quantified via a stochastic nonlinear dynamical system. We then further extended the framework to address the important question of intratumor heterogeneity quantitatively. The working network characterized main known features of normal gastric epithelial and GC cell phenotypes. Our results demonstrated that four positive feedback loops in the network are critical for GC cell phenotypes. Moreover, two mechanisms that contribute to GC cell heterogeneity were identified: particular positive feedback loops are responsible for the maintenance of intestinal and gastric phenotypes; GC cell progression routes that were revealed by the dynamical behaviors of individual key components are heterogeneous. In this work, we constructed an endogenous molecular network of GC that can be expanded in the future and would broaden the known mechanisms of intratumor heterogeneity. PMID:25962957

  14. Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.

    Science.gov (United States)

    Siletz, Anaar; Schnabel, Michael; Kniazeva, Ekaterina; Schumacher, Andrew J; Shin, Seungjin; Jeruss, Jacqueline S; Shea, Lonnie D

    2013-01-01

    The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.

  15. Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.

    Directory of Open Access Journals (Sweden)

    Anaar Siletz

    Full Text Available The epithelial-mesenchymal transition (EMT is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.

  16. Integration of Pathway Knowledge and Dynamic Bayesian Networks for the Prediction of Oral Cancer Recurrence.

    Science.gov (United States)

    Kourou, Konstantina; Papaloukas, Costas; Fotiadis, Dimitrios I

    2017-03-01

    Oral squamous cell carcinoma has been characterized as a complex disease which involves dynamic genomic changes at the molecular level. These changes indicate the worth to explore the interactions of the molecules and especially of differentially expressed genes that contribute to cancer progression. Moreover, based on this knowledge the identification of differentially expressed genes and related molecular pathways is of great importance. In the present study, we exploit differentially expressed genes in order to further perform pathway enrichment analysis. According to our results we found significant pathways in which the disease associated genes have been identified as strongly enriched. Furthermore, based on the results of the pathway enrichment analysis we propose a methodology for predicting oral cancer recurrence using dynamic Bayesian networks. The methodology takes into consideration time series gene expression data in order to predict a disease recurrence. Subsequently, we are able to conjecture about the causal interactions between genes in consecutive time intervals. Concerning the performance of the predictive models, the overall accuracy of the algorithm is 81.8% and the area under the ROC curve 89.2% regarding the knowledge from the overrepresented pre-NOTCH Expression and processing pathway.

  17. Barrett's Esophagus Translational Research Network (BETRNet) | Division of Cancer Prevention

    Science.gov (United States)

    The goal of BETRNet is to reduce the incidence, morbidity, and mortality of esophageal adenocarcinoma by answering key questions related to the progression of the disease, especially in the premalignant stage. In partnership with NCI’s Division of Cancer Biology, multidisciplinary translational research centers collaborate to better understand the biology of Barrett's

  18. Case Study: Pancreas cancer with Whipple's operation

    African Journals Online (AJOL)

    Keywords: pancreas cancer, Whipple procedure, SASPEN case study ..... Grade A. Grade B. Grade C. Nasogastric tube required. 4-7 days or reinserted > postoperative day 3 .... malabsorption and vitamin and mineral deficiencies are the most.

  19. Experimental studies on cancer chemotherapy

    International Nuclear Information System (INIS)

    1976-08-01

    The further development of the chemotherapy of cancer in the experimental and clinical fields necessitates a profound knowledge of its chemical, biochemical and pharmacological fundamentals and the mechanism of physiological and pathological growth processes. The 'Arbeitsgemeinschaft Zytostatika' includes chemists, biochemists, pharmacologists, molecular biologists, physicians and immunologists of various scientific institutes and clinics in the Federal Republic of Germany and in West Berlin. It is their aim to carry out basic research as well as clinical-orientated research in the field of the chemotherapy of cancer. In the 15 years of cooperation, fundamental knowledge was gained, especially in the field of the cytotoxic specificity and cancerotoxic selectivity of alkylating cytostatics. New cytostatics with a greater oncostatic selectivity and an altered spectrum of activity were tested and greater knowledge was won on the molecular-biological prerequisites of a rational drug design. (orig.) [de

  20. Cancer incidence study in Mesa County, Colorado

    International Nuclear Information System (INIS)

    Ouimette, D.R.; Ferguson, S.W.; Zoglo, D.; Murphy, S.; Alley, S.; Bahler, S.

    1983-01-01

    In November of 1982 the Colorado Department of Health completed an epidemiologic investigation of leukemia, multiple myeloma, and cancers of the lung, stomach, pancreas and colon in Mesa County, Colorado for the years 1970 to 1979. This investigation was performed in response to a concern that the presence of uranium mill tailings in some Mesa County homes presents a potential cancer hazard. The results of the investigation show that the incidence of multiple myeloma, colon, stomach and pancreatic cancer are not above expected rates. The incidence of leukemia is not above expected rates for the entire study period, 1970 to 1979. The incidence of lung cancer appears elevated when compared to the The Third National Cancer Survey data for Colorado but lower than expected when compared to Surveillance, Epidemiology and End Results data. To further examine the leukemia and lung cancer incidence findings, a case/control study was conducted. The controls consisted of colon, stomach and pancreatic cancer cases. The results of the leukemia case/control analysis show no association with the radiation exposure variables: occupational radiation exposure; uranium mining exposure; having ever lived in a type A home (uranium tailings home); and radiation therapy. The lung cancer case/control analysis shows a significant association with only the radiation exposure variable, uranium mining history, indicating cases were more likely to have been uranium miners than were controls. As with leukemia, the study found no association between lung cancer and living in a uranium mill tailings home. The relatively low radiation exposures typical of type A homes and the small number of persons exposed make it very difficult to establish, by epidemiologic methods, that a risk exists

  1. Inference of hierarchical regulatory network of estrogen-dependent breast cancer through ChIP-based data

    Directory of Open Access Journals (Sweden)

    Parvin Jeffrey

    2010-12-01

    Full Text Available Abstract Background Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks. Results In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2 were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM. A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes. We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes and targeted TFs (25% of common TFs. The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells. Conclusions Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to

  2. TGF-β1 targets a microRNA network that regulates cellular adhesion and migration in renal cancer.

    Science.gov (United States)

    Bogusławska, Joanna; Rodzik, Katarzyna; Popławski, Piotr; Kędzierska, Hanna; Rybicka, Beata; Sokół, Elżbieta; Tański, Zbigniew; Piekiełko-Witkowska, Agnieszka

    2018-01-01

    In our previous study we found altered expression of 19 adhesion-related genes in renal tumors. In this study we hypothesized that disturbed expression of adhesion-related genes could be caused by microRNAs: short, non-coding RNAs that regulate gene expression. Here, we found that expression of 24 microRNAs predicted to target adhesion-related genes was disturbed in renal tumors and correlated with expression of their predicted targets. miR-25-3p, miR-30a-5p, miR-328 and miR-363-3p directly targeted adhesion-related genes, including COL5A1, COL11A1, ITGA5, MMP16 and THBS2. miR-363-3p and miR-328 inhibited proliferation of renal cancer cells, while miR-25-3p inhibited adhesion, promoted proliferation and migration of renal cancer cells. TGF-β1 influenced the expression of miR-25-3p, miR-30a-5p, and miR-328. The analyzed microRNAs, their target genes and TGF-β1 formed a network of strong correlations in tissue samples from renal cancer patients. The expression signature of microRNAs linked with TGF-β1 levels correlated with poor survival of renal cancer patients. The results of our study suggest that TGF-β1 coordinates the expression of microRNA network that regulates cellular adhesion in cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. A Medical Center Network for Optimized Lung Cancer Biospecimen Banking

    Science.gov (United States)

    2017-10-01

    of a centralized biobank of high quality tissue, blood, urine , bronchoscopic washing and saliva samples from lung cancer subjects that are...specimen collection kits, informatics infrastructure, quality control procedures and specimen storage as well as being the contact site for...insufficient sample collection. Follow-up Accrual The LCBRN attempts to collect clinical follow-up data on all LCBRN patients at 6 months intervals

  4. Satisfaction with support versus size of network: differential effects of social support on psychological distress in parents of pediatric cancer patients.

    Science.gov (United States)

    Harper, Felicity W K; Peterson, Amy M; Albrecht, Terrance L; Taub, Jeffrey W; Phipps, Sean; Penner, Louis A

    2016-05-01

    This study examined the direct and buffering effects of social support on longer-term global psychological distress among parents coping with pediatric cancer. In both sets of analyses, we examined whether these effects depended on the dimension of social support provided (i.e., satisfaction with support versus size of support network). Participants were 102 parents of pediatric cancer patients. At study entry, parents reported their trait anxiety, depression, and two dimensions of their social support network (satisfaction with support and size of support network). Parents subsequently reported their psychological distress in 3- and 9-month follow-up assessments. Parents' satisfaction with support had a direct effect on longer-term psychological distress; satisfaction was negatively associated with distress at both follow-ups. In contrast, size of support network buffered (moderated) the impact of trait anxiety and depression on later distress. Parents with smaller support networks and higher levels of trait anxiety and depression at baseline had higher levels of psychological distress at both follow-ups; for parents with larger support networks, there was no relationship. Social support can attenuate psychological distress in parents coping with pediatric cancer; however, the nature of the effect depends on the dimension of support. Whereas interventions that focus on increasing satisfaction with social support may benefit all parents, at-risk parents will likely benefit from interventions that ensure they have an adequate number of support resources. Copyright © 2015 John Wiley & Sons, Ltd.

  5. NetNorM: Capturing cancer-relevant information in somatic exome mutation data with gene networks for cancer stratification and prognosis.

    Science.gov (United States)

    Le Morvan, Marine; Zinovyev, Andrei; Vert, Jean-Philippe

    2017-06-01

    Genome-wide somatic mutation profiles of tumours can now be assessed efficiently and promise to move precision medicine forward. Statistical analysis of mutation profiles is however challenging due to the low frequency of most mutations, the varying mutation rates across tumours, and the presence of a majority of passenger events that hide the contribution of driver events. Here we propose a method, NetNorM, to represent whole-exome somatic mutation data in a form that enhances cancer-relevant information using a gene network as background knowledge. We evaluate its relevance for two tasks: survival prediction and unsupervised patient stratification. Using data from 8 cancer types from The Cancer Genome Atlas (TCGA), we show that it improves over the raw binary mutation data and network diffusion for these two tasks. In doing so, we also provide a thorough assessment of somatic mutations prognostic power which has been overlooked by previous studies because of the sparse and binary nature of mutations.

  6. Statistical study on cancer patients of cancer research hospital

    International Nuclear Information System (INIS)

    Shim, Yoon Sang; Choi, Soo Yong; Won, Hyuk; Kim, Kee Hwa

    1991-01-01

    The total number of malignant neoplasms included on this study 7,787 cases(10.4%) among 74,928 cases for 2 years. On sex, females with 57.6% were much more than males with 42.4%. The highest proportion of cancer 50-59 age group. The most frequent primary site among males was found to be stomach with 36.2%, followed by liver(12.3%), lung(12.2%), esophagus(15.5%) and larynx(4.9%). In females, the first order was uterine cervix with 47.3%, followed most common type of morphology of malignant neoplasms was adenocarcinoma(39.0%) in males an squamous cell carcinoma(56.2%) in females. Among the cancer patients initially diagnosed in this hospital, the proportion of malignant neoplasms by the extent of disease was 4.6% for patient with carcinoma-in-situ, 76.3% for patients with localized involvement, 11.6% for patients with regional involvement and 7.5% for patients with distant involvement. Among,the cancer patients initially treatment in this hospital, the proportion of malignant neoplasms by the method of treatment was 19.0% for surgery, 27.7 for radiotherapy and 24.2% for chemotherapy. Among the cancer patients confirmed by medical records, 11.2% was traced more than 5 years. (Author)

  7. The Oncogenic Palmitoyi-Protein Network in Prostate Cancer

    Science.gov (United States)

    2015-06-01

    was performed by comparing LFQ intensities computed by MaxQuant.16 After statistical analysis, we identified 29 significantly downregulated and 32... statistical analysis, 30 candidate palmitoyl-proteins with an H/L ratio cutoff of 0.667 were accepted as candidate DHHC3 substrates (Table 1). Among...proteomics, we identified a gigantic palmitoyl-protein network regulated by caveolin-1. Moreover, by integrating RNA interference (RNAi), triplex SILAC, and

  8. Social networks and social support for healthy eating among Latina breast cancer survivors: implications for social and behavioral interventions.

    Science.gov (United States)

    Crookes, Danielle M; Shelton, Rachel C; Tehranifar, Parisa; Aycinena, Corina; Gaffney, Ann Ogden; Koch, Pam; Contento, Isobel R; Greenlee, Heather

    2016-04-01

    Little is known about Latina breast cancer survivors' social networks or their perceived social support to achieve and maintain a healthy diet. This paper describes the social networks and perceived support for healthy eating in a sample of breast cancer survivors of predominantly Dominican descent living in New York City. Spanish-speaking Latina breast cancer survivors enrolled in a randomized controlled trial of a culturally tailored dietary intervention. Social networks were assessed using Cohen's Social Network Index and a modified General Social Survey Social Networks Module that included assessments of shared health promoting behaviors. Perceived social support from family and friends for healthy, food-related behaviors was assessed. Participants' networks consisted predominantly of family and friends. Family members were more likely than other individuals to be identified as close network members. Participants were more likely to share food-related activities than exercise activities with close network members. Perceived social support for healthy eating was high, although perceived support from spouses and children was higher than support from friends. Despite high levels of perceived support, family was also identified as a barrier to eating healthy foods by nearly half of women. Although friends are part of Latina breast cancer survivors' social networks, spouses and children may provide greater support for healthy eating than friends. Involving family members in dietary interventions for Latina breast cancer survivors may tap into positive sources of support for women, which could facilitate uptake and maintenance of healthy eating behaviors.

  9. Probability of Alzheimer's disease in breast cancer survivors based on gray-matter structural network efficiency.

    Science.gov (United States)

    Kesler, Shelli R; Rao, Vikram; Ray, William J; Rao, Arvind

    2017-01-01

    Breast cancer chemotherapy is associated with accelerated aging and potentially increased risk for Alzheimer's disease (AD). We calculated the probability of AD diagnosis from brain network and demographic and genetic data obtained from 47 female AD converters and 47 matched healthy controls. We then applied this algorithm to data from 78 breast cancer survivors. The classifier discriminated between AD and healthy controls with 86% accuracy ( P  < .0001). Chemotherapy-treated breast cancer survivors demonstrated significantly higher probability of AD compared to healthy controls ( P  < .0001) and chemotherapy-naïve survivors ( P  = .007), even after stratifying for apolipoprotein e4 genotype. Chemotherapy-naïve survivors also showed higher AD probability compared to healthy controls ( P  = .014). Chemotherapy-treated breast cancer survivors who have a particular profile of brain structure may have a higher risk for AD, especially those who are older and have lower cognitive reserve.

  10. Proteomics in studying cancer stem cell biology.

    Science.gov (United States)

    Kranenburg, Onno; Emmink, Benjamin L; Knol, Jaco; van Houdt, Winan J; Rinkes, Inne H M Borel; Jimenez, Connie R

    2012-06-01

    Normal multipotent tissue stem cells (SCs) are the driving force behind tissue turnover and repair. The cancer stem cell theory holds that tumors also contain stem-like cells that drive tumor growth and metastasis formation. However, very little is known about the regulation of SC maintenance pathways in cancer and how these are affected by cancer-specific genetic alterations and by treatment. Proteomics is emerging as a powerful tool to identify the signaling complexes and pathways that control multi- and pluri-potency and SC differentiation. Here, the authors review the novel insights that these studies have provided and present a comprehensive strategy for the use of proteomics in studying cancer SC biology.

  11. Validation of malayalam version of national comprehensive cancer network distress thermometer and its feasibility in oncology patients

    Directory of Open Access Journals (Sweden)

    M S Biji

    2018-01-01

    Full Text Available Context: This study was designed to translate and validate the National Comprehensive Cancer Network (NCCN distress thermometer (DT in regional language " Malayalam" and to see the feasibility of using it in our patients. Aims: (1 To translate and validate the NCCN DT. (2 To study the feasibility of using validated Malayalam translated DT in Malabar Cancer center. Settings and Design: This is a single-arm prospective observational study. The study was conducted at author's institution between December 8, 2015, and January 20, 2016 in the Department of Cancer Palliative Medicine. Materials and Methods: This was a prospective observational study carried out in two phases. In Phase 1, the linguistic validation of the NCCN DT was done. In Phase 2, the feasibility, face validity, and utility of the translated of NCCN DT in accordance with QQ-10 too was done. Statistical Analysis Used: SPSS version 16 (SPSS Inc. Released 2007. SPSS for Windows, Version 16.0. Chicago, SPSS Inc. was used for analysis. Results: Ten patients were enrolled in Phase 2. The median age was 51.5 years and 40% of patients were male. All patients had completed at least basic education up to the primary level. The primary site of cancer was heterogeneous. The NCCN DT completion rate was 100%. The face validity, utility, reliability, and feasibility were 100%, 100%, 100%, and 90%, respectively. Conclusion: It can be concluded that the Malayalam validated DT has high face validity, utility, and it is feasible for its use.

  12. Validation of Malayalam Version of National Comprehensive Cancer Network Distress Thermometer and its Feasibility in Oncology Patients.

    Science.gov (United States)

    Biji, M S; Dessai, Sampada; Sindhu, N; Aravind, Sithara; Satheesan, B

    2018-01-01

    This study was designed to translate and validate the National Comprehensive Cancer Network (NCCN) distress thermometer (DT) in regional language " Malayalam" and to see the feasibility of using it in our patients. (1) To translate and validate the NCCN DT. (2) To study the feasibility of using validated Malayalam translated DT in Malabar Cancer center. This is a single-arm prospective observational study. The study was conducted at author's institution between December 8, 2015, and January 20, 2016 in the Department of Cancer Palliative Medicine. This was a prospective observational study carried out in two phases. In Phase 1, the linguistic validation of the NCCN DT was done. In Phase 2, the feasibility, face validity, and utility of the translated of NCCN DT in accordance with QQ-10 too was done. SPSS version 16 (SPSS Inc. Released 2007. SPSS for Windows, Version 16.0. Chicago, SPSS Inc.) was used for analysis. Ten patients were enrolled in Phase 2. The median age was 51.5 years and 40% of patients were male. All patients had completed at least basic education up to the primary level. The primary site of cancer was heterogeneous. The NCCN DT completion rate was 100%. The face validity, utility, reliability, and feasibility were 100%, 100%, 100%, and 90%, respectively. It can be concluded that the Malayalam validated DT has high face validity, utility, and it is feasible for its use.

  13. Internet and social network recruitment: two case studies.

    Science.gov (United States)

    Johnson, Kathy A; Peace, Jane

    2012-01-01

    The recruitment of study participants is a significant research challenge. The Internet, with its ability to reach large numbers of people in networks connected by email, Facebook and other social networking mechanisms, appears to offer new avenues for recruitment. This paper reports recruitment experiences from two research projects that engaged the Internet and social networks in different ways for study recruitment. Drawing from the non-Internet recruitment literature, we speculate that the relationship with the source of the research and the purpose of the engaged social network should be a consideration in Internet or social network recruitment strategies.

  14. CTD² Dashboard: a searchable web interface to connect validated results from the Cancer Target Discovery and Development Network* | Office of Cancer Genomics

    Science.gov (United States)

    The Cancer Target Discovery and Development (CTD2) Network aims to use functional genomics to accelerate the translation of high-throughput and high-content genomic and small-molecule data towards use in precision oncology.

  15. Targeting Stromal-Cancer Cell Crosstalk Networks in Ovarian Cancer Treatment

    Directory of Open Access Journals (Sweden)

    Tsz-Lun Yeung

    2016-01-01

    Full Text Available Ovarian cancer is a histologically, clinically, and molecularly diverse disease with a five-year survival rate of less than 30%. It has been estimated that approximately 21,980 new cases of epithelial ovarian cancer will be diagnosed and 14,270 deaths will occur in the United States in 2015, making it the most lethal gynecologic malignancy. Ovarian tumor tissue is composed of cancer cells and a collection of different stromal cells. There is increasing evidence that demonstrates that stromal involvement is important in ovarian cancer pathogenesis. Therefore, stroma-specific signaling pathways, stroma-derived factors, and genetic changes in the tumor stroma present unique opportunities for improving the diagnosis and treatment of ovarian cancer. Cancer-associated fibroblasts (CAFs are one of the major components of the tumor stroma that have demonstrated supportive roles in tumor progression. In this review, we highlight various types of signaling crosstalk between ovarian cancer cells and stromal cells, particularly with CAFs. In addition to evaluating the importance of signaling crosstalk in ovarian cancer progression, we discuss approaches that can be used to target tumor-promoting signaling crosstalk and how these approaches can be translated into potential ovarian cancer treatment.

  16. Use of an Artificial Neural Network to Construct a Model of Predicting Deep Fungal Infection in Lung Cancer Patients.

    Science.gov (United States)

    Chen, Jian; Chen, Jie; Ding, Hong-Yan; Pan, Qin-Shi; Hong, Wan-Dong; Xu, Gang; Yu, Fang-You; Wang, Yu-Min

    2015-01-01

    The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05% (200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (≥65 years), use of antibiotics, low serum albumin concentrations (≤37.18 g /L), radiotherapy, surgery, low hemoglobin hyperlipidemia (≤93.67 g /L), long time of hospitalization (≥14 days) were apt to deep fungal infection and the ANN model consisted of the seven factors. The AUC of ANN model (0.829±0.019) was higher than that of LR model (0.756±0.021). The artificial neural network model with variables consisting of age, use of antibiotics, serum albumin concentrations, received radiotherapy, received surgery, hemoglobin, time of hospitalization should be useful for predicting the deep fungal infection in lung cancer.

  17. Curcumin AntiCancer Studies in Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    Sabrina Bimonte

    2016-07-01

    Full Text Available Pancreatic cancer (PC is one of the deadliest cancers worldwide. Surgical resection remains the only curative therapeutic treatment for this disease, although only the minority of patients can be resected due to late diagnosis. Systemic gemcitabine-based chemotherapy plus nab-paclitaxel are used as the gold-standard therapy for patients with advanced PC; although this treatment is associated with a better overall survival compared to the old treatment, many side effects and poor results are still present. Therefore, new alternative therapies have been considered for treatment of advanced PC. Several preclinical studies have demonstrated that curcumin, a naturally occurring polyphenolic compound, has anticancer effects against different types of cancer, including PC, by modulating many molecular targets. Regarding PC, in vitro studies have shown potent cytotoxic effects of curcumin on different PC cell lines including MiaPaCa-2, Panc-1, AsPC-1, and BxPC-3. In addition, in vivo studies on PC models have shown that the anti-proliferative effects of curcumin are caused by the inhibition of oxidative stress and angiogenesis and are due to the induction of apoptosis. On the basis of these results, several researchers tested the anticancer effects of curcumin in clinical trials, trying to overcome the poor bioavailability of this agent by developing new bioavailable forms of curcumin. In this article, we review the results of pre-clinical and clinical studies on the effects of curcumin in the treatment of PC.

  18. NIH study confirms risk factors for male breast cancer

    Science.gov (United States)

    Pooled data from studies of about 2,400 men with breast cancer and 52,000 men without breast cancer confirmed that risk factors for male breast cancer include obesity, a rare genetic condition called Klinefelter syndrome, and gynecomastia.

  19. A Study on Knowledge and Screening for Cervical Cancer among ...

    African Journals Online (AJOL)

    A Study on Knowledge and Screening for Cervical Cancer among Women in ... and source of information for awareness of women about cervical cancer in India. ... Results: Majority of the women have poor knowledge about cervical cancer ...

  20. Failure detection studies by layered neural network

    International Nuclear Information System (INIS)

    Ciftcioglu, O.; Seker, S.; Turkcan, E.

    1991-06-01

    Failure detection studies by layered neural network (NN) are described. The particular application area is an operating nuclear power plant and the failure detection is of concern as result of system surveillance in real-time. The NN system is considered to be consisting of 3 layers, one of which being hidden, and the NN parameters are determined adaptively by the backpropagation (BP) method, the process being the training phase. Studies are performed using the power spectra of the pressure signal of the primary system of an operating nuclear power plant of PWR type. The studies revealed that, by means of NN approach, failure detection can effectively be carried out using the redundant information as well as this is the case in this work; namely, from measurement of the primary pressure signals one can estimate the primary system coolant temperature and hence the deviation from the operational temperature state, the operational status identified in the training phase being referred to as normal. (author). 13 refs.; 4 figs.; 2 tabs

  1. Voltage-gated Na+ channel SCN5A is a key regulator of a gene transcriptional network that controls colon cancer invasion

    Science.gov (United States)

    House, Carrie D.; Vaske, Charles J.; Schwartz, Arnold M.; Obias, Vincent; Frank, Bryan; Luu, Truong; Sarvazyan, Narine; Irby, Rosalyn; Strausberg, Robert L.; Hales, Tim G.; Stuart, Joshua M.; Lee, Norman H.

    2010-01-01

    Voltage-gated Na+ channels (VGSCs) have been implicated in the metastatic potential of human breast, prostate and lung cancer cells. Specifically, the SCN5A gene encoding the VGSC isotype Nav1.5 has been defined as a key driver of human cancer cell invasion. In this study, we examined the expression and function of VGSCs in a panel of colon cancer cell lines by electrophysiological recordings. Na+ channel activity and invasive potential were inhibited pharmacologically by tetrodotoxin or genetically by siRNAs specifically targeting SCN5A. Clinical relevance was established by immunohistochemistry of patient biopsies, where there was strong Nav1.5 protein staining in colon cancer specimens but little to no staining in matched-paired normal colon tissues. We explored the mechanism of VGSC-mediated invasive potential on the basis of reported links between VGSC activity and gene expression in excitable cells. Probabilistic modeling of loss-of-function screens and microarray data established an unequivocal role of VGSC SCN5A as a high level regulator of a colon cancer invasion network, involving genes that encompass Wnt signaling, cell migration, ectoderm development, response to biotic stimulus, steroid metabolic process and cell cycle control. siRNA-mediated knockdown of predicted downstream network components caused a loss of invasive behavior, demonstrating network connectivity and its function in driving colon cancer invasion. PMID:20651255

  2. Network-Based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis.

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2015-12-01

    Full Text Available High-throughput mRNA sequencing (RNA-Seq is widely used for transcript quantification of gene isoforms. Since RNA-Seq data alone is often not sufficient to accurately identify the read origins from the isoforms for quantification, we propose to explore protein domain-domain interactions as prior knowledge for integrative analysis with RNA-Seq data. We introduce a Network-based method for RNA-Seq-based Transcript Quantification (Net-RSTQ to integrate protein domain-domain interaction network with short read alignments for transcript abundance estimation. Based on our observation that the abundances of the neighboring isoforms by domain-domain interactions in the network are positively correlated, Net-RSTQ models the expression of the neighboring transcripts as Dirichlet priors on the likelihood of the observed read alignments against the transcripts in one gene. The transcript abundances of all the genes are then jointly estimated with alternating optimization of multiple EM problems. In simulation Net-RSTQ effectively improved isoform transcript quantifications when isoform co-expressions correlate with their interactions. qRT-PCR results on 25 multi-isoform genes in a stem cell line, an ovarian cancer cell line, and a breast cancer cell line also showed that Net-RSTQ estimated more consistent isoform proportions with RNA-Seq data. In the experiments on the RNA-Seq data in The Cancer Genome Atlas (TCGA, the transcript abundances estimated by Net-RSTQ are more informative for patient sample classification of ovarian cancer, breast cancer and lung cancer. All experimental results collectively support that Net-RSTQ is a promising approach for isoform quantification. Net-RSTQ toolbox is available at http://compbio.cs.umn.edu/Net-RSTQ/.

  3. Usage of Probabilistic and General Regression Neural Network for Early Detection and Prevention of Oral Cancer

    Directory of Open Access Journals (Sweden)

    Neha Sharma

    2015-01-01

    Full Text Available In India, the oral cancers are usually presented in advanced stage of malignancy. It is critical to ascertain the diagnosis in order to initiate most advantageous treatment of the suspicious lesions. The main hurdle in appropriate treatment and control of oral cancer is identification and risk assessment of early disease in the community in a cost-effective fashion. The objective of this research is to design a data mining model using probabilistic neural network and general regression neural network (PNN/GRNN for early detection and prevention of oral malignancy. The model is built using the oral cancer database which has 35 attributes and 1025 records. All the attributes pertaining to clinical symptoms and history are considered to classify malignant and non-malignant cases. Subsequently, the model attempts to predict particular type of cancer, its stage and extent with the help of attributes pertaining to symptoms, gross examination and investigations. Also, the model envisages anticipating the survivability of a patient on the basis of treatment and follow-up details. Finally, the performance of the PNN/GRNN model is compared with that of other classification models. The classification accuracy of PNN/GRNN model is 80% and hence is better for early detection and prevention of the oral cancer.

  4. Usage of Probabilistic and General Regression Neural Network for Early Detection and Prevention of Oral Cancer.

    Science.gov (United States)

    Sharma, Neha; Om, Hari

    2015-01-01

    In India, the oral cancers are usually presented in advanced stage of malignancy. It is critical to ascertain the diagnosis in order to initiate most advantageous treatment of the suspicious lesions. The main hurdle in appropriate treatment and control of oral cancer is identification and risk assessment of early disease in the community in a cost-effective fashion. The objective of this research is to design a data mining model using probabilistic neural network and general regression neural network (PNN/GRNN) for early detection and prevention of oral malignancy. The model is built using the oral cancer database which has 35 attributes and 1025 records. All the attributes pertaining to clinical symptoms and history are considered to classify malignant and non-malignant cases. Subsequently, the model attempts to predict particular type of cancer, its stage and extent with the help of attributes pertaining to symptoms, gross examination and investigations. Also, the model envisages anticipating the survivability of a patient on the basis of treatment and follow-up details. Finally, the performance of the PNN/GRNN model is compared with that of other classification models. The classification accuracy of PNN/GRNN model is 80% and hence is better for early detection and prevention of the oral cancer.

  5. Epidemiological studies on gastric cancer in Nagasaki

    International Nuclear Information System (INIS)

    Iwasaki, Keisuke; Kawamoto, Kenji; Shimokawa, Isao; Matsuo, Takeshi; Ikeda, Takayoshi

    1984-01-01

    One thousand-four hundred and twenty-four cases of gastric cancer registered at the Nagasaki Tumor Registry between 1973 and 1977 were studied. The incidence of gastric cancer tended to be higher in persons exposed to the atomic bomb within 2.0 km from the hypocenter, especially in young persons, than in non-exposed individuals, but the difference was not statistically significant. Compared with the nonexposed, the corrected relative risk of gastric cancer in persons exposed within 2.0 km from the hypocenter was 1.28 in males and 1.11 in females. In terms of histologic type or location, the incidence of gastric cancer showed no statistically significant difference between the exposed and nonexposed persons. (author)

  6. Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

    Science.gov (United States)

    Wutsqa, D. U.; Marwah, M.

    2017-06-01

    In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

  7. Deep Space Network information system architecture study

    Science.gov (United States)

    Beswick, C. A.; Markley, R. W. (Editor); Atkinson, D. J.; Cooper, L. P.; Tausworthe, R. C.; Masline, R. C.; Jenkins, J. S.; Crowe, R. A.; Thomas, J. L.; Stoloff, M. J.

    1992-01-01

    The purpose of this article is to describe an architecture for the DSN information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990's. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies--i.e., computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control.

  8. SentiHealth-Cancer: A sentiment analysis tool to help detecting mood of patients in online social networks.

    Science.gov (United States)

    Rodrigues, Ramon Gouveia; das Dores, Rafael Marques; Camilo-Junior, Celso G; Rosa, Thierson Couto

    2016-01-01

    Cancer is a critical disease that affects millions of people and families around the world. In 2012 about 14.1 million new cases of cancer occurred globally. Because of many reasons like the severity of some cases, the side effects of some treatments and death of other patients, cancer patients tend to be affected by serious emotional disorders, like depression, for instance. Thus, monitoring the mood of the patients is an important part of their treatment. Many cancer patients are users of online social networks and many of them take part in cancer virtual communities where they exchange messages commenting about their treatment or giving support to other patients in the community. Most of these communities are of public access and thus are useful sources of information about the mood of patients. Based on that, Sentiment Analysis methods can be useful to automatically detect positive or negative mood of cancer patients by analyzing their messages in these online communities. The objective of this work is to present a Sentiment Analysis tool, named SentiHealth-Cancer (SHC-pt), that improves the detection of emotional state of patients in Brazilian online cancer communities, by inspecting their posts written in Portuguese language. The SHC-pt is a sentiment analysis tool which is tailored specifically to detect positive, negative or neutral messages of patients in online communities of cancer patients. We conducted a comparative study of the proposed method with a set of general-purpose sentiment analysis tools adapted to this context. Different collections of posts were obtained from two cancer communities in Facebook. Additionally, the posts were analyzed by sentiment analysis tools that support the Portuguese language (Semantria and SentiStrength) and by the tool SHC-pt, developed based on the method proposed in this paper called SentiHealth. Moreover, as a second alternative to analyze the texts in Portuguese, the collected texts were automatically translated

  9. Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients.

    Science.gov (United States)

    Kim, Yun Hak; Jeong, Dae Cheon; Pak, Kyoungjune; Goh, Tae Sik; Lee, Chi-Seung; Han, Myoung-Eun; Kim, Ji-Young; Liangwen, Liu; Kim, Chi Dae; Jang, Jeon Yeob; Cha, Wonjae; Oh, Sae-Ock

    2017-09-29

    Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison of C-index and AUC values in receiver operating characteristic analysis at 5 years showed fewer differences between training and validation cohorts with the Net scoring system than other statistical methods, suggesting minimal overfitting. The Net-based scoring system also successfully predicted prognosis in various independent GEO cohorts with high discriminatory power. In conclusion, the Net-based scoring system showed better discriminative power than previous statistical methods in prognostic prediction for breast cancer patients. This new system will mark a new era in prognosis prediction for cancer patients.

  10. Studies on retrospective analysis of leading primary cancers and improvement of cancer treatment method in Korea cancer center hospital

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jong In; Lee, Kang Hyun; Choi, Soo Yong; Kim, Ki Wha; Kang, Sung Mok

    2000-12-01

    a. Retrospective studies included cancers of the stomach, breast, bladder, salivary gland, thyroid, esophagus, endometrium and ovary. (1) Study cancers were analyzed about clinical characteristics, prognostic factors influenced on survival time, survival rate, etc. (2) Among 5,305 study patients, 1,405(26.5%) were identified with death, 3,485(65.7%) were alive and 415(7.8%) were not identified. b. Prospective studies included 10 subjects such as bladder cancer, retinoblastoma, malignant patients, gastric cancer, uterine cervix cancer and ovary cancer. We are continuing registering eligible study patients. c. Results for 11 papers were published at the journal. d. We established follow-up system in order to identify the survival for study subjects through National Statistical Office, Government Provincial Office and Cancer Registration System at Korea Cancer Center Hospital. e. At present, we are establishing computerized registration system about case report form for study cancers.

  11. Studies on retrospective analysis of leading primary cancers and improvement of cancer treatment method in Korea cancer center hospital

    International Nuclear Information System (INIS)

    Lee, Jong In; Lee, Kang Hyun; Choi, Soo Yong; Kim, Ki Wha; Kang, Sung Mok

    2000-12-01

    a. Retrospective studies included cancers of the stomach, breast, bladder, salivary gland, thyroid, esophagus, endometrium and ovary. (1) Study cancers were analyzed about clinical characteristics, prognostic factors influenced on survival time, survival rate, etc. (2) Among 5,305 study patients, 1,405(26.5%) were identified with death, 3,485(65.7%) were alive and 415(7.8%) were not identified. b. Prospective studies included 10 subjects such as bladder cancer, retinoblastoma, malignant patients, gastric cancer, uterine cervix cancer and ovary cancer. We are continuing registering eligible study patients. c. Results for 11 papers were published at the journal. d. We established follow-up system in order to identify the survival for study subjects through National Statistical Office, Government Provincial Office and Cancer Registration System at Korea Cancer Center Hospital. e. At present, we are establishing computerized registration system about case report form for study cancers

  12. Experimental percolation studies of random networks

    Science.gov (United States)

    Feinerman, A.; Weddell, J.

    2017-06-01

    This report establishes an experimental method of studying electrically percolating networks at a higher resolution than previously implemented. This method measures the current across a conductive sheet as a function of time as elliptical pores are cut into the sheet. This is done utilizing a Universal Laser System X2-600 100 W CO2 laser system with a 76 × 46 cm2 field and 394 dpc (dots/cm) resolution. This laser can cut a random system of elliptical pores into a conductive sheet with a potential voltage applied across it and measures the current versus time. This allows for experimental verification of a percolation threshold as a function of the ellipse's aspect ratio (minor/major diameter). We show that as an ellipse's aspect ratio approaches zero, the percolation threshold approaches one. The benefit of this method is that it can experimentally measure the effect of removing small pores, as well as pores with complex geometries, such as an asterisk from a conductive sheet.

  13. Stage at presentation of breast cancer in Luanda, Angola - a retrospective study.

    Science.gov (United States)

    Lopes, Lygia Vieira; Miguel, Fernando; Freitas, Helga; Tavares, António; Pangui, Salvador; Castro, Clara; Lacerda, Gonçalo Forjaz; Longatto-Filho, Adhemar; Weiderpass, Elisabete; Santos, Lúcio Lara

    2015-10-15

    It is expected that, by 2020, 15 million new cases of cancer will occur every year in the world, one million of them in Africa. Knowledge of cancer trends in African countries is far from adequate, and improvements in cancer prevention efforts are urgently needed. The aim of this study was to characterize breast cancer clinically and pathologically at presentation in Luanda, Angola; we additionally provide quality information that will be useful for breast cancer care planning in the country. Data on breast cancer cases were retrieved from the Angolan Institute of Cancer Control, from 2006 to 2014. For women diagnosed in 2009 (5-years of follow-up), demographic, clinical and pathological information, at presentation, was collected, namely age at diagnosis, parity, methods used for pathological diagnoses, tumor pathological characteristics, stage of disease and treatment. Descriptive statistics were performed. The median age of women diagnosed with breast cancer in 2009 was 47 years old (range 25-89). The most frequent clinical presentation was breast swelling with axillary lymph nodes metastasis (44.9 %), followed by a mass larger than 5 cm (14.2 %) and lump (12.9 %). Invasive ductal carcinoma was the main histologic type (81.8 %). Only 10.1 % of cancer cases had a well differentiated histological grade. Cancers were diagnosed mostly at advanced stages (66.7 % in stage III and 11.1 % in stage IV). In this study, breast cancer was diagnosed at a very advanced stage. Although it reports data from a single cancer center in Luanda, Angola it reinforces the need for early diagnosis and increasing awareness. According to the main challenges related to breast cancer diagnosis and treatment herein presented, we propose a realistic framework that would allow for the implementation of a breast cancer care program, built under a strong network based on cooperation, teaching, audit, good practices and the organization of health services. Angola needs urgently a program for

  14. Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.

    Science.gov (United States)

    Hirasawa, Toshiaki; Aoyama, Kazuharu; Tanimoto, Tetsuya; Ishihara, Soichiro; Shichijo, Satoki; Ozawa, Tsuyoshi; Ohnishi, Tatsuya; Fujishiro, Mitsuhiro; Matsuo, Keigo; Fujisaki, Junko; Tada, Tomohiro

    2018-07-01

    Image recognition using artificial intelligence with deep learning through convolutional neural networks (CNNs) has dramatically improved and been increasingly applied to medical fields for diagnostic imaging. We developed a CNN that can automatically detect gastric cancer in endoscopic images. A CNN-based diagnostic system was constructed based on Single Shot MultiBox Detector architecture and trained using 13,584 endoscopic images of gastric cancer. To evaluate the diagnostic accuracy, an independent test set of 2296 stomach images collected from 69 consecutive patients with 77 gastric cancer lesions was applied to the constructed CNN. The CNN required 47 s to analyze 2296 test images. The CNN correctly diagnosed 71 of 77 gastric cancer lesions with an overall sensitivity of 92.2%, and 161 non-cancerous lesions were detected as gastric cancer, resulting in a positive predictive value of 30.6%. Seventy of the 71 lesions (98.6%) with a diameter of 6 mm or more as well as all invasive cancers were correctly detected. All missed lesions were superficially depressed and differentiated-type intramucosal cancers that were difficult to distinguish from gastritis even for experienced endoscopists. Nearly half of the false-positive lesions were gastritis with changes in color tone or an irregular mucosal surface. The constructed CNN system for detecting gastric cancer could process numerous stored endoscopic images in a very short time with a clinically relevant diagnostic ability. It may be well applicable to daily clinical practice to reduce the burden of endoscopists.

  15. Network analysis of an in vitro model of androgen-resistance in prostate cancer

    International Nuclear Information System (INIS)

    Detchokul, Sujitra; Elangovan, Aparna; Crampin, Edmund J.; Davis, Melissa J.; Frauman, Albert G.

    2015-01-01

    The development of androgen resistance is a major limitation to androgen deprivation treatment in prostate cancer. We have developed an in vitro model of androgen-resistance to characterise molecular changes occurring as androgen resistance evolves over time. Our aim is to understand biological network profiles of transcriptomic changes occurring during the transition to androgen-resistance and to validate these changes between our in vitro model and clinical datasets (paired samples before and after androgen-deprivation therapy of patients with advanced prostate cancer). We established an androgen-independent subline from LNCaP cells by prolonged exposure to androgen-deprivation. We examined phenotypic profiles and performed RNA-sequencing. The reads generated were compared to human clinical samples and were analysed using differential expression, pathway analysis and protein-protein interaction networks. After 24 weeks of androgen-deprivation, LNCaP cells had increased proliferative and invasive behaviour compared to parental LNCaP, and its growth was no longer responsive to androgen. We identified key genes and pathways that overlap between our cell line and clinical RNA sequencing datasets and analysed the overlapping protein-protein interaction network that shared the same pattern of behaviour in both datasets. Mechanisms bypassing androgen receptor signalling pathways are significantly enriched. Several steroid hormone receptors are differentially expressed in both datasets. In particular, the progesterone receptor is significantly differentially expressed and is part of the interaction network disrupted in both datasets. Other signalling pathways commonly altered in prostate cancer, MAPK and PI3K-Akt pathways, are significantly enriched in both datasets. The overlap between the human and cell-line differential expression profiles and protein networks was statistically significant showing that the cell-line model reproduces molecular patterns observed in

  16. Internet and Social Network Recruitment: Two Case Studies

    OpenAIRE

    Johnson, Kathy A.; Peace, Jane

    2012-01-01

    The recruitment of study participants is a significant research challenge. The Internet, with its ability to reach large numbers of people in networks connected by email, Facebook and other social networking mechanisms, appears to offer new avenues for recruitment. This paper reports recruitment experiences from two research projects that engaged the Internet and social networks in different ways for study recruitment. Drawing from the non-Internet recruitment literature, we speculate that th...

  17. Statistical study on cancer patients of Korea cancer centre hospital

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Soo Yong; Kim, Kee Hwa; Mok, Kang Sung [Korea Cancer Center Hospital of Korea Atomic Energy Research Institute, Seoul (Korea, Republic of)

    1994-12-01

    The total number of malignant neoplasms included in this study 53,566 cases(14.1%) among 379,582 patients from 1984 to 1993. On sex, females with 51.3% were much more than males with 48.7%. The highest proportion of cancer patients by age was 35.0% in males and 28.4% in females, respectively for 50-59 age group. The most frequent primary site among males was found to be stomach with 33.2%, followed by liver(15.1%), lung(14.9%), esophagus(5.3%) and larynx(3.3%). In females, the first order was uterine cervix with 37.8%, followed by stomach(16.5%), breast(14.8%), thyroid gland(4.3%) and lung (3.8%). The proportion of malignant neoplasms diagnosed by histology made up 67.0%, whereas 20.2% was diagnosed by clinical investigation(X-ray, CT, MRI etc). Among the cancer patients initially diagnosed in this hospital, the proportion of malignant neoplasms by the extent of disease was 3.7% for patient with carcinoma-in-situ, 58.7% for patients with localized involvement, 18.4% for patients with regional involvement and 11.1% for patients with distant involvement. Among the cancer patients initially treatment in this hospital, the proportion of malignant neoplasms by the method of treatment was 27.5% for surgery, 22.5% for radiotherapy and 30.1% for chemotherapy. The proportion of cancer patients traced to death was only to 3.6%, 1,944 cases. Among them, 72.5% survived for less than 1 year. 17 figs, 7 tabs, 28 refs. (Author).

  18. Statistical study on cancer patients of cancer research hospital

    International Nuclear Information System (INIS)

    Shim, Yun Sang; Choi, Soo Yong; Kim, Ki Wha; Kang, Sung Mok

    1993-01-01

    The total number of malignant neoplasms included in this study 15,737 cases(11.8%) among 133,251 cases for 3 years. On sex, females with 52.9% were much more than males with 47.1%. The highest proportion of cancer patients by age was 33.7% in males and 28.5% in females, respectivelty for 50-59 age group. The most frequent primary site among males was found to be stomach with 35.5%, followed by liver(14.7%), lung(13.0%), esophagus(5.4%) and colon (3.2%). In females, the first order was uterine cervix with 40.6%, followed by stomach(17.2%), breast(14.4), rectum(3.7%) and lung(3.4%). The most common type of morphology of malignant neoplasms was adenocarcinoma(47.4%) in males an squamous cell carcinoma(58.0%) in females. Among the cancer patients initially diagnosed in this hospital, the proportion of malignant neoplasms by the exent of disease was 2.5% for patient with carcinoma-in-situ, 54.1% for patients with localized involvement, 13.3% for patients with regional involvement and 8.5% for patients with distant involvement. Among the cancer patients initially treatment in this hospital, the proportion of malignant neoplasms by the method of treatment was 23.6% for surgery, 25.3% for radiotherapy and 30.3% for chemotherapy. Among the cancer patients confirmed by medical records, 7.7% was traced more than 5 years. (Author)

  19. Statistical study on cancer patients of Korea cancer centre hospital

    International Nuclear Information System (INIS)

    Choi, Soo Yong; Kim, Kee Hwa; Kang Sung Mok

    1994-12-01

    The total number of malignant neoplasms included in this study 53,566 cases(14.1%) among 379,582 patients from 1984 to 1993. On sex, females with 51.3% were much more than males with 48.7%. The highest proportion of cancer patients by age was 35.0% in males and 28.4% in females, respectively for 50-59 age group. The most frequent primary site among males was found to be stomach with 33.2%, followed by liver(15.1%), lung(14.9%), esophagus(5.3%) and larynx(3.3%). In females, the first order was uterine cervix with 37.8%, followed by stomach(16.5%), breast(14.8%), thyroid gland(4.3%) and lung (3.8%). The proportion of malignant neoplasms diagnosed by histology made up 67.0%, whereas 20.2% was diagnosed by clinical investigation(X-ray, CT, MRI etc). Among the cancer patients initially diagnosed in this hospital, the proportion of malignant neoplasms by the extent of disease was 3.7% for patient with carcinoma-in-situ, 58.7% for patients with localized involvement, 18.4% for patients with regional involvement and 11.1% for patients with distant involvement. Among the cancer patients initially treatment in this hospital, the proportion of malignant neoplasms by the method of treatment was 27.5% for surgery, 22.5% for radiotherapy and 30.1% for chemotherapy. The proportion of cancer patients traced to death was only to 3.6%, 1,944 cases. Among them, 72.5% survived for less than 1 year. 17 figs, 7 tabs, 28 refs. (Author)

  20. Social networks and mortality based on the Komo-Ise cohort study in Japan.

    Science.gov (United States)

    Iwasaki, Motoki; Otani, Tetsuya; Sunaga, Rumiko; Miyazaki, Hiroko; Xiao, Liu; Wang, Naren; Yosiaki, Sasazawa; Suzuki, Shosuke

    2002-12-01

    No prospective studies have examined the association between social networks and all-cause and cause-specific mortality among middle-aged Japanese. The study of varied populations may contribute to clarifying the robustness of the observed effects of social networks and extend their generalizability. To clarify the association between social networks and mortality among middle-aged and elderly Japanese, a community-based prospective study, the Komo-Ise Study, was conducted in two areas of Gunma Prefecture, Japan. A total of 11 565 subjects aged 40-69 years at baseline in 1993 completed a self-administered questionnaire. During the 7-year follow-up period, 335 men and 155 women died and the relative risk (RR) of each social network item was estimated by the Cox proportional hazard model. Single women had significantly increased risks of all-cause (multivariate RR = 2.2), and all circulatory system disease (age-area adjusted RR = 2.6) mortality. Men who did not participate in hobbies, club activities, or community groups had significantly higher multivariate RR for all-cause (RR = 1.5), all circulatory system disease (RR = 1.6) and non-cancer and non-circulatory system disease (RR = 2.3) mortality. Urban women who rarely or never met close relatives had significantly elevated risks of all-cause (RR = 2.4), all cancer (RR = 2.6), and non-cancer and non-circulatory system disease (RR = 2.7) mortality after adjustment for established risk factors. This study provides evidence that social networks are an important predictor of mortality risk for middle-aged and elderly Japanese men and women. Lack of participation, for men, and being single and lack of meeting close relatives, for women, were independent risk factors for mortality.

  1. Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes.

    Directory of Open Access Journals (Sweden)

    Christof Winter

    Full Text Available Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.

  2. Physician social networks and variation in prostate cancer treatment in three cities.

    Science.gov (United States)

    Pollack, Craig Evan; Weissman, Gary; Bekelman, Justin; Liao, Kaijun; Armstrong, Katrina

    2012-02-01

    To examine whether physician social networks are associated with variation in treatment for men with localized prostate cancer. 2004-2005 Surveillance, Epidemiology and End Results-Medicare data from three cities. We identified the physicians who care for patients with prostate cancer and created physician networks for each city based on shared patients. Subgroups of urologists were defined as physicians with dense connections with one another via shared patients. Subgroups varied widely in their unadjusted rates of prostatectomy and the racial/ethnic and socioeconomic composition of their patients. There was an association between urologist subgroup and receipt of prostatectomy. In city A, four subgroups had significantly lower odds of prostatectomy compared with the subgroup with the highest rates of prostatectomy after adjusting for patient clinical and sociodemographic characteristics. Similarly, in cities B and C, subgroups had significantly lower odds of prostatectomy compared with the baseline. Using claims data to identify physician networks may provide an insight into the observed variation in treatment patterns for men with prostate cancer. © Health Research and Educational Trust.

  3. The Cancer Cell Map Initiative: Defining the Hallmark Networks of Cancer

    OpenAIRE

    Krogan, Nevan J.; Lippman, Scott; Agard, David A.; Ashworth, Alan; Ideker, Trey

    2015-01-01

    Progress in DNA sequencing has revealed the startling complexity of cancer genomes, which typically carry thousands of somatic mutations. However, it remains unclear which are the key driver mutations or dependencies in a given cancer and how these influence pathogenesis and response to therapy. Although tumors of similar types and clinical outcomes can have patterns of mutations that are strikingly different, it is becoming apparent that these mutations recurrently hijack the same hallmark m...

  4. Network stigma towards people living with HIV/AIDS and their caregivers: An egocentric network study.

    Science.gov (United States)

    Wu, Fei; He, Xin; Guida, Jennifer; Xu, Yongfang; Liu, Hongjie

    2015-10-01

    HIV stigma occurs among peers in social networks. However, the features of social networks that drive HIV stigma are not well understood. The objective of this study is to investigate anticipated HIV stigma within the social networks of people living with HIV/AIDS (PLWHA) (N = 147) and the social networks of PLWHA's caregivers (N = 148). The egocentric social network data were collected in Guangxi, China. More than half of PLWHA (58%) and their caregivers (53%) anticipated HIV stigma from their network peers. Both PLWHA and their caregivers anticipated that spouses or other family members were less likely to stigmatise them, compared to friend peers or other relationships. Married network peers were believed to stigmatise caregivers more than unmarried peers. The association between frequent contacts and anticipated stigma was negative among caregivers. Being in a close relationship with PLWHA or caregivers (e.g., a spouse or other family member) was associated with less anticipated stigma. Lower network density was associated with higher anticipated stigma among PLWHA's alters, but not among caregivers' alters. Findings may shed light on innovative stigma reduction interventions at the social network level and therefore improve HIV/AIDS treatment utilisation.

  5. Czech studies of lung cancer and radon

    International Nuclear Information System (INIS)

    Tomasek, L.

    2002-01-01

    According to the International Agency for Research on Cancer, there is a significant evidence to classify radon as a carcinogen. Using extrapolations from occupational studies, it can be shown that for some countries environmental exposure to radon is the second most important cause of lung cancer in the general population after cigarette smoking. Czech studies among uranium miners, established in 1970 by Josef Sevc, and in the general population aim to contribute to knowledge on the risk from radon, particularly by evaluating temporal factors and interaction of radon exposure and smoking

  6. Bladder cancer treatment response assessment in CT urography using two-channel deep-learning network

    Science.gov (United States)

    Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Samala, Ravi K.; Cohan, Richard H.; Caoili, Elaine M.; Weizer, Alon Z.; Alva, Ajjai

    2018-02-01

    We are developing a CAD system for bladder cancer treatment response assessment in CT. We trained a 2- Channel Deep-learning Convolution Neural Network (2Ch-DCNN) to identify responders (T0 disease) and nonresponders to chemotherapy. The 87 lesions from 82 cases generated 18,600 training paired ROIs that were extracted from segmented bladder lesions in the pre- and post-treatment CT scans and partitioned for 2-fold cross validation. The paired ROIs were input to two parallel channels of the 2Ch-DCNN. We compared the 2Ch-DCNN with our hybrid prepost- treatment ROI DCNN method and the assessments by 2 experienced abdominal radiologists. The radiologist estimated the likelihood of stage T0 after viewing each pre-post-treatment CT pair. Receiver operating characteristic analysis was performed and the area under the curve (AUC) and the partial AUC at sensitivity AUC0.9) were compared. The test AUCs were 0.76+/-0.07 and 0.75+/-0.07 for the 2 partitions, respectively, for the 2Ch-DCNN, and were 0.75+/-0.08 and 0.75+/-0.07 for the hybrid ROI method. The AUCs for Radiologist 1 were 0.67+/-0.09 and 0.75+/-0.07 for the 2 partitions, respectively, and were 0.79+/-0.07 and 0.70+/-0.09 for Radiologist 2. For the 2Ch-DCNN, the AUC0.9s were 0.43 and 0.39 for the 2 partitions, respectively, and were 0.19 and 0.28 for the hybrid ROI method. For Radiologist 1, the AUC0.9s were 0.14 and 0.34 for partition 1 and 2, respectively, and were 0.33 and 0.23 for Radiologist 2. Our study demonstrated the feasibility of using a 2Ch-DCNN for the estimation of bladder cancer treatment response in CT.

  7. A Bayesian network approach for modeling local failure in lung cancer

    International Nuclear Information System (INIS)

    Oh, Jung Hun; Craft, Jeffrey; Al Lozi, Rawan; Vaidya, Manushka; Meng, Yifan; Deasy, Joseph O; Bradley, Jeffrey D; El Naqa, Issam

    2011-01-01

    Locally advanced non-small cell lung cancer (NSCLC) patients suffer from a high local failure rate following radiotherapy. Despite many efforts to develop new dose-volume models for early detection of tumor local failure, there was no reported significant improvement in their application prospectively. Based on recent studies of biomarker proteins' role in hypoxia and inflammation in predicting tumor response to radiotherapy, we hypothesize that combining physical and biological factors with a suitable framework could improve the overall prediction. To test this hypothesis, we propose a graphical Bayesian network framework for predicting local failure in lung cancer. The proposed approach was tested using two different datasets of locally advanced NSCLC patients treated with radiotherapy. The first dataset was collected retrospectively, which comprises clinical and dosimetric variables only. The second dataset was collected prospectively in which in addition to clinical and dosimetric information, blood was drawn from the patients at various time points to extract candidate biomarkers as well. Our preliminary results show that the proposed method can be used as an efficient method to develop predictive models of local failure in these patients and to interpret relationships among the different variables in the models. We also demonstrate the potential use of heterogeneous physical and biological variables to improve the model prediction. With the first dataset, we achieved better performance compared with competing Bayesian-based classifiers. With the second dataset, the combined model had a slightly higher performance compared to individual physical and biological models, with the biological variables making the largest contribution. Our preliminary results highlight the potential of the proposed integrated approach for predicting post-radiotherapy local failure in NSCLC patients.

  8. User survey of Nanny Angel Network, a free childcare service for mothers with cancer.

    Science.gov (United States)

    Cohen, L; Schwartz, N; Guth, A; Kiss, A; Warner, E

    2017-08-01

    The purpose of the present study was to determine user satisfaction with Nanny Angel Network (nan), a free childcare service for mothers undergoing cancer treatment. All 243 living mothers who had used the nan service were invited by telephone to participate in an online research survey; 197 mothers (81%) consented to participate. The survey, sent by e-mail, consisted of 39 items divided into these categories: demographics, supports, use, satisfaction, and general comments. Of the 197 mothers who consented to receive the e-mailed survey, 104 (53%) completed it. More than 90% of the mothers were very satisfied with the help and support from their Nanny Angel. Many mothers mentioned that the Nanny Angel was most helpful during treatment and medical appointments, with 75% also mentioning that their Nanny Angel helped them to adhere to their scheduled medical appointments. However, 64% felt that they had not received enough visits from their Nanny Angel. Satisfaction with the nan childcare provider was high, but mothers wished the service had been available to them more often. Our study highlights the importance of providing childcare to mothers with inadequate support systems, so as to allow for greater adherence to treatment and medical appointments, and for more time to recover.

  9. Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering.

    Science.gov (United States)

    Nahid, Abdullah-Al; Mehrabi, Mohamad Ali; Kong, Yinan

    2018-01-01

    Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends on digital biomedical photography analysis such as histopathological images by doctors and physicians. Analyzing histopathological images is a nontrivial task, and decisions from investigation of these kinds of images always require specialised knowledge. However, Computer Aided Diagnosis (CAD) techniques can help the doctor make more reliable decisions. The state-of-the-art Deep Neural Network (DNN) has been recently introduced for biomedical image analysis. Normally each image contains structural and statistical information. This paper classifies a set of biomedical breast cancer images (BreakHis dataset) using novel DNN techniques guided by structural and statistical information derived from the images. Specifically a Convolutional Neural Network (CNN), a Long-Short-Term-Memory (LSTM), and a combination of CNN and LSTM are proposed for breast cancer image classification. Softmax and Support Vector Machine (SVM) layers have been used for the decision-making stage after extracting features utilising the proposed novel DNN models. In this experiment the best Accuracy value of 91.00% is achieved on the 200x dataset, the best Precision value 96.00% is achieved on the 40x dataset, and the best F -Measure value is achieved on both the 40x and 100x datasets.

  10. Network connection of distributed electricity production - a preliminary study

    International Nuclear Information System (INIS)

    Pleym, Anngjerd; Mogstad, Olve

    2002-01-01

    It will be necessary to lower the barriers for utilisation of distributed energy sources in order to increase the use of such sources in Norway. A relatively extensive R and D activity would be required for reaching this goal. Available Norwegian and international guidelines and technical requirements with respect to network connection of the distributed energy sources are studied with the aim of exposing needs for further R and D initiatives. A limited monitor is also carried out among the Norwegian network businesses with distributed units in their networks. The results show that the main focus in the R and D activities has drifted away from establishing guidelines for technical requirements for network coupling. Some verification work remains in investigating the usefulness of the existing international and the specific commercial network guidelines. For the network industry the main focus must be on the two following areas: 1) How will large concentrations of distributed production units connected to the same network influence the voltage quality and the delivery reliability in the networks. 2) How can the network businesses employ the distributed production units in their networks. A Nordic project (Finland, Sweden, Norway) which will study these problems is being established. Large national scientific institutions will be involved. The executive committee will consist of representatives from Finenergy, Elforsk and EBL Kompetanse and other financing institutions and industries. A Finnish business Merinova, is to be appointed to the project leadership

  11. Breast Cancer Chemoprevention: A Network Meta-Analysis of Randomized Controlled Trials.

    Science.gov (United States)

    Mocellin, Simone; Pilati, Pierluigi; Briarava, Marta; Nitti, Donato

    2016-02-01

    Several agents have been advocated for breast cancer primary prevention. However, few of them appear effective, the associated severe adverse effects limiting their uptake. We performed a comprehensive search for randomized controlled trials (RCTs) reporting on the ability of chemoprevention agents (CPAs) to reduce the incidence of primary breast carcinoma. Using network meta-analysis, we ranked CPAs based simultaneously on efficacy and acceptability (an inverse measure of toxicity). All statistical tests were two-sided. We found 48 eligible RCTs, enrolling 271 161 women randomly assigned to receive either placebo or one of 21 CPAs. Aromatase inhibitors (anastrozole and exemestane, considered a single CPA class because of the lack of between-study heterogeneity; relative risk [RR] = 0.468, 95% confidence interval [CI] = 0.346 to 0.634), arzoxifene (RR = 0.415, 95% CI = 0.253 to 0.682), lasofoxifene (RR = 0.208, 95% CI = 0.079 to 0.544), raloxifene (RR = 0.572, 95% CI = 0.372 to 0.881), tamoxifen (RR = 0.708, 95% CI = 0.595 to 0.842), and tibolone (RR = 0.317, 95% CI = 0.127 to 0.792) were statistically significantly associated with a therapeutic effect, which was restricted to estrogen receptor-positive tumors of postmenopausal women (except for tamoxifen, which is active also during premenopause). Network meta-analysis ranking showed that the new selective estrogen receptor modulators (SERMs) arzoxifene, lasofoxifene, and raloxifene have the best benefit-risk ratio. Aromatase inhibitors and tamoxifen ranked second and third, respectively. These results provide physicians and health care regulatory agencies with RCT-based evidence on efficacy and acceptability of currently available breast cancer CPAs; at the same time, we pinpoint how much work still remains to be done before pharmacological primary prevention becomes a routine option to reduce the burden of this disease. © The Author 2015. Published by Oxford University Press. All rights reserved. For

  12. Photospheric network from study of manganese lines

    Energy Technology Data Exchange (ETDEWEB)

    Elste, G; Teske, R G [Michigan Univ., Ann Arbor (USA). Dept. of Astronomy

    1978-10-01

    Area scans with the multi-channel magnetograph at the Kitt Peak McMath Telescope provided simultaneous measures of equivalent widths in two Mn lines, continuum intensity and longitudinal magnetic field component. Observations were carried out with apertures of 2.5 X 3.5 seconds arc and 1 X 1 seconds arc. For the network elements, which were identified using the magnetic field as tracer, the authors developed relationships between Isub(continuum), Wsub(lambda), Vsub(Doppler) and longitudinal field strength. With a minimum of assumptions it is possible to write from these observed relations an expression connecting true temperature perturbation in the line forming layers of the network to true longitudinal field strength. The results provide some constraints upon possible network models.

  13. Dosimetry studies during breast cancer radiation treatment

    International Nuclear Information System (INIS)

    Ahmed, M. O. M.

    2005-06-01

    Previous studies indicated that breast cancer is wildly spread especially in women as compared to men. It is increased after an age of thirty five years in women so it is important to study the effect of exposure to the radiation on the intact breast during the treatment of the breast suffering from cancer. In this work the scattered doses for the intact breast during the treatment of the breast suffering from cancer were measured and also the probability of inducing cancer in it is also discussed. The study was performed for a group of patients composed of twenty five females. Also the backscattered doses to the intact breast were measured for thirteen female patients. During the treatment using gamma rays from Co-60 source the two tangential fields (lateral and medial) were selected for the measurements. The results of exposure to gamma radiation for the lateral and medial fields showed that the mean scattered and backscattered doses to the intact breast were (241.26 cGY,47.49 cGY) and (371.6 cGY,385.4 cGY), respectively. Beside that the somatic risk of induced cancer to the intact breast was found to be (6 .1X10 -3 ,1.2X10 -3 ) and (9.29X10 -3 , 9.63X10 -3 ), respectively. From the results obtained it was concluded that the intact breast received small amounts of radiation doses which may lead to breast cancer for the healthy breast. The recommendations from the present study are to take care of radiation protection to the patient, and also to take care of the patient treatment conditions like temperature, pressure and humidity during the radiation exposure.(Author)

  14. Influence networks based on coexpression improve drug target discovery for the development of novel cancer therapeutics

    Science.gov (United States)

    2014-01-01

    Background The demand for novel molecularly targeted drugs will continue to rise as we move forward toward the goal of personalizing cancer treatment to the molecular signature of individual tumors. However, the identification of targets and combinations of targets that can be safely and effectively modulated is one of the greatest challenges facing the drug discovery process. A promising approach is to use biological networks to prioritize targets based on their relative positions to one another, a property that affects their ability to maintain network integrity and propagate information-flow. Here, we introduce influence networks and demonstrate how they can be used to generate influence scores as a network-based metric to rank genes as potential drug targets. Results We use this approach to prioritize genes as drug target candidates in a set of ER + breast tumor samples collected during the course of neoadjuvant treatment with the aromatase inhibitor letrozole. We show that influential genes, those with high influence scores, tend to be essential and include a higher proportion of essential genes than those prioritized based on their position (i.e. hubs or bottlenecks) within the same network. Additionally, we show that influential genes represent novel biologically relevant drug targets for the treatment of ER + breast cancers. Moreover, we demonstrate that gene influence differs between untreated tumors and residual tumors that have adapted to drug treatment. In this way, influence scores capture the context-dependent functions of genes and present the opportunity to design combination treatment strategies that take advantage of the tumor adaptation process. Conclusions Influence networks efficiently find essential genes as promising drug targets and combinations of targets to inform the development of molecularly targeted drugs and their use. PMID:24495353

  15. Mouse Models for Studying Oral Cancer: Impact in the Era of Cancer Immunotherapy.

    Science.gov (United States)

    Luo, J J; Young, C D; Zhou, H M; Wang, X J

    2018-04-01

    Model systems for oral cancer research have progressed from tumor epithelial cell cultures to in vivo systems that mimic oral cancer genetics, pathological characteristics, and tumor-stroma interactions of oral cancer patients. In the era of cancer immunotherapy, it is imperative to use model systems to test oral cancer prevention and therapeutic interventions in the presence of an immune system and to discover mechanisms of stromal contributions to oral cancer carcinogenesis. Here, we review in vivo mouse model systems commonly used for studying oral cancer and discuss the impact these models are having in advancing basic mechanisms, chemoprevention, and therapeutic intervention of oral cancer while highlighting recent discoveries concerning the role of immune cells in oral cancer. Improvements to in vivo model systems that highly recapitulate human oral cancer hold the key to identifying features of oral cancer initiation, progression, and invasion as well as molecular and cellular targets for prevention, therapeutic response, and immunotherapy development.

  16. Epidemiological characterization of oral cancer. Study Protocol.

    Directory of Open Access Journals (Sweden)

    Alejandra Fernández

    2015-04-01

    Full Text Available Oral cancer is a disease of high impact globally. It ranks as the sixth more frequent one among all types of cancer. In spite of being a widely known pathology and easy access to the diagnosis, the lack of epidemiological data reported in the last 10 years in Chile called attention to. At the global level, the World Health Organization (WHO has developed a project called “GLOBOCAN” in order to collect epidemiological data of the global cancer, between its data, highlights the high incidence and high rate of mortality in the male sex, parameter that shows tendency to replicate in both America and Chile. In consequence to these data, a narrative review of the literature concerning the epidemiological profile of the different forms of oral cancer in the past 15 years was done. The diagnosis of oral cancer crosses transversely the Dental Science, forcing us to establish triads of work between oral and maxillofacial surgeons, pathologists and dentists of the various specialties, so as to allow a timely research, appropriate biopsies and histopathological studies finishes with the purpose of, on the one hand, obtain timely and accurate diagnostics, in addition, maintaining the epidemiological indicators.

  17. Transport Network Technologies – Study and Testing

    DEFF Research Database (Denmark)

    Bozorgebrahimi, K.; Channegowda, M.; Colmenero, A.

    Following on from the theoretical research into Carrier Class Transport Network Technologies (CCTNTs) documented in DJ1.1.1, this report describes the extensive testing performed by JRA1 Task 1. The tests covered EoMPLS, Ethernet OAM, Synchronous Ethernet, PBB-TE, MPLS-TP, OTN and GMPLS...

  18. Chromatin organisation and cancer prognosis: a pan-cancer study.

    Science.gov (United States)

    Kleppe, Andreas; Albregtsen, Fritz; Vlatkovic, Ljiljana; Pradhan, Manohar; Nielsen, Birgitte; Hveem, Tarjei S; Askautrud, Hanne A; Kristensen, Gunnar B; Nesbakken, Arild; Trovik, Jone; Wæhre, Håkon; Tomlinson, Ian; Shepherd, Neil A; Novelli, Marco; Kerr, David J; Danielsen, Håvard E

    2018-03-01

    Chromatin organisation affects gene expression and regional mutation frequencies and contributes to carcinogenesis. Aberrant organisation of DNA has been correlated with cancer prognosis in analyses of the chromatin component of tumour cell nuclei using image texture analysis. As yet, the methodology has not been sufficiently validated to permit its clinical application. We aimed to define and validate a novel prognostic biomarker for the automatic detection of heterogeneous chromatin organisation. Machine learning algorithms analysed the chromatin organisation in 461 000 images of tumour cell nuclei stained for DNA from 390 patients (discovery cohort) treated for stage I or II colorectal cancer at the Aker University Hospital (Oslo, Norway). The resulting marker of chromatin heterogeneity, termed Nucleotyping, was subsequently independently validated in six patient cohorts: 442 patients with stage I or II colorectal cancer in the Gloucester Colorectal Cancer Study (UK); 391 patients with stage II colorectal cancer in the QUASAR 2 trial; 246 patients with stage I ovarian carcinoma; 354 patients with uterine sarcoma; 307 patients with prostate carcinoma; and 791 patients with endometrial carcinoma. The primary outcome was cancer-specific survival. In all patient cohorts, patients with chromatin heterogeneous tumours had worse cancer-specific survival than patients with chromatin homogeneous tumours (univariable analysis hazard ratio [HR] 1·7, 95% CI 1·2-2·5, in the discovery cohort; 1·8, 1·0-3·0, in the Gloucester validation cohort; 2·2, 1·1-4·5, in the QUASAR 2 validation cohort; 3·1, 1·9-5·0, in the ovarian carcinoma cohort; 2·5, 1·8-3·4, in the uterine sarcoma cohort; 2·3, 1·2-4·6, in the prostate carcinoma cohort; and 4·3, 2·8-6·8, in the endometrial carcinoma cohort). After adjusting for established prognostic patient characteristics in multivariable analyses, Nucleotyping was prognostic in all cohorts except for the prostate carcinoma

  19. Network-based identification of biomarkers coexpressed with multiple pathways.

    Science.gov (United States)

    Guo, Nancy Lan; Wan, Ying-Wooi

    2014-01-01

    Unraveling complex molecular interactions and networks and incorporating clinical information in modeling will present a paradigm shift in molecular medicine. Embedding biological relevance via modeling molecular networks and pathways has become increasingly important for biomarker identification in cancer susceptibility and metastasis studies. Here, we give a comprehensive overview of computational methods used for biomarker identification, and provide a performance comparison of several network models used in studies of cancer susceptibility, disease progression, and prognostication. Specifically, we evaluated implication networks, Boolean networks, Bayesian networks, and Pearson's correlation networks in constructing gene coexpression networks for identifying lung cancer diagnostic and prognostic biomarkers. The results show that implication networks, implemented in Genet package, identified sets of biomarkers that generated an accurate prediction of lung cancer risk and metastases; meanwhile, implication networks revealed more biologically relevant molecular interactions than Boolean networks, Bayesian networks, and Pearson's correlation networks when evaluated with MSigDB database.

  20. Awareness and uptake of direct-to-consumer genetic testing among cancer cases, their relatives, and controls: the Northwest Cancer Genetics Network.

    Science.gov (United States)

    Hall, Taryn O; Renz, Anne D; Snapinn, Katherine W; Bowen, Deborah J; Edwards, Karen L

    2012-07-01

    To determine if awareness of, interest in, and use of direct-to-consumer (DTC) genetic testing is greater in a sample of high-risk individuals (cancer cases and their relatives), compared to controls. Participants were recruited from the Northwest Cancer Genetics Network. A follow-up survey was mailed to participants to assess DTC genetic testing awareness, interest, and use. One thousand two hundred sixty-seven participants responded to the survey. Forty-nine percent of respondents were aware of DTC genetic testing. Of those aware, 19% indicated interest in obtaining and testing. Additional information supplied by respondents who reported use of DTC genetic tests indicated that 55% of these respondents likely engaged in clinical genetic testing, rather than DTC genetic testing. Awareness of DTC genetic testing was greater in our sample of high-risk individuals than in controls and population-based studies. Although interest in and use of these tests among cases in our sample were equivalent to other population-based studies, interest in testing was higher among relatives and people who self-referred for a registry focused on cancer than among cases and controls. Additionally, our results suggest that there may be some confusion about what constitutes DTC genetic testing.

  1. Earth Regimes Network Evolution Study (ERNESt): Introducing the Space Mobile Network

    Science.gov (United States)

    Menrad, Bob

    2016-01-01

    Speaker and Presenter at the Lincoln Laboratory Communications Workshop on April 5, 2016 at the Massachusetts Institute of Technology Lincoln Laboratory in Lexington, MA. A visual presentation titled Earth Regimes Network Evolution Study (ERNESt).

  2. Design principles for cancer therapy guided by changes in complexity of protein-protein interaction networks.

    Science.gov (United States)

    Benzekry, Sebastian; Tuszynski, Jack A; Rietman, Edward A; Lakka Klement, Giannoula

    2015-05-28

    The ever-increasing expanse of online bioinformatics data is enabling new ways to, not only explore the visualization of these data, but also to apply novel mathematical methods to extract meaningful information for clinically relevant analysis of pathways and treatment decisions. One of the methods used for computing topological characteristics of a space at different spatial resolutions is persistent homology. This concept can also be applied to network theory, and more specifically to protein-protein interaction networks, where the number of rings in an individual cancer network represents a measure of complexity. We observed a linear correlation of R = -0.55 between persistent homology and 5-year survival of patients with a variety of cancers. This relationship was used to predict the proteins within a protein-protein interaction network with the most impact on cancer progression. By re-computing the persistent homology after computationally removing an individual node (protein) from the protein-protein interaction network, we were able to evaluate whether such an inhibition would lead to improvement in patient survival. The power of this approach lied in its ability to identify the effects of inhibition of multiple proteins and in the ability to expose whether the effect of a single inhibition may be amplified by inhibition of other proteins. More importantly, we illustrate specific examples of persistent homology calculations, which correctly predict the survival benefit observed effects in clinical trials using inhibitors of the identified molecular target. We propose that computational approaches such as persistent homology may be used in the future for selection of molecular therapies in clinic. The technique uses a mathematical algorithm to evaluate the node (protein) whose inhibition has the highest potential to reduce network complexity. The greater the drop in persistent homology, the greater reduction in network complexity, and thus a larger

  3. A Bayesian network meta-analysis on second-line systemic therapy in advanced gastric cancer.

    Science.gov (United States)

    Zhu, Xiaofu; Ko, Yoo-Joung; Berry, Scott; Shah, Keya; Lee, Esther; Chan, Kelvin

    2017-07-01

    It is unclear which regimen is the most efficacious among the available therapies for advanced gastric cancer in the second-line setting. We performed a network meta-analysis to determine their relative benefits. We conducted a systematic review of randomized controlled trials (RCTs) through the MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases and American Society of Clinical Oncology abstracts up to June 2014 to identify phase III RCTs on advanced gastric cancer in the second-line setting. Overall survival (OS) data were the primary outcome of interest. Hazard ratios (HRs) were extracted from the publications on the basis of reported values or were extracted from survival curves by established methods. A Bayesian network meta-analysis was performed with WinBUGS to compare all regimens simultaneously. Eight RCTs (2439 patients) were identified and contained extractable data for quantitative analysis. Network meta-analysis showed that paclitaxel plus ramucirumab was superior to single-agent ramucirumab [OS HR 0.51, 95 % credible region (CR) 0.30-0.86], paclitaxel (OS HR 0.81, 95 % CR 0.68-0.96), docetaxel (OS HR 0.56, 95 % CR 0.33-0.94), and irinotecan (OS HR 0.71, 95 % CR 0.52-0.99). Paclitaxel plus ramucirumab also had an 89 % probability of being the best regimen among all these regimens. Single-agent ramucirumab, paclitaxel, docetaxel, and irinotecan were comparable to each other with respect to OS and were superior to best supportive care. This is the first network meta-analysis to compare all second-line regimens reported in phase III gastric cancer trials. The results suggest the paclitaxel plus ramucirumab combination is the most effective therapy and should be the reference regimen for future comparative trials.

  4. MicroRNAs as Regulator of Signaling Networks in Metastatic Colon Cancer

    Science.gov (United States)

    Wang, Jian; Du, Yong; Liu, Xiaoming; Cho, William C.; Yang, Yinxue

    2015-01-01

    MicroRNAs (miRNAs) are a class of small, noncoding RNA molecules capable of regulating gene expression translationally and/or transcriptionally. A large number of evidence have demonstrated that miRNAs have a functional role in both physiological and pathological processes by regulating the expression of their target genes. Recently, the functionalities of miRNAs in the initiation, progression, angiogenesis, metastasis, and chemoresistance of tumors have gained increasing attentions. Particularly, the alteration of miRNA profiles has been correlated with the transformation and metastasis of various cancers, including colon cancer. This paper reports the latest findings on miRNAs involved in different signaling networks leading to colon cancer metastasis, mainly focusing on miRNA profiling and their roles in PTEN/PI3K, EGFR, TGFβ, and p53 signaling pathways of metastatic colon cancer. The potential of miRNAs used as biomarkers in the diagnosis, prognosis, and therapeutic targets in colon cancer is also discussed. PMID:26064956

  5. MicroRNAs as Regulator of Signaling Networks in Metastatic Colon Cancer.

    Science.gov (United States)

    Wang, Jian; Du, Yong; Liu, Xiaoming; Cho, William C; Yang, Yinxue

    2015-01-01

    MicroRNAs (miRNAs) are a class of small, noncoding RNA molecules capable of regulating gene expression translationally and/or transcriptionally. A large number of evidence have demonstrated that miRNAs have a functional role in both physiological and pathological processes by regulating the expression of their target genes. Recently, the functionalities of miRNAs in the initiation, progression, angiogenesis, metastasis, and chemoresistance of tumors have gained increasing attentions. Particularly, the alteration of miRNA profiles has been correlated with the transformation and metastasis of various cancers, including colon cancer. This paper reports the latest findings on miRNAs involved in different signaling networks leading to colon cancer metastasis, mainly focusing on miRNA profiling and their roles in PTEN/PI3K, EGFR, TGFβ, and p53 signaling pathways of metastatic colon cancer. The potential of miRNAs used as biomarkers in the diagnosis, prognosis, and therapeutic targets in colon cancer is also discussed.

  6. MicroRNAs as Regulator of Signaling Networks in Metastatic Colon Cancer

    Directory of Open Access Journals (Sweden)

    Jian Wang

    2015-01-01

    Full Text Available MicroRNAs (miRNAs are a class of small, noncoding RNA molecules capable of regulating gene expression translationally and/or transcriptionally. A large number of evidence have demonstrated that miRNAs have a functional role in both physiological and pathological processes by regulating the expression of their target genes. Recently, the functionalities of miRNAs in the initiation, progression, angiogenesis, metastasis, and chemoresistance of tumors have gained increasing attentions. Particularly, the alteration of miRNA profiles has been correlated with the transformation and metastasis of various cancers, including colon cancer. This paper reports the latest findings on miRNAs involved in different signaling networks leading to colon cancer metastasis, mainly focusing on miRNA profiling and their roles in PTEN/PI3K, EGFR, TGFβ, and p53 signaling pathways of metastatic colon cancer. The potential of miRNAs used as biomarkers in the diagnosis, prognosis, and therapeutic targets in colon cancer is also discussed.

  7. LSD1 activates a lethal prostate cancer gene network independently of its demethylase function.

    Science.gov (United States)

    Sehrawat, Archana; Gao, Lina; Wang, Yuliang; Bankhead, Armand; McWeeney, Shannon K; King, Carly J; Schwartzman, Jacob; Urrutia, Joshua; Bisson, William H; Coleman, Daniel J; Joshi, Sunil K; Kim, Dae-Hwan; Sampson, David A; Weinmann, Sheila; Kallakury, Bhaskar V S; Berry, Deborah L; Haque, Reina; Van Den Eeden, Stephen K; Sharma, Sunil; Bearss, Jared; Beer, Tomasz M; Thomas, George V; Heiser, Laura M; Alumkal, Joshi J

    2018-05-01

    Medical castration that interferes with androgen receptor (AR) function is the principal treatment for advanced prostate cancer. However, clinical progression is universal, and tumors with AR-independent resistance mechanisms appear to be increasing in frequency. Consequently, there is an urgent need to develop new treatments targeting molecular pathways enriched in lethal prostate cancer. Lysine-specific demethylase 1 (LSD1) is a histone demethylase and an important regulator of gene expression. Here, we show that LSD1 promotes the survival of prostate cancer cells, including those that are castration-resistant, independently of its demethylase function and of the AR. Importantly, this effect is explained in part by activation of a lethal prostate cancer gene network in collaboration with LSD1's binding protein, ZNF217. Finally, that a small-molecule LSD1 inhibitor-SP-2509-blocks important demethylase-independent functions and suppresses castration-resistant prostate cancer cell viability demonstrates the potential of LSD1 inhibition in this disease.

  8. Uncovering robust patterns of microRNA co-expression across cancers using Bayesian Relevance Networks.

    Directory of Open Access Journals (Sweden)

    Parameswaran Ramachandran

    Full Text Available Co-expression networks have long been used as a tool for investigating the molecular circuitry governing biological systems. However, most algorithms for constructing co-expression networks were developed in the microarray era, before high-throughput sequencing-with its unique statistical properties-became the norm for expression measurement. Here we develop Bayesian Relevance Networks, an algorithm that uses Bayesian reasoning about expression levels to account for the differing levels of uncertainty in expression measurements between highly- and lowly-expressed entities, and between samples with different sequencing depths. It combines data from groups of samples (e.g., replicates to estimate group expression levels and confidence ranges. It then computes uncertainty-moderated estimates of cross-group correlations between entities, and uses permutation testing to assess their statistical significance. Using large scale miRNA data from The Cancer Genome Atlas, we show that our Bayesian update of the classical Relevance Networks algorithm provides improved reproducibility in co-expression estimates and lower false discovery rates in the resulting co-expression networks. Software is available at www.perkinslab.ca.

  9. Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

    Science.gov (United States)

    Li, Qiongge; Chan, Maria F

    2017-01-01

    Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuous improvement of patient safety and quality of care. Cumulative longitudinal QA measurements are valuable for understanding the behavior of the Linac and allow physicists to identify trends in the output and take preventive actions. In this study, artificial neural networks (ANNs) and autoregressive moving average (ARMA) time-series prediction modeling techniques were both applied to 5-year daily Linac QA data. Verification tests and other evaluations were then performed for all models. Preliminary results showed that ANN time-series predictive modeling has more advantages over ARMA techniques for accurate and effective applicability in the dosimetry and QA field. © 2016 New York Academy of Sciences.

  10. A Bayesian Approach to Measurement Bias in Networking Studies

    NARCIS (Netherlands)

    Zhu, Ling; Robinson, Scott E.; Torenvlied, René

    2014-01-01

    The study of managerial networking has been growing in the field of public administration; a field that analyzes how managers in open system organizations interact with different external actors and organizations. Coincident with this interest in managerial networking is the use of self-reported

  11. Statistical methods for studying the evolution of networks and behavior

    NARCIS (Netherlands)

    Schweinberger, Michael

    2007-01-01

    Studying longitudinal network and behavior data is important for understanding social processes, because human beings are interrelated, and the relationships among human beings (human networks) on one hand and human behavior on the other hand are not independent. The complex nature of longitudinal

  12. Detection of breast cancer using advanced techniques of data mining with neural networks

    International Nuclear Information System (INIS)

    Ortiz M, J. A.; Celaya P, J. M.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Lopez H, Y.; Ortiz R, J. M.

    2016-10-01

    The breast cancer is one of the biggest health problems worldwide, is the most diagnosed cancer in women and prevention seems impossible since its cause is unknown, due to this; the early detection has a key role in the patient prognosis. In developing countries such as Mexico, where access to specialized health services is minimal, the regular clinical review is infrequent and there are not enough radiologists; the most common form of detection of breast cancer is through self-exploration, but this is only detected in later stages, when is already palpable. For these reasons, the objective of the present work is the creation of a system of computer assisted diagnosis (CAD x) using information analysis techniques such as data mining and advanced techniques of artificial intelligence, seeking to offer a previous medical diagnosis or a second opinion, as if it was a second radiologist in order to reduce the rate of mortality from breast cancer. In this paper, advances in the design of computational algorithms using computer vision techniques for the extraction of features derived from mammograms are presented. Using data mining techniques of data mining is possible to identify patients with a high risk of breast cancer. With the information obtained from the mammography analysis, the objective in the next stage will be to establish a methodology for the generation of imaging bio-markers to establish a breast cancer risk index for Mexican patients. In this first stage we present results of the classification of patients with high and low risk of suffering from breast cancer using neural networks. (Author)

  13. Earthquake correlations and networks: A comparative study

    Science.gov (United States)

    Krishna Mohan, T. R.; Revathi, P. G.

    2011-04-01

    We quantify the correlation between earthquakes and use the same to extract causally connected earthquake pairs. Our correlation metric is a variation on the one introduced by Baiesi and Paczuski [M. Baiesi and M. Paczuski, Phys. Rev. E EULEEJ1539-375510.1103/PhysRevE.69.06610669, 066106 (2004)]. A network of earthquakes is then constructed from the time-ordered catalog and with links between the more correlated ones. A list of recurrences to each of the earthquakes is identified employing correlation thresholds to demarcate the most meaningful ones in each cluster. Data pertaining to three different seismic regions (viz., California, Japan, and the Himalayas) are comparatively analyzed using such a network model. The distribution of recurrence lengths and recurrence times are two of the key features analyzed to draw conclusions about the universal aspects of such a network model. We find that the unimodal feature of recurrence length distribution, which helps to associate typical rupture lengths with different magnitude earthquakes, is robust across the different seismic regions. The out-degree of the networks shows a hub structure rooted on the large magnitude earthquakes. In-degree distribution is seen to be dependent on the density of events in the neighborhood. Power laws, with two regimes having different exponents, are obtained with recurrence time distribution. The first regime confirms the Omori law for aftershocks while the second regime, with a faster falloff for the larger recurrence times, establishes that pure spatial recurrences also follow a power-law distribution. The crossover to the second power-law regime can be taken to be signaling the end of the aftershock regime in an objective fashion.

  14. Earthquake correlations and networks: A comparative study

    International Nuclear Information System (INIS)

    Krishna Mohan, T. R.; Revathi, P. G.

    2011-01-01

    We quantify the correlation between earthquakes and use the same to extract causally connected earthquake pairs. Our correlation metric is a variation on the one introduced by Baiesi and Paczuski [M. Baiesi and M. Paczuski, Phys. Rev. E 69, 066106 (2004)]. A network of earthquakes is then constructed from the time-ordered catalog and with links between the more correlated ones. A list of recurrences to each of the earthquakes is identified employing correlation thresholds to demarcate the most meaningful ones in each cluster. Data pertaining to three different seismic regions (viz., California, Japan, and the Himalayas) are comparatively analyzed using such a network model. The distribution of recurrence lengths and recurrence times are two of the key features analyzed to draw conclusions about the universal aspects of such a network model. We find that the unimodal feature of recurrence length distribution, which helps to associate typical rupture lengths with different magnitude earthquakes, is robust across the different seismic regions. The out-degree of the networks shows a hub structure rooted on the large magnitude earthquakes. In-degree distribution is seen to be dependent on the density of events in the neighborhood. Power laws, with two regimes having different exponents, are obtained with recurrence time distribution. The first regime confirms the Omori law for aftershocks while the second regime, with a faster falloff for the larger recurrence times, establishes that pure spatial recurrences also follow a power-law distribution. The crossover to the second power-law regime can be taken to be signaling the end of the aftershock regime in an objective fashion.

  15. From cell biology to immunology: Controlling metastatic progression of cancer via microRNA regulatory networks.

    Science.gov (United States)

    Park, Jae Hyon; Theodoratou, Evropi; Calin, George A; Shin, Jae Il

    2016-01-01

    Recently, the study of microRNAs has expanded our knowledge of the fundamental processes of cancer biology and the underlying mechanisms behind tumor metastasis. Extensive research in the fields of microRNA and its novel mechanisms of actions against various cancers has more recently led to the trial of a first cancer-targeted microRNA drug, MRX34. Yet, these microRNAs are mostly being studied and clinically trialed solely based on the understanding of their cell biologic effects, thus, neglecting the important immunologic effects that are sometimes opposite of the cell biologic effects. Here, we summarize both the cell biologic and immunologic effects of various microRNAs and discuss the importance of considering both effects before using them in clinical settings. We stress the importance of understanding the miRNA's effect on cancer metastasis from a "systems" perspective before developing a miRNA-targeted therapeutic in treating cancer metastasis.

  16. Comparative Study of Intelligent Systems for Management of GIT Cancers

    Directory of Open Access Journals (Sweden)

    Labib Nevine

    2017-01-01

    Full Text Available Intelligent Systems contribute in the management of different GIT cancer types. The paper discusses different types of intelligent systems, classified according to the medical task achieved, such as early detection, diagnosis and prognosis. It is found out that these types include rule-based and case-based expert systems, artificial neural networks, genetic algorithms, machine learning, in addition to data mining techniques and statistical methods. The study focuses on comparing between different techniques and tools used. The comparison results in identifying the benefits of using data mining techniques for the diagnosis task, since it is based on huge amounts of data in order to discover new patterns hence new predisposing factors. It also points out the use of expert systems in the prognosis task, since this task is mainly based on the specialist experience that should be transferred to less- experienced medical professionals. Based on the previous results, it is recommended to develop an Intelligent Tutoring System (ITS that focuses on the early diagnosis of GIT cancers, since managing the disease depends mainly on proper diagnosis, and also to build an expert system that helps transferring GIT cancers management knowledge to medical doctors in different hospitals.

  17. Risk of Salivary Gland Cancer After Childhood Cancer: A Report From the Childhood Cancer Survivor Study

    Energy Technology Data Exchange (ETDEWEB)

    Boukheris, Houda [Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States); Stovall, Marilyn [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Gilbert, Ethel S. [Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States); Stratton, Kayla L. [Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington (United States); Smith, Susan A.; Weathers, Rita [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Hammond, Sue [Department of Pathology, Ohio State University School of Medicine, Columbus, Ohio (United States); Mertens, Ann C. [Department of Pediatrics, Emory University, Atlanta, Georgia (United States); Donaldson, Sarah S. [Department of Radiation Oncology, Stanford University Medical Center, Stanford, California (United States); Armstrong, Gregory T.; Robison, Leslie L. [Department of Epidemiology and Cancer Control, St. Jude Children' s Research Hospital, Memphis, Tennessee (United States); Neglia, Joseph P. [Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota (United States); Inskip, Peter D., E-mail: inskippe@mail.nih.gov [Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States)

    2013-03-01

    Purpose: To evaluate effects of radiation therapy, chemotherapy, cigarette smoking, and alcohol consumption on the risk of second primary salivary gland cancer (SGC) in the Childhood Cancer Survivor Study (CCSS). Methods and Materials: Standardized incidence ratios (SIR) and excess absolute risks (EAR) of SGC in the CCSS were calculated using incidence rates from Surveillance, Epidemiology, and End Results population-based cancer registries. Radiation dose to the salivary glands was estimated based on medical records. Poisson regression was used to assess risks with respect to radiation dose, chemotherapy, smoking, and alcohol consumption. Results: During the time period of the study, 23 cases of SGC were diagnosed among 14,135 childhood cancer survivors. The mean age at diagnosis of the first primary cancer was 8.3 years, and the mean age at SGC diagnosis was 24.8 years. The incidence of SGC was 39-fold higher in the cohort than in the general population (SIR = 39.4; 95% CI = 25.4-57.8). The EAR was 9.8 per 100,000 person-years. Risk increased linearly with radiation dose (excess relative risk = 0.36/Gy; 95% CI = 0.06-2.5) and remained elevated after 20 years. There was no significant trend of increasing risk with increasing dose of chemotherapeutic agents, pack-years of cigarette smoking, or alcohol intake. Conclusion: Although the cumulative incidence of SGC was low, childhood cancer survivors treated with radiation experienced significantly increased risk for at least 2 decades after exposure, and risk was positively associated with radiation dose. Results underscore the importance of long-term follow up of childhood cancer survivors for the development of new malignancies.

  18. Risk of Salivary Gland Cancer After Childhood Cancer: A Report From the Childhood Cancer Survivor Study

    International Nuclear Information System (INIS)

    Boukheris, Houda; Stovall, Marilyn; Gilbert, Ethel S.; Stratton, Kayla L.; Smith, Susan A.; Weathers, Rita; Hammond, Sue; Mertens, Ann C.; Donaldson, Sarah S.; Armstrong, Gregory T.; Robison, Leslie L.; Neglia, Joseph P.; Inskip, Peter D.

    2013-01-01

    Purpose: To evaluate effects of radiation therapy, chemotherapy, cigarette smoking, and alcohol consumption on the risk of second primary salivary gland cancer (SGC) in the Childhood Cancer Survivor Study (CCSS). Methods and Materials: Standardized incidence ratios (SIR) and excess absolute risks (EAR) of SGC in the CCSS were calculated using incidence rates from Surveillance, Epidemiology, and End Results population-based cancer registries. Radiation dose to the salivary glands was estimated based on medical records. Poisson regression was used to assess risks with respect to radiation dose, chemotherapy, smoking, and alcohol consumption. Results: During the time period of the study, 23 cases of SGC were diagnosed among 14,135 childhood cancer survivors. The mean age at diagnosis of the first primary cancer was 8.3 years, and the mean age at SGC diagnosis was 24.8 years. The incidence of SGC was 39-fold higher in the cohort than in the general population (SIR = 39.4; 95% CI = 25.4-57.8). The EAR was 9.8 per 100,000 person-years. Risk increased linearly with radiation dose (excess relative risk = 0.36/Gy; 95% CI = 0.06-2.5) and remained elevated after 20 years. There was no significant trend of increasing risk with increasing dose of chemotherapeutic agents, pack-years of cigarette smoking, or alcohol intake. Conclusion: Although the cumulative incidence of SGC was low, childhood cancer survivors treated with radiation experienced significantly increased risk for at least 2 decades after exposure, and risk was positively associated with radiation dose. Results underscore the importance of long-term follow up of childhood cancer survivors for the development of new malignancies

  19. Formal modeling and analysis of ER-α associated Biological Regulatory Network in breast cancer

    Directory of Open Access Journals (Sweden)

    Samra Khalid

    2016-10-01

    Full Text Available Background Breast cancer (BC is one of the leading cause of death among females worldwide. The increasing incidence of BC is due to various genetic and environmental changes which lead to the disruption of cellular signaling network(s. It is a complex disease in which several interlinking signaling cascades play a crucial role in establishing a complex regulatory network. The logical modeling approach of René Thomas has been applied to analyze the behavior of estrogen receptor-alpha (ER-α associated Biological Regulatory Network (BRN for a small part of complex events that leads to BC metastasis. Methods A discrete model was constructed using the kinetic logic formalism and its set of logical parameters were obtained using the model checking technique implemented in the SMBioNet software which is consistent with biological observations. The discrete model was further enriched with continuous dynamics by converting it into an equivalent Petri Net (PN to analyze the logical parameters of the involved entities. Results In-silico based discrete and continuous modeling of ER-α associated signaling network involved in BC provides information about behaviors and gene-gene interaction in detail. The dynamics of discrete model revealed, imperative behaviors represented as cyclic paths and trajectories leading to pathogenic states such as metastasis. Results suggest that the increased expressions of receptors ER-α, IGF-1R and EGFR slow down the activity of tumor suppressor genes (TSGs such as BRCA1, p53 and Mdm2 which can lead to metastasis. Therefore, IGF-1R and EGFR are considered as important inhibitory targets to control the metastasis in BC. Conclusion The in-silico approaches allow us to increase our understanding of the functional properties of living organisms. It opens new avenues of investigations of multiple inhibitory targets (ER-α, IGF-1R and EGFR for wet lab experiments as well as provided valuable insights in the treatment of cancers

  20. Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

    Science.gov (United States)

    Zhou, Xionghui; Liu, Juan

    2014-01-01

    Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for

  1. Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks

    Science.gov (United States)

    Le, Minh Hung; Chen, Jingyu; Wang, Liang; Wang, Zhiwei; Liu, Wenyu; (Tim Cheng, Kwang-Ting; Yang, Xin

    2017-08-01

    multimodal CNNs but have not been carefully studied previously. (1) Given limited training data, how can these be augmented in sufficient numbers and variety for fine-tuning deep CNN networks for PCa diagnosis? (2) How can multimodal MP-MRI information be effectively combined in CNNs? (3) What is the impact of different CNN architectures on the accuracy of PCa diagnosis? Experimental results on extensive clinical data from 364 patients with a total of 463 PCa lesions and 450 identified noncancerous image patches demonstrate that our system can achieve a sensitivity of 89.85% and a specificity of 95.83% for distinguishing cancer from noncancerous tissues and a sensitivity of 100% and a specificity of 76.92% for distinguishing indolent PCa from CS PCa. This result is significantly superior to the state-of-the-art method relying on handcrafted features.

  2. Uranium miner lung cancer study. Final report

    International Nuclear Information System (INIS)

    Saccomanno, G.

    1986-06-01

    This study on uranium miners was started in 1957 and extended through June 30, 1986. It consisted of the routine screening of sputum from uranium miners of the Colorado Plateau, and collection of surgical and autopsy material from uranium miners who developed lung cancer. The projects resulted in: (1) Proof, for the first time, that cancer takes from 10 to 15 years to develop from the maximum accumulated carcinogenic insult and can be demonstrated through progressive cellular changes of the bronchial tree; (2) Development of a method for preserving, concentrating, and processing sputum samples. This is known as the Saccomanno Technique, and is used worldwide in diagnosing lung cancer; (3) Publication of the 1st and 2nd editions of a full-color textbook entitled ''Diagnostic Pulmonary Cytology;'' (4) Presentation of conclusive data on the effects of cigarette smoking and alpha progeny radiation on uranium miners, and information on safe radiation exposure levels; (5) Development of a brush-wash tube for collecting, concentrating, and preparing bronchial brushings and washings; (6) Development of cytological criteria which has improved sensitivity from 30% to about 60%; (7) Development of criteria for cytologic identification of carcinoma in situ, making it possible to diagnose lung cancer before it can be detected on chest x-ray

  3. Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network

    Science.gov (United States)

    Lebedeva, Galina; Sorokin, Anatoly; Faratian, Dana; Mullen, Peter; Goltsov, Alexey; Langdon, Simon P.; Harrison, David J.; Goryanin, Igor

    2012-01-01

    High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a

  4. Study on Dissemination Patterns in Location-Aware Gossiping Networks

    Science.gov (United States)

    Kami, Nobuharu; Baba, Teruyuki; Yoshikawa, Takashi; Morikawa, Hiroyuki

    We study the properties of information dissemination over location-aware gossiping networks leveraging location-based real-time communication applications. Gossiping is a promising method for quickly disseminating messages in a large-scale system, but in its application to information dissemination for location-aware applications, it is important to consider the network topology and patterns of spatial dissemination over the network in order to achieve effective delivery of messages to potentially interested users. To this end, we propose a continuous-space network model extended from Kleinberg's small-world model applicable to actual location-based applications. Analytical and simulation-based study shows that the proposed network achieves high dissemination efficiency resulting from geographically neutral dissemination patterns as well as selective dissemination to proximate users. We have designed a highly scalable location management method capable of promptly updating the network topology in response to node movement and have implemented a distributed simulator to perform dynamic target pursuit experiments as one example of applications that are the most sensitive to message forwarding delay. The experimental results show that the proposed network surpasses other types of networks in pursuit efficiency and achieves the desirable dissemination patterns.

  5. A STUDY ON NETWORK SECURITY TECHNIQUES

    OpenAIRE

    Dr.T.Hemalatha; Dr.G.Rashita Banu; Dr.Murtaza Ali

    2016-01-01

    Internet plays a vital role in our day today life. Data security in web application has become very crucial. The usage of internet becomes more and more in recent years. Through internet the information’s can be shared through many social networks like Facebook, twitter, LinkedIn, blogs etc. There is chance of hacking the data while sharing from one to one. To prevent the data being hacked there are so many techniques such as Digital Signature, Cryptography, Digital watermarking, Data Sanit...

  6. Reducing time-to-treatment in underserved Latinas with breast cancer: the Six Cities Study.

    Science.gov (United States)

    Ramirez, Amelie; Perez-Stable, Eliseo; Penedo, Frank; Talavera, Gregory; Carrillo, J Emilio; Fernández, María; Holden, Alan; Munoz, Edgar; San Miguel, Sandra; Gallion, Kipling

    2014-03-01

    The interaction of clinical and patient-level challenges following a breast cancer diagnosis can be a significant source of health care disparities. Failure to address specific cultural features that create or exacerbate barriers can lead to less-than optimal navigation results, specifically in Hispanic/Latino women. To address these disparities, the study leaders in San Antonio, Texas, and 5 other regional partners of the federally-funded Redes En Acción: The National Latino Cancer Research Network developed a culturally-tailored patient navigation intervention model for Latinas with breast cancer. Compared with control patients, a higher percentage of navigated subjects initiated treatment within 30 days (69.0% versus 46.3%, P = .029) and 60 days (97.6% versus 73.1%, P = .001) following their cancer diagnosis. Time from cancer diagnosis to first treatment was lower in the navigated group (mean, 22.22 days; median, 23.00 days) than controls (mean, 48.30 days; median, 33.00 days). These results were independent of cancer stage at diagnosis and numerous characteristics of cancer clinics and individual participants. Successful application of patient navigation increased the percentage of Latinas initiating breast cancer treatment within 30 and 60 days of diagnosis. This was achieved through navigator provision of services such as accompaniment to appointments, transportation arrangements, patient telephone support, patient-family telephone support, Spanish-English language translation, and assistance with insurance paperwork. © 2013 American Cancer Society.

  7. A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes.

    Science.gov (United States)

    Cheng, Feixiong; Zhao, Junfei; Fooksa, Michaela; Zhao, Zhongming

    2016-07-01

    Development of computational approaches and tools to effectively integrate multidomain data is urgently needed for the development of newly targeted cancer therapeutics. We proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. The underlying assumption is that a drug would have a high potential for anticancer indication if its up-/down-regulated genes from the Connectivity Map tended to be SMGs or their neighbors in the human protein interaction network. We assembled and curated 693 SMGs in 29 cancer types and found 121 proteins currently targeted by known anticancer or noncancer (repurposed) drugs. We found that the approved or experimental cancer drugs could potentially target these SMGs in 33.3% of the mutated cancer samples, and this number increased to 68.0% by drug repositioning through surveying exome-sequencing data in approximately 5000 normal-tumor pairs from The Cancer Genome Atlas. Furthermore, we identified 284 potential new indications connecting 28 cancer types and 48 existing drugs (adjusted P < .05), with a 66.7% success rate validated by literature data. Several existing drugs (e.g., niclosamide, valproic acid, captopril, and resveratrol) were predicted to have potential indications for multiple cancer types. Finally, we used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1). In summary, we demonstrated that our integrative network-based infrastructure is a promising strategy to identify potential druggable targets and uncover new indications for existing drugs to speed up molecularly targeted cancer therapeutics. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All

  8. Deep learning beyond cats and dogs: recent advances in diagnosing breast cancer with deep neural networks.

    Science.gov (United States)

    Burt, Jeremy R; Torosdagli, Neslisah; Khosravan, Naji; RaviPrakash, Harish; Mortazi, Aliasghar; Tissavirasingham, Fiona; Hussein, Sarfaraz; Bagci, Ulas

    2018-04-10

    Deep learning has demonstrated tremendous revolutionary changes in the computing industry and its effects in radiology and imaging sciences have begun to dramatically change screening paradigms. Specifically, these advances have influenced the development of computer-aided detection and diagnosis (CAD) systems. These technologies have long been thought of as "second-opinion" tools for radiologists and clinicians. However, with significant improvements in deep neural networks, the diagnostic capabilities of learning algorithms are approaching levels of human expertise (radiologists, clinicians etc.), shifting the CAD paradigm from a "second opinion" tool to a more collaborative utility. This paper reviews recently developed CAD systems based on deep learning technologies for breast cancer diagnosis, explains their superiorities with respect to previously established systems, defines the methodologies behind the improved achievements including algorithmic developments, and describes remaining challenges in breast cancer screening and diagnosis. We also discuss possible future directions for new CAD models that continue to change as artificial intelligence algorithms evolve.

  9. Integrative analyses reveal a long noncoding RNA-mediated sponge regulatory network in prostate cancer.

    Science.gov (United States)

    Du, Zhou; Sun, Tong; Hacisuleyman, Ezgi; Fei, Teng; Wang, Xiaodong; Brown, Myles; Rinn, John L; Lee, Mary Gwo-Shu; Chen, Yiwen; Kantoff, Philip W; Liu, X Shirley

    2016-03-15

    Mounting evidence suggests that long noncoding RNAs (lncRNAs) can function as microRNA sponges and compete for microRNA binding to protein-coding transcripts. However, the prevalence, functional significance and targets of lncRNA-mediated sponge regulation of cancer are mostly unknown. Here we identify a lncRNA-mediated sponge regulatory network that affects the expression of many protein-coding prostate cancer driver genes, by integrating analysis of sequence features and gene expression profiles of both lncRNAs and protein-coding genes in tumours. We confirm the tumour-suppressive function of two lncRNAs (TUG1 and CTB-89H12.4) and their regulation of PTEN expression in prostate cancer. Surprisingly, one of the two lncRNAs, TUG1, was previously known for its function in polycomb repressive complex 2 (PRC2)-mediated transcriptional regulation, suggesting its sub-cellular localization-dependent function. Our findings not only suggest an important role of lncRNA-mediated sponge regulation in cancer, but also underscore the critical influence of cytoplasmic localization on the efficacy of a sponge lncRNA.

  10. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes

    Directory of Open Access Journals (Sweden)

    Xinguo Lu

    2018-01-01

    Full Text Available With advances in next-generation sequencing(NGS technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profiles and copy number variation (CNV data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.

  11. Cancer risk at low doses of ionizing radiation. Artificial neural networks inference from atomic bomb survivors

    International Nuclear Information System (INIS)

    Sasaki, Masao S.; Tachibana, Akira; Takeda, Shunichi

    2014-01-01

    Cancer risk at low doses of ionizing radiation remains poorly defined because of ambiguity in the quantitative link to doses below 0.2 Sv in atomic bomb survivors in Hiroshima and Nagasaki arising from limitations in the statistical power and information available on overall radiation dose. To deal with these difficulties, a novel nonparametric statistics based on the ‘integrate-and-fire’ algorithm of artificial neural networks was developed and tested in cancer databases established by the Radiation Effects Research Foundation. The analysis revealed unique features at low doses that could not be accounted for by nominal exposure dose, including (1) the presence of a threshold that varied with organ, gender and age at exposure, and (2) a small but significant bumping increase in cancer risk at low doses in Nagasaki that probably reflects internal exposure to 239 Pu. The threshold was distinct from the canonical definition of zero effect in that it was manifested as negative excess relative risk, or suppression of background cancer rates. Such a unique tissue response at low doses of radiation exposure has been implicated in the context of the molecular basis of radiation–environment interplay in favor of recently emerging experimental evidence on DNA double-strand break repair pathway choice and its epigenetic memory by histone marking. (author)

  12. Study of the association between blood types and breast cancer among Isfahanian women with breast cancer

    Directory of Open Access Journals (Sweden)

    Amir Hossein Mirlohi Flavarjani

    2014-01-01

    Conclusion: According to the obtained results from this study, there was no relative frequency in specific blood group for these three types of cancer and the blood type could not be influenced as a risk factor in breast cancer.

  13. Discrimination of liver cancer in cellular level based on backscatter micro-spectrum with PCA algorithm and BP neural network

    Science.gov (United States)

    Yang, Jing; Wang, Cheng; Cai, Gan; Dong, Xiaona

    2016-10-01

    The incidence and mortality rate of the primary liver cancer are very high and its postoperative metastasis and recurrence have become important factors to the prognosis of patients. Circulating tumor cells (CTC), as a new tumor marker, play important roles in the early diagnosis and individualized treatment. This paper presents an effective method to distinguish liver cancer based on the cellular scattering spectrum, which is a non-fluorescence technique based on the fiber confocal microscopic spectrometer. Combining the principal component analysis (PCA) with back propagation (BP) neural network were utilized to establish an automatic recognition model for backscatter spectrum of the liver cancer cells from blood cell. PCA was applied to reduce the dimension of the scattering spectral data which obtained by the fiber confocal microscopic spectrometer. After dimensionality reduction by PCA, a neural network pattern recognition model with 2 input layer nodes, 11 hidden layer nodes, 3 output nodes was established. We trained the network with 66 samples and also tested it. Results showed that the recognition rate of the three types of cells is more than 90%, the relative standard deviation is only 2.36%. The experimental results showed that the fiber confocal microscopic spectrometer combining with the algorithm of PCA and BP neural network can automatically identify the liver cancer cell from the blood cells. This will provide a better tool for investigating the metastasis of liver cancers in vivo, the biology metabolic characteristics of liver cancers and drug transportation. Additionally, it is obviously referential in practical application.

  14. The Heritability of Breast Cancer among women in the Nordic Twin Study of Cancer

    DEFF Research Database (Denmark)

    Möller, Sören; Mucci, Lorelei A; Harris, Jennifer R

    2016-01-01

    and heritability of breast cancer among 21,054 monozygotic and 30,939 dizygotic female twin pairs from the Nordic Twin Study of Cancer, the largest twin study of cancer in the world. We accounted for left-censoring, right-censoring, as well as the competing risk of death. Results From 1943 through 2010, 3...

  15. Alcohol intake and mortality among survivors of colorectal cancer: The Cancer Prevention Study II Nutrition Cohort.

    Science.gov (United States)

    Yang, Baiyu; Gapstur, Susan M; Newton, Christina C; Jacobs, Eric J; Campbell, Peter T

    2017-06-01

    Alcohol consumption is associated with a higher risk of colorectal cancer, but to the authors' knowledge its influence on survival after a diagnosis of colorectal cancer is unclear. The authors investigated associations between prediagnosis and postdiagnosis alcohol intake with mortality among survivors of colorectal cancer. The authors identified 2458 men and women who were diagnosed with invasive, nonmetastatic colorectal cancer between 1992 (enrollment into the Cancer Prevention Study II Nutrition Cohort) and 2011. Alcohol consumption was self-reported at baseline and updated in 1997, 1999, 2003, and 2007. Postdiagnosis alcohol data were available for 1599 participants. Of the 2458 participants diagnosed with colorectal cancer, 1156 died during follow-up through 2012. Prediagnosis and postdiagnosis alcohol consumption were not found to be associated with all-cause mortality, except for an association between prediagnosis consumption of colorectal cancer-specific mortality, although there was some suggestion of increased colorectal cancer-specific mortality with postdiagnosis drinking (RR, 1.27 [95% CI, 0.87-1.86] for current drinking of colorectal cancer. The association between postdiagnosis drinking and colorectal cancer-specific mortality should be examined in larger studies of individuals diagnosed with nonmetastatic colorectal cancer. Cancer 2017;123:2006-2013. © 2017 American Cancer Society. © 2017 American Cancer Society.

  16. Men's perspectives of prostate cancer screening: A systematic review of qualitative studies.

    Directory of Open Access Journals (Sweden)

    Laura J James

    Full Text Available Prostate cancer is the most commonly diagnosed non-skin cancer in men. Screening for prostate cancer is widely accepted; however concerns regarding the harms outweighing the benefits of screening exist. Although patient's play a pivotal role in the decision making process, men may not be aware of the controversies regarding prostate cancer screening. Therefore we aimed to describe men's attitudes, beliefs and experiences of prostate cancer screening.Systematic review and thematic synthesis of qualitative studies on men's perspectives of prostate cancer screening. Electronic databases and reference lists were searched to October 2016.Sixty studies involving 3,029 men aged from 18-89 years, who had been screened for prostate cancer by Prostate Specific Antigen (PSA or Digital Rectal Examination (DRE and not screened, across eight countries were included. Five themes were identified: Social prompting (trusting professional opinion, motivation from family and friends, proximity and prominence of cancer; gaining decisional confidence (overcoming fears, survival imperative, peace of mind, mental preparation, prioritising wellbeing; preserving masculinity (bodily invasion, losing sexuality, threatening manhood, medical avoidance; avoiding the unknown and uncertainties (taboo of cancer-related death, lacking tangible cause, physiological and symptomatic obscurity, ambiguity of the procedure, confusing controversies; and prohibitive costs.Men are willing to participate in prostate cancer screening to prevent cancer and gain reassurance about their health, particularly when supported or prompted by their social networks or healthcare providers. However, to do so they needed to mentally overcome fears of losing their masculinity and accept the intrusiveness of screening, the ambiguities about the necessity and the potential for substantial costs. Addressing the concerns and priorities of men may facilitate informed decisions about prostate cancer screening

  17. Updating risk prediction tools: a case study in prostate cancer.

    Science.gov (United States)

    Ankerst, Donna P; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J; Feng, Ziding; Sanda, Martin G; Partin, Alan W; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M

    2012-01-01

    Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically, the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [-2]proPSA measured on an external case-control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. [Clues to differentiate pregnancy-associated breast cancer from those diagnosed in postpartum period: A monocentric experience of pregnancy-associated cancer network (CALG)].

    Science.gov (United States)

    Boudy, Anne-Sophie; Naoura, Iptissem; Zilberman, Sonia; Gligorov, Joseph; Chabbert-Buffet, Nathalie; Ballester, Marcos; Selleret, Lise; Darai, Emile

    2017-06-01

    To compare epidemiological, histological, therapeutic characteristics and prognosis of patients with breast cancer diagnosed during pregnancy with those diagnosed in postpartum period at a national expert center, « Cancer Associé à La Grossesse » network. Retrospective study of 108 patients with a pregnancy-associated breast cancer (PABC) between 2002 and 2016 comparing 51 patients with PABC during pregnancy and 57 patients with PABC of postpartum. Median gestational age at diagnosis was 16 weeks of gestation (WG). Median size (P=0.92), initial axillary pathology (P=0.29), histological type (P=0.33) and hormone receptor positive (P=0.93), were similar between groups. PABC during pregnancy overexpressed less frequently HER2 (12 % vs 36 %, P=0.003) and were less proliferant (Ki67≥15 %; 64 % vs 75 %, P=0.018) with less radical surgery (45 % vs 70 %, P=0.008). Sentinel lymph node biopsy was performed in 8 patients during pregnancy. Less patients of PABC during pregnancy received trastuzumab 12 % vs 37 %, P=0.003. Median delivery term was 37 WG. Median follow-up 3.2 vs 5.6 years (P=0.002) and recurrence rate for PABC during pregnancy and of postpartum were 3.2 vs 5.6 years (P=0.002) and 12 % vs 32 % (P=0.01), respectively. Our results emphasize histological, surgical and adjuvant treatment differences imposing differentiating PABC during pregnancy from those diagnosed in the postpartum period. Copyright © 2017 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

  19. Study protocol: The Intensive Care Outcome Network ('ICON' study

    Directory of Open Access Journals (Sweden)

    Barber Vicki S

    2008-06-01

    Full Text Available Abstract Background Extended follow-up of survivors of ICU treatment has shown many patients suffer long-term physical and psychological consequences that affect their health-related quality of life. The current lack of rigorous longitudinal studies means that the true prevalence of these physical and psychological problems remains undetermined. Methods/Design The ICON (Intensive Care Outcome Network study is a multi-centre, longitudinal study of survivors of critical illness. Patients will be recruited prior to hospital discharge from 20–30 ICUs in the UK and will be assessed at 3, 6, and 12 months following ICU discharge for health-related quality of life as measured by the Short Form-36 (SF-36 and the EuroQoL (EQ-5D; anxiety and depression as measured by the Hospital Anxiety and Depression Scale (HADS; and post traumatic stress disorder (PTSD symptoms as measured by the PTSD Civilian Checklist (PCL-C. Postal questionnaires will be used. Discussion The ICON study will create a valuable UK database detailing the prevalence of physical and psychological morbidity experienced by patients as they recover from critical illness. Knowledge of the prevalence of physical and psychological morbidity in ICU survivors is important because research to generate models of causality, prognosis and treatment effects is dependent on accurate determination of prevalence. The results will also inform economic modelling of the long-term burden of critical illness. Trial Registration ISRCTN69112866

  20. Type 2 diabetes mellitus is associated with increased risk of pancreatic cancer: A veteran administration registry study

    OpenAIRE

    Makhoul, Issam; Yacoub, Abdulraheem; Siegel, Eric

    2016-01-01

    Background: The etiology of pancreatic cancer remains elusive. Several studies have suggested a role for diabetes mellitus, but the magnitude of its contribution remains controversial. Objectives: Utilizing a large administrative database, this retrospective cohort study was designed to investigate the relationship between type 2 diabetes mellitus and pancreatic cancer. Patients and design: Using the Veterans Integrated Services Network 16 database, 322,614 subjects were enrolled in the study...

  1. Social network, autonomy, and adherence correlates of future time perspective in patients with head and neck cancer.

    Science.gov (United States)

    Baldensperger, Linda; Wiedemann, Amelie U; Wessel, Lauri; Keilholz, Ulrich; Knoll, Nina

    2018-06-01

    Socioemotional selectivity theory proposes that, with more limited future time perspective (FTP), the meaning of individual life goals shifts from instrumental and long-term goals, such as autonomy, to emotionally meaningful and short-term life goals, especially concerning meaningful social relationships. Adverse side effects of cancer therapy may conflict with the realization of emotionally meaningful goals leading to nonadherence. In line with the theoretical assumptions, this study aimed to investigate (a) associations among disease symptoms, physical and cognitive limitations, and FTP and (b) among FTP, family network size, striving for autonomy, and treatment adherence. One hundred fifty-seven patients (43-90 years; 75% male) with head and/or neck cancer of a German University Medical Centre completed a questionnaire measuring FTP, age, disease symptoms, physical and cognitive functioning, family network size, and treatment adherence. Autonomy was assessed with a card sort task. A structural equation model yielded an acceptable fit χ 2 (28) = 44.41, P = .025, χ 2 /df = 1.59, root mean square error of approximation = 0.06 (90% CI = 0.02, 0.09), Tucker-Lewis Index = 0.92, and Comparative Fit Index = 0.96. An increased level of disease symptoms and physical and cognitive limitations was related to a shorter subjective FTP. Furthermore, individuals with a limited FTP reported a smaller family network, a lowered quest for autonomy, and lower treatment adherence. Hypotheses derived from socioemotional selectivity theory were supported by the data. Longitudinal investigations should follow to corroborate findings and to focus on underlying mechanisms as improving patients FTP may play a crucial role in future disease management programs. Copyright © 2018 John Wiley & Sons, Ltd.

  2. Privacy Practices of Health Social Networking Sites: Implications for Privacy and Data Security in Online Cancer Communities.

    Science.gov (United States)

    Charbonneau, Deborah H

    2016-08-01

    While online communities for social support continue to grow, little is known about the state of privacy practices of health social networking sites. This article reports on a structured content analysis of privacy policies and disclosure practices for 25 online ovarian cancer communities. All of the health social networking sites in the study sample provided privacy statements to users, yet privacy practices varied considerably across the sites. The majority of sites informed users that personal information was collected about participants and shared with third parties (96%, n = 24). Furthermore, more than half of the sites (56%, n = 14) stated that cookies technology was used to track user behaviors. Despite these disclosures, only 36% (n = 9) offered opt-out choices for sharing data with third parties. In addition, very few of the sites (28%, n = 7) allowed individuals to delete their personal information. Discussions about specific security measures used to protect personal information were largely missing. Implications for privacy, confidentiality, consumer choice, and data safety in online environments are discussed. Overall, nurses and other health professionals can utilize these findings to encourage individuals seeking online support and participating in social networking sites to build awareness of privacy risks to better protect their personal health information in the digital age.

  3. A study of reactor monitoring method with neural network

    Energy Technology Data Exchange (ETDEWEB)

    Nabeshima, Kunihiko [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    2001-03-01

    The purpose of this study is to investigate the methodology of Nuclear Power Plant (NPP) monitoring with neural networks, which create the plant models by the learning of the past normal operation patterns. The concept of this method is to detect the symptom of small anomalies by monitoring the deviations between the process signals measured from an actual plant and corresponding output signals from the neural network model, which might not be equal if the abnormal operational patterns are presented to the input of the neural network. Auto-associative network, which has same output as inputs, can detect an kind of anomaly condition by using normal operation data only. The monitoring tests of the feedforward neural network with adaptive learning were performed using the PWR plant simulator by which many kinds of anomaly conditions can be easily simulated. The adaptively trained feedforward network could follow the actual plant dynamics and the changes of plant condition, and then find most of the anomalies much earlier than the conventional alarm system during steady state and transient operations. Then the off-line and on-line test results during one year operation at the actual NPP (PWR) showed that the neural network could detect several small anomalies which the operators or the conventional alarm system didn't noticed. Furthermore, the sensitivity analysis suggests that the plant models by neural networks are appropriate. Finally, the simulation results show that the recurrent neural network with feedback connections could successfully model the slow behavior of the reactor dynamics without adaptive learning. Therefore, the recurrent neural network with adaptive learning will be the best choice for the actual reactor monitoring system. (author)

  4. Improved survival for rectal cancer compared to colon cancer: the four cohort study.

    Science.gov (United States)

    Buchwald, Pamela; Hall, Claire; Davidson, Callum; Dixon, Liane; Dobbs, Bruce; Robinson, Bridget; Frizelle, Frank

    2018-03-01

    Colorectal cancer (CRC) is the third most common cancer worldwide. This study was undertaken to evaluate survival outcomes and changes of disease outcomes of CRC patients over the last decades. A retrospective analysis of CRC patients in Christchurch was performed in four patient cohorts at 5 yearly intervals; 1993-94, 1998-99, 2004-05 and 2009. Data on cancer location, stage, surgical and oncological treatment and survival were collected. Univariate, multivariate and Kaplan-Meier survival analysis were performed. There were 1391 patients (355, 317, 419 and 300 per cohort), 1037 colon and 354 rectal cancers, respectively. For colon cancer, right-sided cancers appeared more common in later cohorts (P = 0.01). There was a significant decrease in the number of permanent stomas for colon cancer patients (P = 0.001). There was an analogous trend for rectal cancers (P = 0.075). More CRC patients with stage IV disease were treated surgically (P = 0.001) and colon cancer stages I and II tended to have increased survival if operated by a colorectal surgeon (P = 0.06). Oncology referrals have increased remarkably (P = 0.001). Overall 56% of patients were alive at 5 years however rectal cancer patients had significantly better 5-year survival than those with colon cancer (P rectal cancer patients have a better 5-year survival than colon cancer patients. The improved survival with early stage colon cancers operated on by specialist colorectal surgeons needs further exploration. © 2016 Royal Australasian College of Surgeons.

  5. Benchmarking pathway interaction network for colorectal cancer to identify dysregulated pathways

    Directory of Open Access Journals (Sweden)

    Q. Wang

    Full Text Available Different pathways act synergistically to participate in many biological processes. Thus, the purpose of our study was to extract dysregulated pathways to investigate the pathogenesis of colorectal cancer (CRC based on the functional dependency among pathways. Protein-protein interaction (PPI information and pathway data were retrieved from STRING and Reactome databases, respectively. After genes were aligned to the pathways, each pathway activity was calculated using the principal component analysis (PCA method, and the seed pathway was discovered. Subsequently, we constructed the pathway interaction network (PIN, where each node represented a biological pathway based on gene expression profile, PPI data, as well as pathways. Dysregulated pathways were then selected from the PIN according to classification performance and seed pathway. A PIN including 11,960 interactions was constructed to identify dysregulated pathways. Interestingly, the interaction of mRNA splicing and mRNA splicing-major pathway had the highest score of 719.8167. Maximum change of the activity score between CRC and normal samples appeared in the pathway of DNA replication, which was selected as the seed pathway. Starting with this seed pathway, a pathway set containing 30 dysregulated pathways was obtained with an area under the curve score of 0.8598. The pathway of mRNA splicing, mRNA splicing-major pathway, and RNA polymerase I had the maximum genes of 107. Moreover, we found that these 30 pathways had crosstalks with each other. The results suggest that these dysregulated pathways might be used as biomarkers to diagnose CRC.

  6. Analysis of the molecular networks in androgen dependent and independent prostate cancer revealed fragile and robust subsystems.

    Directory of Open Access Journals (Sweden)

    Ryan Tasseff

    Full Text Available Androgen ablation therapy is currently the primary treatment for metastatic prostate cancer. Unfortunately, in nearly all cases, androgen ablation fails to permanently arrest cancer progression. As androgens like testosterone are withdrawn, prostate cancer cells lose their androgen sensitivity and begin to proliferate without hormone growth factors. In this study, we constructed and analyzed a mathematical model of the integration between hormone growth factor signaling, androgen receptor activation, and the expression of cyclin D and Prostate-Specific Antigen in human LNCaP prostate adenocarcinoma cells. The objective of the study was to investigate which signaling systems were important in the loss of androgen dependence. The model was formulated as a set of ordinary differential equations which described 212 species and 384 interactions, including both the mRNA and protein levels for key species. An ensemble approach was chosen to constrain model parameters and to estimate the impact of parametric uncertainty on model predictions. Model parameters were identified using 14 steady-state and dynamic LNCaP data sets taken from literature sources. Alterations in the rate of Prostatic Acid Phosphatase expression was sufficient to capture varying levels of androgen dependence. Analysis of the model provided insight into the importance of network components as a function of androgen dependence. The importance of androgen receptor availability and the MAPK/Akt signaling axes was independent of androgen status. Interestingly, androgen receptor availability was important even in androgen-independent LNCaP cells. Translation became progressively more important in androgen-independent LNCaP cells. Further analysis suggested a positive synergy between the MAPK and Akt signaling axes and the translation of key proliferative markers like cyclin D in androgen-independent cells. Taken together, the results support the targeting of both the Akt and MAPK

  7. Pathologically confirmed breast cancer in Malawi: a descriptive study

    African Journals Online (AJOL)

    2015-03-12

    Mar 12, 2015 ... Breast cancer is the most common female cancer in Africa, yet no published studies have ... receptor (HR) negative. However, HR ... to develop early diagnosis efforts to address high mortality rates. .... High Incidence of Triple-.

  8. Quasi-Prospective Study of Breast Cancer and Diet

    National Research Council Canada - National Science Library

    Hebert, James R; Adams, Swann A

    2006-01-01

    .... These factors may exert powerful influences on physiologic processes leading to cancer. This case-control study aims to investigate the relationship between physical activity, diet, adult weight history, and breast cancer...

  9. Quasi-Prospective Study of Breast Cancer and Diet

    National Research Council Canada - National Science Library

    Hebert, James

    2001-01-01

    This study aims to refine estimates of the effect of diet on breast cancer. Besides diet we will measure adult weight history and physical activity in women undergoing a diagnostic work-up for breast cancer...

  10. Quasi-Prospective Study of Breast Cancer and Diet

    National Research Council Canada - National Science Library

    Hebert, James

    2003-01-01

    .... These factors may exert powerful influences on physiologic processes leading to cancer. This case control study aims to investigate the relationship between physical activity, diet, and adult weight history and breast cancer...

  11. Quasi-Prospective Study of Breast Cancer and Diet

    National Research Council Canada - National Science Library

    Hebert, James R; Matthews, Chuck

    2005-01-01

    .... These factors may exert powerful influences on physiologic processes leading to cancer. This case control study aims to investigate the relationship between physical activity, diet, and adult weight history and breast cancer...

  12. [Application of cohort study in cancer prevention and control].

    Science.gov (United States)

    Dai, Min; Bai, Yana; Pu, Hongquan; Cheng, Ning; Li, Haiyan; He, Jie

    2016-03-01

    Cancer control is a long-term work. Cancer research and intervention really need the support of cohort study. In the recent years, more and more cohort studies on cancer control were conducted in China along with the increased ability of scientific research in China. Since 2010, Cancer Hospital, Chinese Academy of Medical Sciences, collaborated with Lanzhou University and the Worker' s Hospital of Jinchuan Group Company Limited, have carried out a large-scale cohort study on cancer, which covered a population of more than 50 000 called " Jinchang cohort". Since 2012, a National Key Public Health Project, "cancer screening in urban China" , has been conducted in Jinchang, which strengthened the Jinchang cohort study. Based on the Jinchang cohort study, historical cohort study, cross-sectional study and prospective cohort study have been conducted, which would provide a lot of evidence for the cancer control in China.

  13. Potential upstream regulators of cannabinoid receptor 1 signaling in prostate cancer: a Bayesian network analysis of data from a tissue microarray.

    Science.gov (United States)

    Häggström, Jenny; Cipriano, Mariateresa; Forshell, Linus Plym; Persson, Emma; Hammarsten, Peter; Stella, Nephi; Fowler, Christopher J

    2014-08-01

    The endocannabinoid system regulates cancer cell proliferation, and in prostate cancer a high cannabinoid CB1 receptor expression is associated with a poor prognosis. Down-stream mediators of CB1 receptor signaling in prostate cancer are known, but information on potential upstream regulators is lacking. Data from a well-characterized tumor tissue microarray were used for a Bayesian network analysis using the max-min hill-climbing method. In non-malignant tissue samples, a directionality of pEGFR (the phosphorylated form of the epidermal growth factor receptor) → CB1 receptors were found regardless as to whether the endocannabinoid metabolizing enzyme fatty acid amide hydrolase (FAAH) was included as a parameter. A similar result was found in the tumor tissue, but only when FAAH was included in the analysis. A second regulatory pathway, from the growth factor receptor ErbB2 → FAAH was also identified in the tumor samples. Transfection of AT1 prostate cancer cells with CB1 receptors induced a sensitivity to the growth-inhibiting effects of the CB receptor agonist CP55,940. The sensitivity was not dependent upon the level of receptor expression. Thus a high CB1 receptor expression alone does not drive the cells towards a survival phenotype in the presence of a CB receptor agonist. The data identify two potential regulators of the endocannabinoid system in prostate cancer and allow the construction of a model of a dysregulated endocannabinoid signaling network in this tumor. Further studies should be designed to test the veracity of the predictions of the network analysis in prostate cancer and other solid tumors. © 2014 The Authors. The Prostate published by Wiley Periodicals, Inc.

  14. Province wide clinical governance network for clinical audit for quality improvement in endometrial cancer management.

    Science.gov (United States)

    Mandato, Vincenzo Dario; Formisano, Debora; Pirillo, Debora; Ciarlini, Gino; Cerami, Lillo Bruno; Ventura, Alessandro; Spreafico, Lorenzo; Palmieri, Tamara; La Sala, Giovanni Battista; Abrate, Martino

    2012-01-01

    According to the hub-and-spoke model introduced in the Provincial Healthcare System of Reggio Emilia, early endometrial cancer is treated in peripheral low-volume hospitals (spokes) by general gynecologist, whereas more complex cancers are treated by gynecological oncologists at the main hospital (hub). To guarantee a uniformly high standard of care to all patients with endometrial cancer treated in hub and spoke hospitals of Reggio Emilia Province. The specialists of the 5 hospitals of Reggio Emilia Province instituted an inter hospital and multidisciplinary oncology group to write common and shared guidelines based on evidence-based medicine through the use of clinical audit. They valued the process indicators before and after guidelines introduction identifying the site of improvement and verifying the standard achievement. Diagnostic hysteroscopy use increased significantly from preguideline period, 53%, to postguideline period, 74%. Magnetic resonance use and accuracy increased significantly from preguideline to postguideline periods: 8.1% to 35.3% and 37.3% to 74.7%, respectively. Laparoscopy use increased from 1.6% (preguideline) to 18.6 (postguideline). Early surgical complications decreased from 16% (preguideline) to 9% (postguideline). Radiotherapy use increased from 14.% (preguideline) to 32.3% (postguideline). It is possible for a provincial oncology group to build an oncology network providing an improvement in the assistance of patients with endometrial cancer through the use of clinical audit. Clinical audit made it possible to obtain the full attendance of specialists of various disciplines involved in the treatment of endometrial cancer to optimize response time schematizing process.

  15. Studying Policy Transfer through the Lens of Social Network Analysis

    DEFF Research Database (Denmark)

    Staunæs, Dorthe; Brøgger, Katja; Steiner-Khamsi, Gita

    Studying Policy Transfer through the Lens of Social Network Analysis The panelists present the findings of a joint empirical research project carried out at Aarhus University (DPU/Copenhagen) and at Teachers College, Columbia University (New York). The research project succeeded to identify...... discursive networks of political stakeholders and policy advisors that were considered key actors in the Danish school reform. The research team investigated how these networks interrelate, change over time, and represent different constituents (government, academe, business), at times contradicting...... or collaborating with each other, respectively. Against the backdrop of globalization studies in comparative education, the research project attempted to identify borrowers, translators, and brokers of educational reform drawing on a complementary set of expertise from social network analysis methodology (Oren...

  16. Personal and Network Dynamics in Performance of Knowledge Workers: A Study of Australian Breast Radiologists.

    Directory of Open Access Journals (Sweden)

    Seyedamir Tavakoli Taba

    Full Text Available In this paper, we propose a theoretical model based upon previous studies about personal and social network dynamics of job performance. We provide empirical support for this model using real-world data within the context of the Australian radiology profession. An examination of radiologists' professional network topology through structural-positional and relational dimensions and radiologists' personal characteristics in terms of knowledge, experience and self-esteem is provided. Thirty one breast imaging radiologists completed a purpose designed questionnaire regarding their network characteristics and personal attributes. These radiologists also independently read a test set of 60 mammographic cases: 20 cases with cancer and 40 normal cases. A Jackknife free response operating characteristic (JAFROC method was used to measure the performance of the radiologists' in detecting breast cancers.Correlational analyses showed that reader performance was positively correlated with the social network variables of degree centrality and effective size, but negatively correlated with constraint and hierarchy. For personal characteristics, the number of mammograms read per year and self-esteem (self-evaluation positively correlated with reader performance. Hierarchical multiple regression analysis indicated that the combination of number of mammograms read per year and network's effective size, hierarchy and tie strength was the best fitting model, explaining 63.4% of the variance in reader performance. The results from this study indicate the positive relationship between reading high volumes of cases by radiologists and expertise development, but also strongly emphasise the association between effective social/professional interactions and informal knowledge sharing with high performance.

  17. US findings of bilateral primary breast cancer: Retrospective study

    International Nuclear Information System (INIS)

    Lou Li; Cong Xinli; Yu Guofang; Li Jichang; Ma Yuxiang

    2007-01-01

    Background: For women with breast cancer, the contralateral breast is at high risk. The bilateral cancers may be synchronous or metachronous. If the bilateral breast cancers have similar ultrasonography (US) appearances, the US findings of the first breast cancer (index cancer) might lead to early detection of the contralateral cancer. The purpose of this study was to identify the US characteristics of bilateral breast cancer and to determine whether bilateral breast cancers have similar US appearances and whether the US findings for one breast cancer might be predictive of the contralateral breast cancer. Methods: We retrospectively reviewed the US manifestations of 58 patients with surgically proven bilateral primary breast cancer and compared the contralateral cancer with the index cancer by evaluation the margin, shape, inside echoes, posterior attenuation, calcification and color flow signals of 58 lesion pairs to investigate whether the bilateral breast cancers have similar US appearances. Results: Bilateral primary breast cancers were more located in upper outer quadrant, frequently spiculation, taller than wide shape, with irregular margin, heterogeneous internal echo and acoustic shadowing, containing microcalcification and abundant color flow signals. The most common US appearances were taller than wide shape (75.0%, 87/116), irregular margins (79.3%, 92/116) and heterogeneous internal echo (86.2%, 100/116). Of the total 58 lesion pairs, 18 (31.0%) pairs had similar US characteristics, whereas 40 (69.0%) pairs had different US characteristics. Conclusions: US signs of the index cancer do not indicate the most likely appearance of the second cancer in the contralateral breast. Evaluation of the contralateral cancer should be performed without regard for the US findings for the index cancer

  18. Breast. cancer. Prognosis factors - preliminar study

    International Nuclear Information System (INIS)

    Rotstein, S.; Fonseca, N.M.

    1984-01-01

    A preliminar study of prognosis factors in 8 cases of breast cancer is made. Are used as parameters the dimension, the localization and the nuclear differentiation degree (gN) of the primary tumor, the vascular invasion and the axillary histologic status (pN) and the sinus histiocytosis phenomenon. Among the studied factors, have special importance the presence of vascular invasion and the negative sinus histiocytosis (minimal or absent sinus histiocytosis). Both phenomena are considered as an expression of potential systemic disease, independent of the clinical stage. Consequently the use of chemotherapy in the surgery complementation is preconized, to a best control of the disease. (author)

  19. Network graph analysis of gene-gene interactions in genome-wide association study data.

    Science.gov (United States)

    Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

    2012-12-01

    Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

  20. STUDY OF GASTROINTESTINAL CANCERS IN A TERTIARY CARE HOSPITAL

    Directory of Open Access Journals (Sweden)

    Rema Nair Sarkar

    2017-11-01

    Full Text Available BACKGROUND Cancer is one of the leading cause of death both in developed and developing countries. In India, it accounts for 0.3 million deaths per year. Cancers of lung, GIT and oral cancers dominated among men while breast, cervix, ovary and oral cavity were commonest cancer seen in women. Among the gastrointestinal cancers, cancers of the oesophagus, stomach, colon, rectum and liver cancers were commonest. The aim of the study is to evaluate the incidence of the various GIT cancers in a tertiary hospital of Coastal Andhra when compared to other studies. MATERIALS AND METHODS In this retrospective study, a total of 509 health records of patients affected by cancers were studied and relevant details noted. RESULTS A total of 509 cancer cases were reported in this period of 18 months (January 2016 - June 2017 of which 85 cases (16.3% were of Gastrointestinal (GIT cancers. The age group between 40 and 60 recorded the maximum incidence of 47 cancers (55.1%. The incidence of gastrointestinal cancers were significantly higher in the men (56 cases (65.8% than the women (29 cases (34.11%. The commonest site of GIT cancers was the colorectal region (30 cases (35.7%. The most common type of cancer seen was adenocarcinoma seen in 73 cases (85.8%. CONCLUSION Public education and awareness for the warning symptoms should be increased to prevent reduction of the life span and health caused by the gastrointestinal cancers with intense awareness drive using various means including social media undertaken to educate the public regarding the warning symptoms and screening of such group for GIT cancers.

  1. VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.

    Science.gov (United States)

    Jia, Peilin; Zhao, Zhongming

    2014-02-01

    A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data.

  2. Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

    Directory of Open Access Journals (Sweden)

    Sharma Animesh

    2007-01-01

    Full Text Available Abstract Background The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set. Results Our method discerned just seven biomarkers that precisely categorized the four subgroups of cancer both in training and blind samples. For the same problem, others suggested 19–94 genes. These seven biomarkers include three novel genes (NAB2, LSP1 and EHD1 – not identified by others with distinct class-specific signatures and important role in cancer biology, including cellular proliferation, transendothelial migration and trafficking of MHC class antigens. Interestingly, NAB2 is downregulated in other tumors including Non-Hodgkin lymphoma and Neuroblastoma but we observed moderate to high upregulation in a few cases of Ewing sarcoma and Rabhdomyosarcoma, suggesting that NAB2 might be mutated in these tumors. These genes can discover the subgroups correctly with unsupervised learning, can differentiate non-SRBCT samples and they perform equally well with other machine learning tools including support vector machines. These biomarkers lead to four simple human interpretable

  3. A COMPARATIVE STUDY OF CAREGIVER BURDEN IN CANCER CERVIX AND CANCER BREAST ILLNESSES

    Directory of Open Access Journals (Sweden)

    Srinivasagopalan, Nappinnai, Solayappan

    2015-07-01

    Full Text Available Background: Caregivers of individuals suffering from cancer illnesses are at risk of having subjected to mental health consequences. There is a paucity of data comparing the caregiver burden of cancer breast and cancer cervix patients. Aim: The aim of the present study is to compare the caregiver burden of cancer breast and cancer cervix patients. To study the association of caregiver burden with demographic factors like age, gender, duration of caregiving etc. Materials & Methods: This Cross sectional study is performed on the key relatives of patients of 31 cancer cervix and 31 cancer breast patients. Burden assessment schedule was used. Results: Our findings suggest burden is more in male caregivers of breast cancer patients. It is not so in caregivers of cancer cervix patients. Whenever the caregiver is closely related to the patients the burden is high in both groups. Whenever the burden scores were high the depression scores were also high. Treatment modalities as a whole correlates with burden scores in caregivers of breast cancer patients but not in cancer cervix patients. Conclusion: Caregivers with breast and cervical cancer patients are vulnerable if the caregiver is male, from low socioeconomical background, more closely related and when the patients received poor treatment modalities.

  4. Kids, Adolescents, and Young Adults Cancer Study-A Methodological Approach in Cancer Epidemiology Research

    International Nuclear Information System (INIS)

    Link, N. L.; Maurer, E.; Largent, J.; Kent, E.; Sender, E.; Culver, H. A.; Morris, R. A.; Sender, E.

    2009-01-01

    Advances have been made in treatment and outcomes for pediatric cancer. However adolescents and young adults (AYAs) with cancer have not experienced similar relative improvements. We undertook a study to develop the methodology necessary for epidemiologic cancer research in these age groups. Our goal was to create the Kids, Adolescents, and Young Adults Cancer (KAYAC) project to create a resource to address research questions relevant to this population. We used a combination of clinic and population-based ascertainment to enroll 111 cases aged 0-39 for this methodology development study. The largest groups of cancer types enrolled include: breast cancer, leukemia, lymphoma, and melanoma. The overall participation rate is 69.8% and varies by age and tumor type. The study included patients, mothers, and fathers. The methods used to establish this resource are described, and the values of the resource in studies of childhood and young adult cancer are outlined.

  5. Associations of Coffee Drinking and Cancer Mortality in the Cancer Prevention Study-II.

    Science.gov (United States)

    Gapstur, Susan M; Anderson, Rebecca L; Campbell, Peter T; Jacobs, Eric J; Hartman, Terryl J; Hildebrand, Janet S; Wang, Ying; McCullough, Marjorie L

    2017-10-01

    Background: Associations of coffee consumption with cancer mortality are inconsistent for many types of cancer, and confounding by smoking is an important concern. Methods: Cox proportional hazards regression was used to estimate multivariable-adjusted HRs for coffee consumption associated with death from all cancers combined and from specific cancer types among 922,896 Cancer Prevention Study-II participants ages 28-94 years who completed a four-page questionnaire and were cancer free at baseline in 1982. Results: During follow-up through 2012, there were 118,738 cancer-related deaths. There was a nonlinear association between coffee consumption and all-cancer death among current smokers and former smokers and no association among never smokers. Among nonsmokers, a 2 cup/day increase in coffee consumption was inversely associated with death from colorectal [HR = 0.97; 95% confidence interval (CI) 0.95-0.99], liver [HR = 0.92; 95% CI, 0.88-0.96], and female breast (HR = 0.97; 95% CI, 0.94-0.99) cancers, and positively associated with esophageal cancer-related death (HR = 1.07; 95% CI, 1.02-1.12). For head and neck cancer, a nonlinear inverse association was observed starting at 2-3 cups per day (HR = 0.72; 95% CI, 0.55-0.95), with similar associations observed at higher levels of consumption. Conclusions: These findings are consistent with many other studies that suggest coffee drinking is associated with a lower risk of colorectal, liver, female breast, and head and neck cancer. The association of coffee consumption with higher risk of esophageal cancer among nonsmokers in our study should be confirmed. Impact: These results underscore the importance of assessing associations between coffee consumption and cancer mortality by smoking status. Cancer Epidemiol Biomarkers Prev; 26(10); 1477-86. ©2017 AACR . ©2017 American Association for Cancer Research.

  6. Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends.

    Science.gov (United States)

    Jurca, Gabriela; Addam, Omar; Aksac, Alper; Gao, Shang; Özyer, Tansel; Demetrick, Douglas; Alhajj, Reda

    2016-04-26

    Breast cancer is a serious disease which affects many women and may lead to death. It has received considerable attention from the research community. Thus, biomedical researchers aim to find genetic biomarkers indicative of the disease. Novel biomarkers can be elucidated from the existing literature. However, the vast amount of scientific publications on breast cancer make this a daunting task. This paper presents a framework which investigates existing literature data for informative discoveries. It integrates text mining and social network analysis in order to identify new potential biomarkers for breast cancer. We utilized PubMed for the testing. We investigated gene-gene interactions, as well as novel interactions such as gene-year, gene-country, and abstract-country to find out how the discoveries varied over time and how overlapping/diverse are the discoveries and the interest of various research groups in different countries. Interesting trends have been identified and discussed, e.g., different genes are highlighted in relationship to different countries though the various genes were found to share functionality. Some text analysis based results have been validated against results from other tools that predict gene-gene relations and gene functions.

  7. Water supply network district metering theory and case study

    CERN Document Server

    Di Nardo, Armando; Di Mauro, Anna

    2013-01-01

    The management of a water supply network can be substantially improved defining permanent sectors or districts that enhances simpler water loss detection and pressure management. However, the water network partitioning may compromise water system performance, since some pipes are usually closed to delimit districts in order not to have too many metering stations, to decrease costs and simplify water balance. This may reduce the reliability of the whole system and not guarantee the delivery of water at the different network nodes. In practical applications, the design of districts or sectors is generally based on empirical approaches or on limited field experiences. The book proposes a design support methodology, based on graph theory principles and tested on real case study. The described methodology can help water utilities, professionals and researchers to define the optimal districts or sectors of a water supply network.

  8. Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD for brain cancer

    Directory of Open Access Journals (Sweden)

    Ying Huang

    2015-07-01

    Full Text Available The rapid development of new and emerging science & technologies (NESTs brings unprecedented challenges, but also opportunities. In this paper, we use bibliometric and social network analyses, at country, institution, and individual levels, to explore the patterns of scientific networking for a key nano area – nano-enabled drug delivery (NEDD. NEDD has successfully been used clinically to modulate drug release and to target particular diseased tissues. The data for this research come from a global compilation of research publication information on NEDD directed at brain cancer. We derive a family of indicators that address multiple facets of research collaboration and knowledge transfer patterns. Results show that: (1 international cooperation is increasing, but networking characteristics change over time; (2 highly productive institutions also lead in influence, as measured by citation to their work, with American institutes leading; (3 research collaboration is dominated by local relationships, with interesting information available from authorship patterns that go well beyond journal impact factors. Results offer useful technical intelligence to help researchers identify potential collaborators and to help inform R&D management and science & innovation policy for such nanotechnologies.

  9. Postoperative telegammatherapy of breast cancer (Dosimetric studies)

    Energy Technology Data Exchange (ETDEWEB)

    Todorov, J; Mitrov, G [Nauchno-Izsledovatelski Onkologichen Inst., Sofia (Bulgaria); Konstantinov, B; Dobrev, D [Meditsinska Akademiya, Sofia (Bulgaria). Nauchen Inst. po Rentgenologiya i Radiobiologiya

    1977-01-01

    The method employed for postoperative radiation therapy of breast cancer at the Radiologic Clinic of the Medical Academy in Sofia is described. Results are reported and discussed of dosimetric studies carried out with the T-100 on heterogeneous tissue-equivalent Rando phantom for dose distributions in the regional lymph basin and the underlying tissues and organs. The results show coincidence between calculated and measured doses in the regional lymph basin and the thoracic wall. It was demonstrated that maximal radiation loading (3600 to 5500 rad) occurs in the apical and the hilar lung area.

  10. Visual Network Asymmetry and Default Mode Network Function in ADHD: An fMRI Study

    Directory of Open Access Journals (Sweden)

    T. Sigi eHale

    2014-07-01

    Full Text Available Background: A growing body of research has identified abnormal visual information processing in ADHD. In particular, slow processing speed and increased reliance on visuo-perceptual strategies have become evident. Objective: The current study used recently developed fMRI methods to replicate and further examine abnormal rightward biased visual information processing in ADHD and to further characterize the nature of this effect; we tested its association to several large-scale distributed network systems. Method: We examined fMRI BOLD response during letter and location judgment tasks, and directly assessed visual network asymmetry and its association to large-scale networks using both a voxelwise and an averaged signal approach. Results: Initial within-group analyses revealed a pattern of left lateralized visual cortical activity in controls but right lateralized visual cortical activity in ADHD children. Direct analyses of visual network asymmetry confirmed atypical rightward bias in ADHD children compared to controls. This ADHD characteristic was atypically associated with reduced activation across several extra-visual networks, including the default mode network (DMN. We also found atypical associations between DMN activation and ADHD subjects’ inattentive symptoms and task performance. Conclusion: The current study demonstrated rightward VNA in ADHD during a simple letter discrimination task. This result adds an important novel consideration to the growing literature identifying abnormal visual processing in ADHD. We postulate that this characteristic reflects greater perceptual engagement of task-extraneous content, and that it may be a basic feature of less efficient top-down task-directed control over visual processing. We additionally argue that abnormal DMN function may contribute to this characteristic.

  11. Childhood Cancer Survivor Study: An Overview

    Science.gov (United States)

    ... To address this issue, the Children’s Oncology Group ( COG ) has prepared a resource for physicians called “ Long- ... of American Medical Association; see the journal article ) Breast cancer risk in childhood cancer survivors without a history ...

  12. Prospective study of blood metabolites associated with colorectal cancer risk.

    Science.gov (United States)

    Shu, Xiang; Xiang, Yong-Bing; Rothman, Nathaniel; Yu, Danxia; Li, Hong-Lan; Yang, Gong; Cai, Hui; Ma, Xiao; Lan, Qing; Gao, Yu-Tang; Jia, Wei; Shu, Xiao-Ou; Zheng, Wei

    2018-02-26

    Few prospective studies, and none in Asians, have systematically evaluated the relationship between blood metabolites and colorectal cancer risk. We conducted a nested case-control study to search for risk-associated metabolite biomarkers for colorectal cancer in an Asian population using blood samples collected prior to cancer diagnosis. Conditional logistic regression was performed to assess associations of metabolites with cancer risk. In this study, we included 250 incident cases with colorectal cancer and individually matched controls nested within two prospective Shanghai cohorts. We found 35 metabolites associated with risk of colorectal cancer after adjusting for multiple comparisons. Among them, 12 metabolites were glycerophospholipids including nine associated with reduced risk of colorectal cancer and three with increased risk [odds ratios per standard deviation increase of transformed metabolites: 0.31-1.98; p values: 0.002-1.25 × 10 -10 ]. The other 23 metabolites associated with colorectal cancer risk included nine lipids other than glycerophospholipid, seven aromatic compounds, five organic acids and four other organic compounds. After mutual adjustment, nine metabolites remained statistically significant for colorectal cancer. Together, these independently associated metabolites can separate cancer cases from controls with an area under the curve of 0.76 for colorectal cancer. We have identified that dysregulation of glycerophospholipids may contribute to risk of colorectal cancer. © 2018 UICC.

  13. Automatic Estimation of Volumetric Breast Density Using Artificial Neural Network-Based Calibration of Full-Field Digital Mammography: Feasibility on Japanese Women With and Without Breast Cancer.

    Science.gov (United States)

    Wang, Jeff; Kato, Fumi; Yamashita, Hiroko; Baba, Motoi; Cui, Yi; Li, Ruijiang; Oyama-Manabe, Noriko; Shirato, Hiroki

    2017-04-01

    Breast cancer is the most common invasive cancer among women and its incidence is increasing. Risk assessment is valuable and recent methods are incorporating novel biomarkers such as mammographic density. Artificial neural networks (ANN) are adaptive algorithms capable of performing pattern-to-pattern learning and are well suited for medical applications. They are potentially useful for calibrating full-field digital mammography (FFDM) for quantitative analysis. This study uses ANN modeling to estimate volumetric breast density (VBD) from FFDM on Japanese women with and without breast cancer. ANN calibration of VBD was performed using phantom data for one FFDM system. Mammograms of 46 Japanese women diagnosed with invasive carcinoma and 53 with negative findings were analyzed using ANN models learned. ANN-estimated VBD was validated against phantom data, compared intra-patient, with qualitative composition scoring, with MRI VBD, and inter-patient with classical risk factors of breast cancer as well as cancer status. Phantom validations reached an R 2 of 0.993. Intra-patient validations ranged from R 2 of 0.789 with VBD to 0.908 with breast volume. ANN VBD agreed well with BI-RADS scoring and MRI VBD with R 2 ranging from 0.665 with VBD to 0.852 with breast volume. VBD was significantly higher in women with cancer. Associations with age, BMI, menopause, and cancer status previously reported were also confirmed. ANN modeling appears to produce reasonable measures of mammographic density validated with phantoms, with existing measures of breast density, and with classical biomarkers of breast cancer. FFDM VBD is significantly higher in Japanese women with cancer.

  14. A clinicopathological study of asymptomatic gastric cancer.

    OpenAIRE

    Matsukuma, A.; Furusawa, M.; Tomoda, H.; Seo, Y.

    1996-01-01

    The clinicopathological profiles of 419 patients with asymptomatic gastric cancer (AGC) first detected by gastric screening, were reviewed and compared with those of the 1727 patients with symptomatic gastric cancer (SGC). The incidence of AGC increased gradually and has amounted to 30% of the total resected cases in recent years. About 75% of AGC cases were of early cancer and 84% were negative for lymph node metastases. In contrast, only 33% of SGC cases were of early cancer and 57% were no...

  15. Social network analysis in identifying influential webloggers: A preliminary study

    Science.gov (United States)

    Hasmuni, Noraini; Sulaiman, Nor Intan Saniah; Zaibidi, Nerda Zura

    2014-12-01

    In recent years, second generation of internet-based services such as weblog has become an effective communication tool to publish information on the Web. Weblogs have unique characteristics that deserve users' attention. Some of webloggers have seen weblogs as appropriate medium to initiate and expand business. These webloggers or also known as direct profit-oriented webloggers (DPOWs) communicate and share knowledge with each other through social interaction. However, survivability is the main issue among DPOW. Frequent communication with influential webloggers is one of the way to keep survive as DPOW. This paper aims to understand the network structure and identify influential webloggers within the network. Proper understanding of the network structure can assist us in knowing how the information is exchanged among members and enhance survivability among DPOW. 30 DPOW were involved in this study. Degree centrality and betweenness centrality measurement in Social Network Analysis (SNA) were used to examine the strength relation and identify influential webloggers within the network. Thus, webloggers with the highest value of these measurements are considered as the most influential webloggers in the network.

  16. Cervical cancer: a qualitative study on subjectivity, family, gender and health services.

    Science.gov (United States)

    Villafuerte, Blanca E Pelcastre; Gómez, Laura L Tirado; Betancourt, Alejandro Mohar; Cervantes, Malaquías López

    2007-03-01

    In 2002, cervical cancer was one of the leading causes of death in Mexico. Quantitative techniques allowed for the identification of socioeconomic, behavioral and biological characteristics that are part of its etiology. However such characteristics, are inadequate to explain sufficiently the role that emotions, family networks and socially-constructed categories such as gender play in the demand and utilization of health services for cervical cancer diagnosis and treatment and neither the timely undertaking of preventive actions, such as getting a PAP smear or seeking adequate and continuous treatment. A qualitative study was carried out to analyze the role of different social and cultural factors in the timely detection of cervical cancer. As part of a multi-level, multi-method research effort, this particular study was based on individual interviews with women diagnosed with cervical cancer (identified as the "cases"), their female friends and relatives (identified as the "controls") and the cases' husbands. The results showed that both: denial and fear are two important components that regulate the behavior of both the women and their partners. Women with a small support network may have limited opportunities for taking action in favor of their own health and wellbeing. Women tend not to worry about their health, in general and neither about cervical cancer in particular, as a consequence of their conceptualizations regarding their body and feminine identify - both of which are socially determined. Furthermore, it is necessary to improve the quality of information provided in health services.

  17. P53 expression in prostatic cancer: an immunohistochemical study

    International Nuclear Information System (INIS)

    Al-Nuaimy, W.M.; Al-Allaf, L.I.; Alnaimi, H.A.

    2011-01-01

    Prostate cancer is the most common malignancy in men and second leading cause of cancer death in the Western world. P53 alterations are the most frequent genetic changes in human cancers. Mutation of the p53 gene has been implicated in the development of >50% of all human cancer. The current study aims at evaluating the immuno-histochemical expression of p53 protein in patients with cancer of prostate, as prognostic parameter in correlation with other parameters including PSA receptors, and to correlate the results with those of other studies. (authors).

  18. Study of co-authorship network of papers in the Journal of Research in Medical Sciences using social network analysis

    Directory of Open Access Journals (Sweden)

    Firoozeh Zare-Farashbandi

    2014-01-01

    Full Text Available Background: Co-authorship is one of the most tangible forms of research collaboration. A co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. The present research using the social network analysis studied co-authorship network of 681 articles published in Journal of Research in Medical Sciences (JRMS during 2008-2012. Materials and Methods: The study was carried out with the scientometrics approach and using co-authorship network analysis of authors. The topology of the co-authorship network of 681 published articles in JRMS between 2008 and 2012 was analyzed using macro-level metrics indicators of network analysis such as density, clustering coefficient, components and mean distance. In addition, in order to evaluate the performance of each authors and countries in the network, the micro-level indicators such as degree centrality, closeness centrality and betweenness centrality as well as productivity index were used. The UCINET and NetDraw softwares were used to draw and analyze the co-authorship network of the papers. Results: The assessment of the authors productivity in this journal showed that the first ranks were belonged to only five authors, respectively. Furthermore, analysis of the co-authorship of the authors in the network demonstrated that in the betweenness centrality index, three authors of them had the good position in the network. They can be considered as the network leaders able to control the flow of information in the network compared with the other members based on the shortest paths. On the other hand, the key role of the network according to the productivity and centrality indexes was belonged to Iran, Malaysia and United States of America. Conclusion: Co-authorship network of JRMS has the characteristics of a small world network. In addition, the theory of 6° separation is valid in this network was also true.

  19. Perceived religiousness is protective for colorectal cancer: data from the Melbourne Colorectal Cancer Study.

    OpenAIRE

    Kune, G A; Kune, S; Watson, L F

    1993-01-01

    The perceived or self-reported degree of 'religiousness' was obtained by interview from 715 colorectal cancer patients and 727 age/sex matched community controls, as part of a large, comprehensive population-based study of colorectal cancer incidence, aetiology and survival (The Melbourne Colorectal Cancer Study) conducted in Melbourne, Australia. Self-reported or perceived 'religiousness', as defined in the study, was a statistically significant protective factor [relative risk (RR) = 0.70, ...

  20. Plant sterol intakes and colorectal cancer risk in the Netherlands : cohort study on diet and cancer

    NARCIS (Netherlands)

    Normén, A.L.; Brants, H.A.M.; Voorrips, L.E.; Andersson, H.A.; Brandt, P.A. van den

    2001-01-01

    Background: Plant sterols in vegetable foods might prevent colorectal cancer. Objective: The objective was to study plant sterol intakes in relation to colorectal cancer risk in an epidemiologic study. Design: The study was performed within the framework of the Netherlands Cohort Study on Diet and

  1. A Study of Rank Defect and Network Effect in Processing the CMONOC Network on Bernese

    Directory of Open Access Journals (Sweden)

    Weiwei Wu

    2018-02-01

    Full Text Available High-precision GPS data processing on Bernese has been employed to routinely resolve daily position solutions of GPS stations in the Crustal Movement Observation Network of China (CMONOC. The rank-deficient problems of the normal equation (NEQ system and the network effect on the frame alignment of NEQs in the processing of CMONOC data on Bernese still present difficulties. In this study, we diagnose the rank-deficient problems of the original NEQ, review the efficiency of the controlled datum removal (CDR method in filtering out the three frame-origin-related datum contents, investigate the reliabilities of the inherited frame orientation and scale information from the fixation of the GPS satellite orbits and the Earth rotation parameters in establishing the NEQ of the CMONOC network on Bernese, and analyze the impact of the network effect on the position time series of GPS stations. Our results confirm the nonsingularity of the original NEQ and the efficiency of the CDR filtering in resolving the rank-deficient problems; show that the frame origin parameters are weakly defined and should be stripped off, while the frame orientation and scale parameters should be retained due to their insufficient redefinition from the minimal constraint (MC implementation through inhomogeneous and asymmetrical fiducial networks; and reveal the superiority of a globally distributed fiducial network for frame alignment of the reconstructed NEQs via No-Net-Translation (NNT MC conditions. Finally, we attribute the two apparent discontinuities in the position time series to the terrestrial reference frame (TRF conversions of the GPS satellite orbits, and identify it as the orbit TRF effect.

  2. Work functioning trajectories in cancer patients: Results from the longitudinal Work Life after Cancer (WOLICA) study.

    Science.gov (United States)

    Dorland, Heleen F; Abma, Femke I; Roelen, Corné A M; Stewart, Roy E; Amick, Benjamin C; Ranchor, Adelita V; Bültmann, Ute

    2017-11-01

    More than 60% of cancer patients are able to work after cancer diagnosis. However, little is known about their functioning at work. Therefore, the aims of this study were to (1) identify work functioning trajectories in the year following return to work (RTW) in cancer patients and (2) examine baseline sociodemographic, health-related and work-related variables associated with work functioning trajectories. This longitudinal cohort study included 384 cancer patients who have returned to work after cancer diagnosis. Work functioning was measured at baseline, 3, 6, 9 and 12 months follow-up. Latent class growth modeling (LCGM) was used to identify work functioning trajectories. Associations of baseline variables with work functioning trajectories were examined using univariate and multivariate analyses. LCGM analyses with cancer patients who completed on at least three time points the Work Role Functioning Questionnaire (n = 324) identified three work functioning trajectories: "persistently high" (16% of the sample), "moderate to high" (54%) and "persistently low" work functioning (32%). Cancer patients with persistently high work functioning had less time between diagnosis and RTW and had less often a changed meaning of work, while cancer patients with persistently low work functioning reported more baseline cognitive symptoms compared to cancer patients in the other trajectories. This knowledge has implications for cancer care and guidance of cancer patients at work. © 2017 UICC.

  3. Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case

    Directory of Open Access Journals (Sweden)

    Guang Hu

    2017-01-01

    Full Text Available The overall topology and interfacial interactions play key roles in understanding structural and functional principles of protein complexes. Elastic Network Model (ENM and Protein Contact Network (PCN are two widely used methods for high throughput investigation of structures and interactions within protein complexes. In this work, the comparative analysis of ENM and PCN relative to hemoglobin (Hb was taken as case study. We examine four types of structural and dynamical paradigms, namely, conformational change between different states of Hbs, modular analysis, allosteric mechanisms studies, and interface characterization of an Hb. The comparative study shows that ENM has an advantage in studying dynamical properties and protein-protein interfaces, while PCN is better for describing protein structures quantitatively both from local and from global levels. We suggest that the integration of ENM and PCN would give a potential but powerful tool in structural systems biology.

  4. Value Assessment of Distribution Network Reconfiguration: A Danish Case Study

    DEFF Research Database (Denmark)

    Vaskantiras, Georgios; You, Shi

    2016-01-01

    . This paper presents a case study-based analysis to explore the potential value of reconfiguration in detail. The study is performed using a 10kV distribution grid of Denmark, while reconfiguration is applied to minimize the energy losses under both normal and post-fault conditions. The results show......Distribution network reconfiguration is a mechanism that can improve the distribution system performance from multiple perspectives. In the context of smart grid wherein the degrees of automation and intelligence are high, the potential value of network reconfiguration can be significant...

  5. Eleventh Hour Network+ Exam N10-004 Study Guide

    CERN Document Server

    Alpern, Naomi

    2009-01-01

    The 11th Hour Network+ Study Guide is keyed to the N10-004 revision of the CompTIA Network+ exam. This book is streamlined to include only core certification information and is presented for ease of last-minute studying. Main objectives of the exam are covered with key concepts highlighted. ..: ..; Fast Facts quickly review fundamentals ..; Exam Warnings highlight particularly tough sections of the exam ..; Crunch Time sidebars point out key concepts to remember ..; Did You Know? sidebars cover sometimes forgotten details ..; Top Five Toughest Questions and answers help you to prepare ..

  6. Alcohol intake and cigarette smoking and risk of a contralateral breast cancer: The Women's Environmental Cancer and Radiation Epidemiology Study

    DEFF Research Database (Denmark)

    Knight, J.A.; Bernstein, L.; Largent, J.

    2009-01-01

    Women with primary breast cancer are at increased risk of developing second primary breast cancer. Few studies have evaluated risk factors for the development of asynchronous contralateral breast cancer in women with breast cancer. In the Women's Environmental Cancer and Radiation Epidemiology St...

  7. A Comparison of Regorafenib and TAS-102 for Metastatic Colorectal Cancer: A Systematic Review and Network Meta-analysis.

    Science.gov (United States)

    Abrahao, Ana B K; Ko, Yoo-Joung; Berry, Scott; Chan, Kelvin K W

    2017-11-21

    Regorafenib and TAS-102 have shown to be superior to placebo in refractory metastatic colorectal cancer. However, no studies have directly compared both drugs. Giving the lack of standard options in this scenario, a systematic review to compare the efficacy and safety of regorafenib and TAS-102 was performed. A systematic review using the PubMed, Medline, Embase, Scopus, and Cochrane databases to identify published and unpublished studies up to November 2015 for randomized controlled trials for patients with metastatic colorectal cancer, involving regorafenib or TAS-102, was performed. Data including overall survival, progression-free survival, and toxicity were extracted. Pairwise direct meta-analyses (regorafenib vs. placebo and TAS-102 vs. placebo) and indirect comparison (regorafenib vs. TAS-102) using network meta-analyses methods to preserve randomization were performed using random effects. Three randomized controlled trials fulfilled eligibility criteria (regorafenib monotherapy for previously treated metastatic colorectal cancer [CORRECT]: an international, multicentre, randomised, pacebo-controlled, phase 3 trial, regorafenib plus best supportive care versus placebo plus best supportive care in Asian patients with previously treated metastatic colorectal cancer [CONCUR]: a randomised, double-blind, placebo-controlled, phase 3 trial, and randomized trial of TAS-102 for refractory metastatic colorectal cancer [RECOURSE] trials) involving 1764 patients (regorafenib, 641; TAS-102, 534; placebo, 589). Subgroups of patients (1659) who had not received prior regorafenib or TAS-102 were used to perform meta-analyses for efficacy. In the indirect comparison, no statistically significant differences were observed between regorafenib and TAS-102 in overall survival (hazard ratio, 0.96; 95% confidence interval [CI], 0.57-1.66; P = .91) or progression-free survival (hazard ratio, 0.85; 95% CI, 0.40-1.81; P = .67). However, regorafenib has statistically more all

  8. SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu; Chao, KSC; Parashar, Bhupesh; Chang, Jenghwa [Weill Cornell Medical College, NY, NY (United States)

    2014-06-01

    Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT, status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation.

  9. AUTOMATED DETECTION OF MITOTIC FIGURES IN BREAST CANCER HISTOPATHOLOGY IMAGES USING GABOR FEATURES AND DEEP NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Maqlin Paramanandam

    2016-11-01

    Full Text Available The count of mitotic figures in Breast cancer histopathology slides is the most significant independent prognostic factor enabling determination of the proliferative activity of the tumor. In spite of the strict protocols followed, the mitotic counting activity suffers from subjectivity and considerable amount of observer variability despite being a laborious task. Interest in automated detection of mitotic figures has been rekindled with the advent of Whole Slide Scanners. Subsequently mitotic detection grand challenge contests have been held in recent years and several research methodologies developed by their participants. This paper proposes an efficient mitotic detection methodology for Hematoxylin and Eosin stained Breast cancer Histopathology Images using Gabor features and a Deep Belief Network- Deep Neural Network architecture (DBN-DNN. The proposed method has been evaluated on breast histopathology images from the publicly available dataset from MITOS contest held at the ICPR 2012 conference. It contains 226 mitoses annotated on 35 HPFs by several pathologists and 15 testing HPFs, yielding an F-measure of 0.74. In addition the said methodology was also tested on 3 slides from the MITOSIS- ATYPIA grand challenge held at the ICPR 2014 conference, an extension of MITOS containing 749 mitoses annotated on 1200 HPFs, by pathologists worldwide. This study has employed 3 slides (294 HPFs from the MITOS-ATYPIA training dataset in its evaluation and the results showed F-measures 0.65, 0.72and 0.74 for each slide. The proposed method is fast and computationally simple yet its accuracy and specificity is comparable to the best winning methods of the aforementioned grand challenges

  10. SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

    International Nuclear Information System (INIS)

    Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu; Chao, KSC; Parashar, Bhupesh; Chang, Jenghwa

    2014-01-01

    Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT, status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation

  11. Familial Risk and Heritability of Colorectal Cancer in the Nordic Twin Study of Cancer

    DEFF Research Database (Denmark)

    Graff, Rebecca E; Möller, Sören; Passarelli, Michael N

    2017-01-01

    included 39,990 monozygotic and 61,443 same-sex dizygotic twins from the Nordic Twin Study of Cancer. We compared each cancer's risk in twins of affected co-twins relative to the cohort risk (familial risk ratio; FRR). We then estimated the proportion of variation in risk that could be attributed......BACKGROUND & AIMS: We analyzed data from twins to determine how much the familial risk of colorectal cancer can be attributed to genetic factors vs environment. We also examined whether heritability is distinct for colon vs rectal cancer, given evidence of distinct etiologies. METHODS: Our data set...... to genetic factors (heritability). RESULTS: From earliest registration in 1943 through 2010, 1861 individuals were diagnosed with colon cancer and 1268 with rectal cancer. Monozygotic twins of affected co-twins had an FRR for colorectal cancer of 3.1 (95% CI, 2.4-3.8) relative to the cohort risk. Dizygotic...

  12. Keeping their world together--meanings and actions created through network-focused nursing in teenager and young adult cancer care.

    Science.gov (United States)

    Olsen, Pia Riis; Harder, Ingegerd

    2009-01-01

    In the transition between dependent childhood and independent young adulthood, teenagers and young adults (TYAs) are extremely vulnerable when diagnosed with cancer and while undergoing treatment. Nurses working on a youth unit for patients aged 15 to 22 years developed a nursing program that aims at supporting these young patients and their significant others to maintain, establish, and strengthen their social network during the treatment period. This article presents a grounded theory study that explored how the network-focused program was perceived by TYAs with cancer and their significant others. A theoretical account is presented on the meanings and actions that the inherent processes and interactions created. Twelve TYAs and 19 significant others participated. Data were generated through interviews, observations, and informal conversations. Embracing the program and building strength were the 2 subcategories that linked to a core concept of keeping their world together. The findings show that nurses are in a unique position to enhance and support the efforts of these young patients and their significant others in connecting with the social network that extends beyond the family and includes the wider social network.

  13. Vulnerability in the power network - a pre study

    International Nuclear Information System (INIS)

    Kjoelle, Gerd H.; Uhlen, Kjetil; Rolfseng, Lars; Stene, Birger

    2006-02-01

    Vulnerability in the power distribution network has been made a current topic because of various factors, from terror attacks to a strained power balance, large breakdowns in the power system in Europe and North America in recent time and an anticipated increase in climate-related challenges in the coming years; all related to the modern society's critical dependence on reliable power supply. Several questions are posed; whether there is a foundation to say that the vulnerability in the power network is increasing because of factors like cuts in staffing, reduced investments and increased exploitation of the capacity in the power systems, or increased average age on the air network. Different development features can indicate that the power network's ability to resist high stress is about to weaken. Examples of this is the slowly increasing trend in the number of non-reported interruptions, as well as an increase in the error frequency for power lines in the distribution network and for distribution transformers. In the pre-study there has not been found enough evidence to give a clear answer to whether the vulnerability in the power network is in fact on the rise. This is mainly due to the lack of good indicators, measuring methods and the foundation for documentation. Suggestions for methodology in order to identify unwanted incidents, estimate the probability and classify consequences for vulnerability analyses of power networks are presented. The methodology is concretised and exemplified in relation to a specific case: Power loss in the southern Norway affecting more than 250 000 people for 8-12 hours. Such a consequence is classified as critical. For four sub areas it has been exemplified which incidents may potentially cause such breaks. A summary is made of the most important challenges related to making vulnerability analyses of power networks. Comprised here are appropriate concepts, definitions, standards and measuring scales as well as data foundation

  14. Fundamental study of photoradiation therapy for cancer

    Energy Technology Data Exchange (ETDEWEB)

    Kashimura, Hiromasa; Kawakita, Isao; Nakahara, Akira; Sai, Shoki; Mitamura, Keiji; Fukutomi, Hisayuki; Sakita, Takao

    1984-12-01

    In an attempt to obtain basic data for endoscopical photoactivation therapy for cancer, photoactivation effect of various porphyrins have been studied using a human hepatoceller carcinoma cell line (PLC/PRF/5) and its transplanted tumors. Porphyrins tested were hematoporphyrin derivative (HpD), protoporphyrin disodium (PPNa), hematoporphyrin (Hp), coproporphyrin, and cobalt-protoporphyrin (COPP). To investigate cytocidal effects by laser irradiation with these drugs, the /sup 51/Cr release assay was used. The results indicate that laser irradiation only has no cytocidal effect, while PPNa has more intense cytocidal effect than that of HpD. To investigate anti-tumor effect by PRT further, 2mg of HpD, 2mg of PPNa or 0.9% NaCl were injected into human hepatocellar cartinomas transplanted to the flanks of BALB/c nu nu mice 48 hours before laser irradiation (514.5nm, 0.1 W, 30 min). The results were analized with respect to effects on tumor regression curve and their histology. The results suggest that laser irradiation alone has no antitumor effect, while PRT with PPNa has stronger anti-tumor effect than PRT with HpD. Therefore, PPNa may be used as a new photosensitizer for photoradiation therapy for cancer. (author).

  15. NEpiC: a network-assisted algorithm for epigenetic studies using mean and variance combined signals.

    Science.gov (United States)

    Ruan, Peifeng; Shen, Jing; Santella, Regina M; Zhou, Shuigeng; Wang, Shuang

    2016-09-19

    DNA methylation plays an important role in many biological processes. Existing epigenome-wide association studies (EWAS) have successfully identified aberrantly methylated genes in many diseases and disorders with most studies focusing on analysing methylation sites one at a time. Incorporating prior biological information such as biological networks has been proven to be powerful in identifying disease-associated genes in both gene expression studies and genome-wide association studies (GWAS) but has been under studied in EWAS. Although recent studies have noticed that there are differences in methylation variation in different groups, only a few existing methods consider variance signals in DNA methylation studies. Here, we present a network-assisted algorithm, NEpiC, that combines both mean and variance signals in searching for differentially methylated sub-networks using the protein-protein interaction (PPI) network. In simulation studies, we demonstrate the power gain from using both the prior biological information and variance signals compared to using either of the two or neither information. Applications to several DNA methylation datasets from the Cancer Genome Atlas (TCGA) project and DNA methylation data on hepatocellular carcinoma (HCC) from the Columbia University Medical Center (CUMC) suggest that the proposed NEpiC algorithm identifies more cancer-related genes and generates better replication results. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

    Science.gov (United States)

    Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

    2017-10-01

    The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

  17. Occupational asbestos exposure and risk of pleural mesothelioma, lung cancer, and laryngeal cancer in the prospective netherlands cohort study

    NARCIS (Netherlands)

    Offermans, N.S.M.; Vermeulen, R.; Burdorf, A.; Goldbohm, R.A.; Kauppinen, T.; Kromhout, H.; Brandt, P.A. van den

    2014-01-01

    OBJECTIVE:: To study the association between occupational asbestos exposure and pleural mesothelioma, lung cancer, and laryngeal cancer, specifically addressing risk associated with the lower end of the exposure distribution, risk of cancer subtypes, and the interaction between asbestos and smoking.

  18. The Heritability of Prostate Cancer in the Nordic Twin Study of Cancer

    DEFF Research Database (Denmark)

    Hjelmborg, Jacob B; Scheike, Thomas; Holst, Klaus

    2014-01-01

    Background: Prostate cancer is thought to be the most heritable cancer, although little is known about how this genetic contribution varies across age. Methods: To address this question, we undertook the world's largest prospective study in the Nordic Twin Study of Cancer cohort, including 18,680....... The role of genetic factors is consistently high across age Impact: Findings impact the search for genetic and epigenetic markers and frame prevention efforts....

  19. Social networks and inflammatory markers in the Framingham Heart Study.

    Science.gov (United States)

    Loucks, Eric B; Sullivan, Lisa M; D'Agostino, Ralph B; Larson, Martin G; Berkman, Lisa F; Benjamin, Emelia J

    2006-11-01

    Lack of social integration predicts coronary heart disease mortality in prospective studies; however, the biological pathways that may be responsible are poorly understood. The specific aims of this study were to examine whether social networks are associated with serum concentrations of the inflammatory markers interleukin-6 (IL-6), C-reactive protein (CRP), soluble intercellular adhesion molecule-1 (sICAM-1) and monocyte chemoattractant protein-1 (MCP-1). Participants in the Framingham Study attending examinations from 1998 to 2001 (n=3267) were eligible for inclusion in the study. Social networks were assessed using the Berkman-Syme Social Network Index (SNI). Concentrations of IL-6, CRP, sICAM-1 and MCP-1 were measured in fasting serum samples. Multivariable linear regression analyses were used to assess the association of social networks with inflammatory markers adjusting for potential confounders including age, smoking, blood pressure, total:HDL cholesterol ratio, body mass index, lipid-lowering and antihypertensive medication, diabetes, cardiovascular disease, depression and socioeconomic status. Results found that the SNI was significantly inversely associated with IL-6 in men (p=0.03) after adjusting for potential confounders. In age-adjusted analyses, social networks also were significantly inversely associated with IL-6 for women (p=0.03) and were marginally to modestly associated with CRP and sICAM-1 for men (p=0.08 and 0.02, respectively), but these associations were not significant in the multivariate analyses. In conclusion, social networks were found to be inversely associated with interleukin-6 levels in men. The possibility that inflammatory markers may be potential mediators between social integration and coronary heart disease merits further investigation.

  20. Convolutional neural network approach for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk

    Science.gov (United States)

    Oustimov, Andrew; Gastounioti, Aimilia; Hsieh, Meng-Kang; Pantalone, Lauren; Conant, Emily F.; Kontos, Despina

    2017-03-01

    We assess the feasibility of a parenchymal texture feature fusion approach, utilizing a convolutional neural network (ConvNet) architecture, to benefit breast cancer risk assessment. Hypothesizing that by capturing sparse, subtle interactions between localized motifs present in two-dimensional texture feature maps derived from mammographic images, a multitude of texture feature descriptors can be optimally reduced to five meta-features capable of serving as a basis on which a linear classifier, such as logistic regression, can efficiently assess breast cancer risk. We combine this methodology with our previously validated lattice-based strategy for parenchymal texture analysis and we evaluate the feasibility of this approach in a case-control study with 424 digital mammograms. In a randomized split-sample setting, we optimize our framework in training/validation sets (N=300) and evaluate its descriminatory performance in an independent test set (N=124). The discriminatory capacity is assessed in terms of the the area under the curve (AUC) of the receiver operator characteristic (ROC). The resulting meta-features exhibited strong classification capability in the test dataset (AUC = 0.90), outperforming conventional, non-fused, texture analysis which previously resulted in an AUC=0.85 on the same case-control dataset. Our results suggest that informative interactions between localized motifs exist and can be extracted and summarized via a fairly simple ConvNet architecture.

  1. Statistical physics, neural networks, brain studies

    International Nuclear Information System (INIS)

    Toulouse, G.

    1999-01-01

    An overview of some aspects of a vast domain, located at the crossroads of physics, biology and computer science is presented: (1) During the last fifteen years, physicists advancing along various pathways have come into contact with biology (computational neurosciences) and engineering (formal neural nets). (2) This move may actually be viewed as one component in a larger picture. A prominent trend of recent years, observable over many countries, has been the establishment of interdisciplinary centers devoted to the study of: cognitive sciences; natural and artificial intelligence; brain, mind and behaviour; perception and action; learning and memory; robotics; man-machine communication, etc. What are the promising lines of development? What opportunities for physicists? An attempt will be made to address such questions and related issues

  2. Immunological network analysis in HPV associated head and neck squamous cancer and implications for disease prognosis.

    Science.gov (United States)

    Chen, Xiaohang; Yan, Bingqing; Lou, Huihuang; Shen, Zhenji; Tong, Fangjia; Zhai, Aixia; Wei, Lanlan; Zhang, Fengmin

    2018-04-01

    Human papillomavirus-positive (HPV+) head and neck squamous cell cancer (HNSCC) exhibits a better prognosis than HPV-negative (HPV-) HNSCC. This difference may in part be due to enhanced immune activation in the HPV+ HNSCC tumor microenvironment. To characterize differences in immune activation between HPV+ and HPV- HNSCC tumors, we identified and annotated differentially expressed genes based upon mRNA expression data from The Cancer Genome Atlas (TCGA). Immune network between immune cells and cytokines was constructed by using single sample Gene Set Enrichment Analysis and conditional mutual information. Multivariate Cox regression analysis was used to determine the prognostic value of immune microenvironment characterization. A total of 1673 differentially expressed genes were functionally annotated. We found that genes upregulated in HPV+ HNSCC are enriched in immune-associated processes. And the up-regulated gene sets were validated by Gene Set Enrichment Analysis. The microenvironment of HPV+ HNSCC exhibited greater numbers of infiltrating B and T cells and fewer neutrophils than HPV- HNSCC. These findings were validated by two independent datasets in the Gene Expression Omnibus (GEO) database. Further analyses of T cell subtypes revealed that cytotoxic T cell subtypes predominated in HPV+ HNSCC. In addition, the ratio of M1/M2 macrophages was much higher in HPV+ HNSCC. The infiltration of these immune cells was correlated with differentially expressed cytokine-associated genes. Enhanced infiltration of B cells and CD8+ T cells were identified as independent protective factors, while high neutrophil infiltration was a risk enhancing factor for HPV+ HNSCC patients. A schematic model of immunological network was established for HPV+ HNSCC to summarize our findings. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. A Systems’ Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Xin Lai

    2013-01-01

    Full Text Available MicroRNAs (miRNAs are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts.

  4. Cooperation and Development: a study of case in network cooperation

    Directory of Open Access Journals (Sweden)

    June Alisson Westarb Cruz

    2009-03-01

    Full Text Available The need to develop new surviving strategies and competitive advantage by individuals and organizations make cooperation to obtain complementary competences and potentialities very important, through the insertion of social actors in multiple networks of relationships and interactions.  This research was made in an Association Network of Carrinheiros[1] located in Curitiba and in the coast of Paraná.  The objective of the study was to analyze the structural characteristics of the network and its implications to develop collective actions. The data was collected through questionnaires, interviews, document analysis, and the daily direct observation of the network.  An interaction system between individuals and organizations from various sectors in society could be verified. This interaction stimulates the structured work connected to associations and cooperatives.  Between the actors of the network, concepts and realities are different, as well as individual objectives are distinct.  However, they converge to a common general objective that establish a common base for collaborative work.

  5. A study on methodologies for assessing safety critical network's risk impact on Nuclear Power Plant

    International Nuclear Information System (INIS)

    Lim, T. J.; Lee, H. J.; Park, S. K.; Seo, S. J.

    2006-08-01

    The objectives of this project is to investigate and study existing reliability analysis techniques for communication networks in order to develop reliability analysis models for Nuclear Power Plant's safety-critical networks. It is necessary to make a comprehensive survey of current methodologies for communication network reliability. Major outputs of the first year study are design characteristics of safety-critical communication networks, efficient algorithms for quantifying reliability of communication networks, and preliminary models for assessing reliability of safety-critical communication networks

  6. Sexuality after a cancer diagnosis: A population-based study.

    Science.gov (United States)

    Jackson, Sarah E; Wardle, Jane; Steptoe, Andrew; Fisher, Abigail

    2016-12-15

    This study explored differences in sexual activity, function, and concerns between cancer survivors and cancer-free controls in a population-based study. The data were from 2982 men and 3708 women who were 50 years old or older and were participating in the English Longitudinal Study of Ageing. Sexual well-being was assessed with the Sexual Relationships and Activities Questionnaire, and cancer diagnoses were self-reported. There were no differences between cancer survivors and controls in levels of sexual activity (76.0% vs 78.5% for men and 58.2% vs 55.5% for women) or sexual function. Men and women with cancer diagnoses were more dissatisfied with their sex lives than controls (age-adjusted percentages: 30.9% vs 19.8% for men [P = .023] and 18.2% vs 11.8% for women [P = .034]), and women with cancer were more concerned about levels of sexual desire (10.2% vs 7.1%; P = .006). Women diagnosed sexual desire (14.8% vs 7.1%; P = .007) and orgasmic experience (17.6% vs 7.1%; P = .042) than controls, but there were no differences in men. Self-reports of sexual activity and functioning in older people with cancer are broadly comparable to age-matched, cancer-free controls. There is a need to identify the causes of sexual dissatisfaction among long-term cancer survivors despite apparently normal levels of sexual activity and function for their age. The development of interventions addressing low sexual desire and problems with sexual functioning in women is also important and may be particularly relevant for cancer survivors after treatment. Cancer 2016;122:3883-3891. © 2016 American Cancer Society. © 2016 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

  7. A COMPARATIVE STUDY OF SYSTEM NETWORK ARCHITECTURE Vs DIGITAL NETWORK ARCHITECTURE

    OpenAIRE

    Seema; Mukesh Arya

    2011-01-01

    The efficient managing system of sources is mandatory for the successful running of any network. Here this paper describes the most popular network architectures one of developed by IBM, System Network Architecture (SNA) and other is Digital Network Architecture (DNA). As we know that the network standards and protocols are needed for the network developers as well as users. Some standards are The IEEE 802.3 standards (The Institute of Electrical and Electronics Engineers 1980) (LAN), IBM Sta...

  8. A Primary Care Initiative for Cancer Survivorship: A Case Study of Cancer in Obese Men

    Directory of Open Access Journals (Sweden)

    Mamdouh M. Shubair

    2017-01-01

    Full Text Available Background: Men in rural and northern areas of Canada experience considerable challenges in health care access for chronic conditions such as obesity, type 2 diabetes (T2D, and cancer. Obese men (body mass index/BMI ≥ 30 kg/m2 in rural/remote northern British Columbia (BC experience poorer health outcomes due to cancer risk compared to other men elsewhere in urban Canada. Context: Challenges faced by men who develop cancer as a complication of being obese are paramount in terms of primary care treatment of their cancers. Oftentimes cancer treatment is multi-modal and complex. Models of shared care have been proposed to provide coordinated survivorship care to the growing population of rural male cancer patients suffering from obesity and the Metabolic Syndrome (MetS. Methods: Objectives: The main objective of the study was to examine the type of cancer care programs that may have focused on men with cancer in northern British Columbia (BC. A secondary objective is to identify challenges in care experienced by men with cancer during their transition from in-hospital care back to their home communities. Population: We conducted a comprehensive literature review and a qualitative focus group interview with primary care physicians (PCPs, oncologists (n=8, and a convenience sample of male cancer patients (n=6 who have underlying obesity and Metabolic Syndrome (MetS. We examined the types of cancer care programs that may have targeted such men. We further identified challenges experienced by male cancer patients while transitioning back to their home communities. Results: The focus group results outlined themes speaking to a comprehensive shared care model that goes beyond surveillance of cancer recurrence in men with obesity. Conclusion: A shared survivorship care plan or model integrates collaboration among specialists in clinical decision making and best practice for treatment of cancer in obese men.

  9. Considerations for Pharmacoepidemiological Studies of Drug-Cancer Associations

    DEFF Research Database (Denmark)

    Pottegård, Anton; Friis, Søren; Stürmer, Til

    2018-01-01

    and future perspectives. Aspects of data sources include assessment of complete history of drug use and data on dose and duration of drug use, allowing estimates of cumulative exposure. Outcome data from formal cancer registries are preferable, but cancer data from other sources, for example, patient......In this MiniReview, we provide general considerations for the planning and conduct of pharmacoepidemiological studies of associations between drug use and cancer development. We address data sources, study design, assessment of drug exposure, ascertainment of cancer outcomes, confounder adjustment...... or pathology registries, medical records or claims are also suitable. The two principal designs for observational studies evaluating drug-cancer associations are the cohort and case-control designs. A key challenge in studies of drug-cancer associations is the exposure assessment due to the typically long...

  10. Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

    Science.gov (United States)

    Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

    2017-10-03

    With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

  11. Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks

    Science.gov (United States)

    Halicek, Martin; Little, James V.; Wang, Xu; Patel, Mihir; Griffith, Christopher C.; El-Deiry, Mark W.; Chen, Amy Y.; Fei, Baowei

    2018-02-01

    Successful outcomes of surgical cancer resection necessitate negative, cancer-free surgical margins. Currently, tissue samples are sent to pathology for diagnostic confirmation. Hyperspectral imaging (HSI) is an emerging, non-contact optical imaging technique. A reliable optical method could serve to diagnose and biopsy specimens in real-time. Using convolutional neural networks (CNNs) as a tissue classifier, we developed a method to use HSI to perform an optical biopsy of ex-vivo surgical specimens, collected from 21 patients undergoing surgical cancer resection. Training and testing on samples from different patients, the CNN can distinguish squamous cell carcinoma (SCCa) from normal aerodigestive tract tissues with an area under the curve (AUC) of 0.82, 81% accuracy, 81% sensitivity, and 80% specificity. Additionally, normal oral tissues can be sub-classified into epithelium, muscle, and glandular mucosa using a decision tree method, with an average AUC of 0.94, 90% accuracy, 93% sensitivity, and 89% specificity. After separately training on thyroid tissue, the CNN differentiates between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multi-nodular goiter (MNG) with an AUC of 0.93, 87% accuracy, 88% sensitivity, and 85% specificity. Classical-type papillary thyroid carcinoma is differentiated from benign MNG with an AUC of 0.91, 86% accuracy, 86% sensitivity, and 86% specificity. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multi-category diagnostic information for normal head-and-neck tissue, SCCa, and thyroid carcinomas. More patient data are needed in order to fully investigate the proposed technique to establish reliability and generalizability of the work.

  12. Inter-organizational network studies - a literature review

    DEFF Research Database (Denmark)

    Bergenholtz, Carsten; Waldstrøm, Christian

    literature review of the last 12 years' research on inter-organizational networks, with a focus on the methodological aspects. The findings of this paper is that few of the previous studies have used the full methodological (and thus theoretical) scope of the available data and that the most cited papers...

  13. International Students' Networks: A Case Study in a UK University

    Science.gov (United States)

    Taha, Nashrawan; Cox, Andrew

    2016-01-01

    The great influx of international students into UK universities has led to internationalisation becoming an important issue. Previous studies have focused on the integration of home and international students, illustrating a lack of intercultural interaction. Yet there has been a lack of research investigating international students' networks and…

  14. Collective Study On Security Threats In VOIP Networks

    Directory of Open Access Journals (Sweden)

    Muhammad Zulkifl Hasan

    2017-01-01

    Full Text Available The Collective study will critically evaluate the voice over internet protocol VOIP Security threats issues amp challenges in the communication over the network the solution provided by different vendors. Authors will be discussing all security issues different protocols but main focus will be on SIP protocol its implementation and vendors VOIP security system.

  15. Social networks and health: a systematic review of sociocentric network studies in low- and middle-income countries.

    Science.gov (United States)

    Perkins, Jessica M; Subramanian, S V; Christakis, Nicholas A

    2015-01-01

    In low- and middle-income countries (LMICs), naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various resources. Understanding how social network structure, and influential individuals within the network, may amplify the effects of interventions in LMICs, by creating, for example, cascade effects to non-targeted participants, presents an opportunity to improve the efficiency and effectiveness of public health interventions in such settings. We conducted a systematic review of PubMed, Econlit, Sociological Abstracts, and PsycINFO to identify a sample of 17 sociocentric network papers (arising from 10 studies) that specifically examined health issues in LMICs. We also separately selected to review 19 sociocentric network papers (arising from 10 other studies) on development topics related to wellbeing in LMICs. First, to provide a methodological resource, we discuss the sociocentric network study designs employed in the selected papers, and then provide a catalog of 105 name generator questions used to measure social ties across all the LMIC network papers (including both ego- and sociocentric network papers) cited in this review. Second, we show that network composition, individual network centrality, and network structure are associated with important health behaviors and health and development outcomes in different contexts across multiple levels of analysis and across distinct network types. Lastly, we highlight the opportunities for health researchers and practitioners in LMICs to 1) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure, 2) measure the spread of outcomes or intervention externalities, and 3) enhance the effectiveness and efficiency of aid based on knowledge of social structure. In summary, human health and wellbeing are connected through complex

  16. Social Networks and Health: A Systematic Review of Sociocentric Network Studies in Low- and Middle-Income Countries

    Science.gov (United States)

    Perkins, Jessica M; Subramanian, S V; Christakis, Nicholas A

    2015-01-01

    In low- and middle-income countries (LMICs), naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various resources. Understanding how social network structure, and influential individuals within the network, may amplify the effects of interventions in LMICs, by creating, for example, cascade effects to non-targeted participants, presents an opportunity to improve the efficiency and effectiveness of public health interventions in such settings. We conducted a systematic review of PubMed, Econlit, Sociological Abstracts, and PsycINFO to identify a sample of 17 sociocentric network papers (arising from 10 studies) that specifically examined health issues in LMICs. We also separately selected to review 19 sociocentric network papers (arising from 10 other studies) on development topics related to wellbeing in LMICs. First, to provide a methodological resource, we discuss the sociocentric network study designs employed in the selected papers, and then provide a catalog of 105 name generator questions used to measure social ties across all the LMIC network papers (including both ego- and sociocentric network papers) cited in this review. Second, we show that network composition, individual network centrality, and network structure are associated with important health behaviors and health and development outcomes in different contexts across multiple levels of analysis and across distinct network types. Lastly, we highlight the opportunities for health researchers and practitioners in LMICs to 1) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure, 2) measure the spread of outcomes or intervention externalities, and 3) enhance the effectiveness and efficiency of aid based on knowledge of social structure. In summary, human health and wellbeing are connected through complex

  17. Cytologic studies on irradiated gestric cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Isono, S; Takeda, T; Amakasu, H; Asakawa, H; Yamada, S [Miyagi Prefectural Adult Disease Center, Natori (Japan)

    1981-06-01

    The smears of the biopsy and resected specimens obtained from 74 cases of irradiated gastric cancer were cytologically analyzed for effects of irradiation. Irradiation increased the amount of both necrotic materials and neutrophils in the smears. Cancer cells were decreased in number almost in inverse proportion to irradiation dose. Clusters of cancer cells shrank in size and cells were less stratified after irradiation. Irradiated cytoplasms were swollen, vacuolated and stained abnormally. Irradiation with less than 3,000 rads gave rise to swelling of cytoplasms in almost all cases. Nuclei became enlarged, multiple, pyknotic and/or stained pale after irradiation. Nuclear swelling was more remarkable in cancer cells of differentiated adenocarcinomas.

  18. Performance Study of Earth Networks Total Lightning Network using Rocket-Triggered Lightning Data in 2014

    Science.gov (United States)

    Heckman, S.

    2015-12-01

    Modern lightning locating systems (LLS) provide real-time monitoring and early warning of lightningactivities. In addition, LLS provide valuable data for statistical analysis in lightning research. It isimportant to know the performance of such LLS. In the present study, the performance of the EarthNetworks Total Lightning Network (ENTLN) is studied using rocket-triggered lightning data acquired atthe International Center for Lightning Research and Testing (ICLRT), Camp Blanding, Florida.In the present study, 18 flashes triggered at ICLRT in 2014 were analyzed and they comprise of 78negative cloud-to-ground return strokes. The geometric mean, median, minimum, and maximum for thepeak currents of the 78 return strokes are 13.4 kA, 13.6 kA, 3.7 kA, and 38.4 kA, respectively. The peakcurrents represent typical subsequent return strokes in natural cloud-to-ground lightning.Earth Networks has developed a new data processor to improve the performance of their network. Inthis study, results are presented for the ENTLN data using the old processor (originally reported in 2014)and the ENTLN data simulated using the new processor. The flash detection efficiency, stroke detectionefficiency, percentage of misclassification, median location error, median peak current estimation error,and median absolute peak current estimation error for the originally reported data from old processorare 100%, 94%, 49%, 271 m, 5%, and 13%, respectively, and those for the simulated data using the newprocessor are 100%, 99%, 9%, 280 m, 11%, and 15%, respectively. The use of new processor resulted inhigher stroke detection efficiency and lower percentage of misclassification. It is worth noting that theslight differences in median location error, median peak current estimation error, and median absolutepeak current estimation error for the two processors are due to the fact that the new processordetected more number of return strokes than the old processor.

  19. Reveal genes functionally associated with ACADS by a network study.

    Science.gov (United States)

    Chen, Yulong; Su, Zhiguang

    2015-09-15

    Establishing a systematic network is aimed at finding essential human gene-gene/gene-disease pathway by means of network inter-connecting patterns and functional annotation analysis. In the present study, we have analyzed functional gene interactions of short-chain acyl-coenzyme A dehydrogenase gene (ACADS). ACADS plays a vital role in free fatty acid β-oxidation and regulates energy homeostasis. Modules of highly inter-connected genes in disease-specific ACADS network are derived by integrating gene function and protein interaction data. Among the 8 genes in ACADS web retrieved from both STRING and GeneMANIA, ACADS is effectively conjoined with 4 genes including HAHDA, HADHB, ECHS1 and ACAT1. The functional analysis is done via ontological briefing and candidate disease identification. We observed that the highly efficient-interlinked genes connected with ACADS are HAHDA, HADHB, ECHS1 and ACAT1. Interestingly, the ontological aspect of genes in the ACADS network reveals that ACADS, HAHDA and HADHB play equally vital roles in fatty acid metabolism. The gene ACAT1 together with ACADS indulges in ketone metabolism. Our computational gene web analysis also predicts potential candidate disease recognition, thus indicating the involvement of ACADS, HAHDA, HADHB, ECHS1 and ACAT1 not only with lipid metabolism but also with infant death syndrome, skeletal myopathy, acute hepatic encephalopathy, Reye-like syndrome, episodic ketosis, and metabolic acidosis. The current study presents a comprehensible layout of ACADS network, its functional strategies and candidate disease approach associated with ACADS network. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. The Heritability of Prostate Cancer in the Nordic Twin Study of Cancer

    DEFF Research Database (Denmark)

    von Bornemann Hjelmborg, Jacob; Scheike, Thomas; Holst, Klaus

    2014-01-01

    Background: Prostate cancer is thought to be the most heritable cancer, although little is known about how this genetic contribution varies across age. Methods: To address this question, we undertook the world’s largest prospective study in the Nordic Twin Study of Cancer cohort, including 18...... risk and liability. Results: The cumulative risk of prostate cancer was similar to that of the background population. The cumulative risk for twins whose co-twin was diagnosed with prostate cancer was greater for MZ than for DZ twins across all ages. Among concordantly affected pairs, the time between...... diagnoses was significantly shorter for MZ than DZ pairs (median 3.8 versus 6.5 years, respectively). Genetic differences contributed substantially to variation in both the risk and the liability (heritability=58% (95% CI 52%–63%) of developing prostate cancer. The relative contribution of genetic factors...

  1. Evaluation of exposure to pioglitazone and risk of prostate cancer: a nested case–control study

    Science.gov (United States)

    Boxall, Naomi; Bennett, Dimitri; Hunger, Matthias; Dolin, Paul; Thompson, Paula L

    2016-01-01

    Objectives Investigate potential association between pioglitazone exposure and risk of prostate cancer. Research design and methods Nested, matched case–control study. UK primary care data (Clinical Practice Research Datalink (CPRD) GOLD) linked to inpatient (Hospital Episode Statistics (HES)) and cancer registry (National Cancer Information Network (NCIN)) data. English men aged ≥40 years diagnosed with type 2 diabetes mellitus, January 1, 2001 to January 5, 2015. Cases, with prostate cancer diagnosis, matched with up to 4 controls by age, cohort entry date and region. ORs for association of exposure to pioglitazone to incident prostate cancer, adjusted for potential confounders. Results From a cohort of 47 772 men with 243 923 person-years follow-up, 756 definite cases of prostate cancer were identified. Incidence was 309.9/100 000 person-years (95% CI 288.6 to 332.8). Pioglitazone use was not associated with prostate cancer risk; adjusted OR 0.759, 95% CI 0.502 to 1.148. Analyses showed no difference when possible cases, prostate cancer in CPRD GOLD only, included (adjusted OR 0.726, 95% CI 0.510 to 1.034). No association when adjusted for channeling bias (OR 0.778, 95% CI 0.511 to 1.184) or limited to an index date prior to July 1, 2011 (adjusted OR 0.508, 95% CI 0.294 to 0.879), despite prostate-specific antigen screening occurring