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

PubMed

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.

Innovative and Community-Driven Communication Practices of the South Carolina Cancer Prevention and Control Research Network

PubMed Central

Brandt, Heather M.; Freedman, Darcy A.; Adams, Swann Arp; Young, Vicki M.; Ureda, John R.; McCracken, James Lyndon; Hébert, James R.

2014-01-01

The South Carolina Cancer Prevention and Control Research Network (SC-CPCRN) is 1 of 10 networks funded by the Centers for Disease Control and Prevention and the National Cancer Institute (NCI) that works to reduce cancer-related health disparities. In partnership with federally qualified health centers and community stakeholders, the SC-CPCRN uses evidence-based approaches (eg, NCI Research-tested Intervention Programs) to disseminate and implement cancer prevention and control messages, programs, and interventions. We describe the innovative stakeholder- and community-driven communication efforts conducted by the SC-CPCRN to improve overall health and reduce cancer-related health disparities among high-risk and disparate populations in South Carolina. We describe how our communication efforts are aligned with 5 core values recommended for dissemination and implementation science: 1) rigor and relevance, 2) efficiency and speed, 3) collaboration, 4) improved capacity, and 5) cumulative knowledge. PMID:25058673

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

PubMed Central

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

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

PubMed

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.

Patient-centered prioritization of bladder cancer research.

PubMed

Smith, Angela B; Chisolm, Stephanie; Deal, Allison; Spangler, Alejandra; Quale, Diane Z; Bangs, Rick; Jones, J Michael; Gore, John L

2018-05-04

Patient-centered research requires the meaningful involvement of patients and caregivers throughout the research process. The objective of this study was to create a process for sustainable engagement for research prioritization within oncology. From December 2014 to 2016, a network of engaged patients for research prioritization was created in partnership with the Bladder Cancer Advocacy Network (BCAN): the BCAN Patient Survey Network (PSN). The PSN leveraged an online bladder cancer community with additional recruitment through print advertisements and social media campaigns. Prioritized research questions were developed through a modified Delphi process and were iterated through multidisciplinary working groups and a repeat survey. In year 1 of the PSN, 354 patients and caregivers responded to the research prioritization survey; the number of responses increased to 1034 in year 2. The majority of respondents had non-muscle-invasive bladder cancer (NMIBC), and the mean time since diagnosis was 5 years. Stakeholder-identified questions for noninvasive, invasive, and metastatic disease were prioritized by the PSN. Free-text questions were sorted with thematic mapping. Several questions submitted by respondents were among the prioritized research questions. A final prioritized list of research questions was disseminated to various funding agencies, and a highly ranked NMIBC research question was included as a priority area in the 2017 Patient-Centered Outcomes Research Institute announcement of pragmatic trial funding. Patient engagement is needed to identify high-priority research questions in oncology. The BCAN PSN provides a successful example of an engagement infrastructure for annual research prioritization in bladder cancer. The creation of an engagement network sets the groundwork for additional phases of engagement, including design, conduct, and dissemination. Cancer 2018. © 2018 American Cancer Society. © 2018 American Cancer Society.

The Cancer Research Network: a platform for epidemiologic and health services research on cancer prevention, care, and outcomes in large, stable populations.

PubMed

Chubak, Jessica; Ziebell, Rebecca; Greenlee, Robert T; Honda, Stacey; Hornbrook, Mark C; Epstein, Mara; Nekhlyudov, Larissa; Pawloski, Pamala A; Ritzwoller, Debra P; Ghai, Nirupa R; Feigelson, Heather Spencer; Clancy, Heather A; Doria-Rose, V Paul; Kushi, Lawrence H

2016-11-01

The ability to collect data on patients for long periods prior to, during, and after a cancer diagnosis is critical for studies of cancer etiology, prevention, treatment, outcomes, and costs. We describe such data capacities within the Cancer Research Network (CRN), a cooperative agreement between the National Cancer Institute (NCI) and organized health care systems across the United States. Data were extracted from each CRN site's virtual data warehouse using a centrally written and locally executed program. We computed the percent of patients continuously enrolled ≥1, ≥5, and ≥10 years before cancer diagnosis in 2012-2015 (year varied by CRN site). To describe retention after diagnosis, we computed the cumulative percentages enrolled, deceased, and disenrolled each year after the diagnosis for patients diagnosed in 2000. Approximately 8 million people were enrolled in ten CRN health plans on December 31, 2014 or 2015 (year varied by CRN site). Among more than 30,000 recent cancer diagnoses, 70 % were enrolled for ≥5 years and 56 % for ≥10 years before diagnosis. Among 25,274 cancers diagnosed in 2000, 28 % were still enrolled in 2010, 45 % had died, and 27 % had disenrolled from CRN health systems. Health plan enrollment before cancer diagnosis was generally long in the CRN, and the proportion of patients lost to follow-up after diagnosis was low. With long enrollment histories among cancer patients pre-diagnosis and low post-diagnosis disenrollment, the CRN provides an excellent platform for epidemiologic and health services research on cancer incidence, outcomes, and costs.

The Cancer Research Network: a platform for epidemiologic and health services research on cancer prevention, care, and outcomes in large, stable populations

PubMed Central

Chubak, Jessica; Ziebell, Rebecca; Greenlee, Robert T.; Honda, Stacey; Hornbrook, Mark C.; Epstein, Mara; Nekhlyudov, Larissa; Pawloski, Pamala A.; Ritzwoller, Debra P.; Ghai, Nirupa R.; Feigelson, Heather Spencer; Clancy, Heather A.; Doria-Rose, V. Paul; Kushi, Lawrence H.

2018-01-01

Purpose The ability to collect data on patients for long periods prior to, during, and after a cancer diagnosis is critical for studies of cancer etiology, prevention, treatment, outcomes and costs. We describe such data capacities within the Cancer Research Network (CRN), a cooperative agreement between the National Cancer Institute (NCI) and organized health care systems across the United States. Methods Data were extracted from each CRN site’s virtual data warehouse using a centrally-written and locally-executed program. We computed the percent of patients continuously enrolled ≥1, ≥5, and ≥10 years before cancer diagnosis in 2012–2015 (year varied by CRN site). To describe retention after diagnosis, we computed the cumulative percentages enrolled, deceased, and disenrolled each year after diagnosis for patients diagnosed in 2000. Results Approximately 8 million people were enrolled in ten CRN health plans on December 31, 2014 or 2015 (year varied by CRN site). Among more than 30,000 recent cancer diagnoses, 70% were enrolled for ≥5 years and 56% for ≥10 years before diagnosis. Among 25,274 cancers diagnosed in 2000, 28% were still enrolled in 2010, 45% had died, and 27% had disenrolled from CRN health systems. Conclusions Health plan enrollment before cancer diagnosis was generally long in the CRN, and the proportion of patients lost to follow-up after diagnosis was low. With long enrollment histories among cancer patients pre-diagnosis and low post-diagnosis disenrollment, the CRN provides an excellent platform for epidemiologic and health services research on cancer incidence, outcomes, and costs. PMID:27639398

Managing cancer care through service delivery networks: The role of professional collaboration in two European cancer networks.

PubMed

Prades, Joan; Morando, Verdiana; Tozzi, Valeria D; Verhoeven, Didier; Germà, Jose R; Borras, Josep M

2017-01-01

Background The study examines two meso-strategic cancer networks, exploring to what extent collaboration can strengthen or hamper network effectiveness. Unlike macro-strategic networks, meso-strategic networks have no hierarchical governance structures nor are they institutionalised within healthcare services' delivery systems. This study aims to analyse the models of professional cooperation and the tools developed for managing clinical practice within two meso-strategic, European cancer networks. Methods Multiple case study design based on the comparative analysis of two cancer networks: Iridium, in Antwerp, Belgium and the Institut Català d'Oncologia in Catalonia, Spain. The case studies applied mixed methods, with qualitative research based on semi-structured interviews ( n = 35) together with case-site observation and material collection. Results The analysis identified four levels of collaborative intensity within medical specialties as well as in multidisciplinary settings, which became both platforms for crosscutting clinical work between hubs' experts and local care teams and the levers for network-based tools development. The organisation of clinical practice relied on professional-based cooperative processes and tiers, lacking vertical integration mechanisms. Conclusions The intensity of professional linkages largely shaped the potential of meso-strategic cancer networks to influence clinical practice organisation. Conversely, the introduction of managerial techniques or network governance structures, without introducing vertical hierarchies, was found to be critical solutions.

TCGA researchers identify 4 subtypes of stomach cancer

Cancer.gov

Stomach cancers fall into four distinct molecular subtypes, researchers with The Cancer Genome Atlas (TCGA) Network have found. Scientists report that this discovery could change how researchers think about developing treatments for stomach cancer, also c

NDEx 2.0: A Clearinghouse for Research on Cancer Pathways.

PubMed

Pratt, Dexter; Chen, Jing; Pillich, Rudolf; Rynkov, Vladimir; Gary, Aaron; Demchak, Barry; Ideker, Trey

2017-11-01

We present NDEx 2.0, the latest release of the Network Data Exchange (NDEx) online data commons (www.ndexbio.org) and the ways in which it can be used to (i) improve the quality and abundance of biological networks relevant to the cancer research community; (ii) provide a medium for collaboration involving networks; and (iii) facilitate the review and dissemination of networks. We describe innovations addressing the challenges of an online data commons: scalability, data integration, data standardization, control of content and format by authors, and decentralized mechanisms for review. The practical use of NDEx is presented in the context of a novel strategy to foster network-oriented communities of interest in cancer research by adapting methods from academic publishing and social media. Cancer Res; 77(21); e58-61. ©2017 AACR . ©2017 American Association for Cancer Research.

Setting Research Priorities for Kidney Cancer.

PubMed

Jones, Jennifer M; Bhatt, Jaimin; Avery, Jonathan; Laupacis, Andreas; Cowan, Katherine; Basappa, Naveen S; Basiuk, Joan; Canil, Christina; Al-Asaaed, Sohaib; Heng, Daniel Y C; Wood, Lori; Stacey, Dawn; Kollmannsberger, Christian; Jewett, Michael A S

2017-12-01

Defining disease-specific research priorities in cancer can facilitate better allocation of limited resources. Involving patients and caregivers as well as expert clinicians in this process is of value. We undertook this approach for kidney cancer as an example. The Kidney Cancer Research Network of Canada sponsored a collaborative consensus-based priority-setting partnership that identified ten research priorities in the management of kidney cancer. These are discussed in the context of current initiatives and gaps in knowledge. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Prostate Cancer Biorepository Network

DTIC Science & Technology

2016-10-01

Cancer Biorepository Network (PCBN). The aim of the PCBN is to provide prostate researchers with high- quality , well-annotated biospecimens obtained...patients and stores them to maintain high quality biospecimens. Additionally, clinical data including pathology and outcome data are annotated with the...that can provide to the wider research community. The major goal of the PCBN is to develop a biorepository with high- quality , well-annotated

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

PubMed

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 < .05). At a population level, patients treated by providers affiliated with CCOP were no more likely to receive at least 1 of 2 surgical innovations for treatment of their 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.

A Generic Data Harmonization Process for Cross-linked Research and Network Interaction. Construction and Application for the Lung Cancer Phenotype Database of the German Center for Lung Research.

PubMed

Firnkorn, D; Ganzinger, M; Muley, T; Thomas, M; Knaup, P

2015-01-01

Joint data analysis is a key requirement in medical research networks. Data are available in heterogeneous formats at each network partner and their harmonization is often rather complex. The objective of our paper is to provide a generic approach for the harmonization process in research networks. We applied the process when harmonizing data from three sites for the Lung Cancer Phenotype Database within the German Center for Lung Research. We developed a spreadsheet-based solution as tool to support the harmonization process for lung cancer data and a data integration procedure based on Talend Open Studio. The harmonization process consists of eight steps describing a systematic approach for defining and reviewing source data elements and standardizing common data elements. The steps for defining common data elements and harmonizing them with local data definitions are repeated until consensus is reached. Application of this process for building the phenotype database led to a common basic data set on lung cancer with 285 structured parameters. The Lung Cancer Phenotype Database was realized as an i2b2 research data warehouse. Data harmonization is a challenging task requiring informatics skills as well as domain knowledge. Our approach facilitates data harmonization by providing guidance through a uniform process that can be applied in a wide range of projects.

NDEx - the Network Data Exchange, A Network Commons for Biologists | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Network models of biology, whether curated or derived from large-scale data analysis, are critical tools in the understanding of cancer mechanisms and in the design and personalization of therapies. The NDEx Project (Network Data Exchange) will create, deploy, and maintain an open-source, web-based software platform and public website to enable scientists, organizations, and software applications to share, store, manipulate, and publish biological networks.

Early Detection Research Network (EDRN) | Division of Cancer Prevention

Cancer.gov

http://edrn.nci.nih.gov/EDRN is a collaborative network that maintains comprehensive infrastructure and resources critical to the discovery, development and validation of biomarkers for cancer risk and early detection. The program comprises a public/private sector consortium to accelerate the development of biomarkers that will change medical practice, ensure data

MBCP - Patients - Support Groups | Center for Cancer Research

Cancer.gov

Support Groups Bladder Cancer Advocacy Network (BCAN) – a community of advocates, survivors, medical and research professionals united in support of people touched by bladder cancer. American Bladder Cancer Society (ABCS) – ABCS features a bladder cancer forum, treatment center finder, blog, and more . . .

Breast Cancer and the Environment Research Program

Cancer.gov

The Breast Cancer and the Environment Research Program supports a multidisciplinary network of scientists, clinicians, and community partners to examine the effects of environmental exposures that may predispose a woman to breast cancer throughout her life.

US-LA CRN Clinical Cancer Research in Latin America

Cancer.gov

The United States – Latin America Cancer Research Network (US-LA CRN) convened its Annual Meeting, in coordination with the Ministry of Health of Chile to discuss the Network’s first multilateral clinical research study: Molecular Profiling of Breast Cancer (MPBC).

Study reveals potentially prognostic gene, metabolism changes in kidney cancers | Center for Cancer Research

Cancer.gov

The Cancer Genome Atlas Research Network investigators, including CCR scientists, identified genetic and metabolic pathway changes linked to reduced survival of patients within and across subtypes of renal cell carcinoma (RCC), a type of kidney cancer. The study, published April 5, 2018, in Cell Reports, is part of The Cancer Genome Atlas (TCGA) Program, a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI).

Network Expands Links on DNA Variants and Cancer Risk

Cancer.gov

Researchers with the NCI-supported GAME-ON initiative and OncoArray Network are publishing studies identifying dozens of new genetic variants associated with the risk for developing some of the most common cancers, as this Cancer Currents blog post reports.

Redes En Acción. Increasing Hispanic participation in cancer research, training, and awareness.

PubMed

Ramirez, Amelie G; Talavera, Gregory A; Marti, Jose; Penedo, Frank J; Medrano, Martha A; Giachello, Aida L; Pérez-Stable, Eliseo J

2006-10-15

Hispanics are affected by many health care disparities. The National Cancer Institute (NCI), through its Special Populations Branch, is supporting networking and capacity-building activities designed to increase Hispanic participation and leadership in cancer research. Redes En Acción established a national network of cancer research centers, community-based organizations, and federal partners to facilitate opportunities for junior Hispanic scientists to participate in training and research projects on cancer control. Since 2000, Redes En Acción has established a network of more than 1800 Hispanic leaders involved in cancer research and education. The project has sustained 131 training positions and submitted 29 pilot projects to NCI for review, with 16 awards for a total of $800,000, plus an additional $8.8 million in competing grant funding based on pilot study results to date. Independent research has leveraged an additional $32 million in non-Redes funding, and together the national and regional network sites have participated in more than 1400 community and professional awareness events. In addition, the program conducted extensive national survey research that provided the basis for the Redes En Acción Latino Cancer Report, a national agenda on Hispanic cancer issues. Redes En Acción has increased participation in cancer control research, training, and awareness among Hispanic scientists and within Hispanic communities. Cancer 2006. (c) 2006 American Cancer Society.

The National Cancer Institute's Physical Sciences - Oncology Network

NASA Astrophysics Data System (ADS)

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.

The Children's Oncology Group Childhood Cancer Research Network (CCRN): case catchment in the United States.

PubMed

Musselman, Jessica R B; Spector, Logan G; Krailo, Mark D; Reaman, Gregory H; Linabery, Amy M; Poynter, Jenny N; Stork, Susan K; Adamson, Peter C; Ross, Julie A

2014-10-01

The Childhood Cancer Research Network (CCRN) was established within the Children's Oncology Group (COG) in July 2008 to provide a centralized pediatric cancer research registry for investigators conducting approved etiologic and survivorship studies. The authors conducted an ecological analysis to characterize CCRN catchment at >200 COG institutions by demographic characteristics, diagnosis, and geographic location to determine whether the CCRN can serve as a population-based registry for childhood cancer. During 2009 to 2011, 18,580 US children newly diagnosed with cancer were registered in the CCRN. These observed cases were compared with age-specific, sex-specific, and race/ethnicity-specific expected numbers calculated from Surveillance, Epidemiology, and End Results (SEER) Program cancer incidence rates and 2010 US Census data. Overall, 42% of children (18,580 observed/44,267 expected) who were diagnosed with cancer at age <20 years were registered in the CCRN, including 45%, 57%, 51%, 44%, and 24% of those diagnosed at birth, ages 1 to 4 years, ages 5 to 9 years, ages 10 to 14 years, and ages 15 to 19 years, respectively. Some malignancies were better represented in the CCRN (leukemia, 59%; renal tumors, 67%) than others (retinoblastoma, 34%). There was little evidence of differences by sex or race/ethnicity, although rates in nonwhites were somewhat lower than rates in whites. Given the low observed-to-expected ratio, it will be important to identify challenges and barriers to registration to improve case ascertainment, especially for rarer diagnoses and older age groups; however, it is encouraging that some diagnoses in younger children are fairly representative of the population. Overall, the CCRN is providing centralized, real-time access to cases for research and could be used as a model for other national cooperative groups. © 2014 American Cancer Society.

NCI-CONNECT - Comprehensive Oncology Network Evaluating Rare CNS Tumors | Center for Cancer Research

Cancer.gov

NCI-CONNECT:  Comprehensive Oncology Network Evaluating Rare CNS Tumors Purpose NCI-CONNECT aims to advance the understanding of rare adult central nervous system (CNS) cancers by establishing and fostering patient-advocacy-provider partnerships and networks to improve approaches to care and treatment.

Collaborating to Move Research Forward: Proceedings of the 10th Annual Bladder Cancer Think Tank.

PubMed

Kamat, Ashish M; Agarwal, Piyush; Bivalacqua, Trinity; Chisolm, Stephanie; Daneshmand, Sia; Doroshow, James H; Efstathiou, Jason A; Galsky, Matthew; Iyer, Gopa; Kassouf, Wassim; Shah, Jay; Taylor, John; Williams, Stephen B; Quale, Diane Zipursky; Rosenberg, Jonathan E

2016-04-27

The 10th Annual Bladder Cancer Think Tank was hosted by the Bladder Cancer Advocacy Network and brought together a multidisciplinary group of clinicians, researchers, representatives and Industry to advance bladder cancer research efforts. Think Tank expert panels, group discussions, and networking opportunities helped generate ideas and strengthen collaborations between researchers and physicians across disciplines and between institutions. Interactive panel discussions addressed a variety of timely issues: 1) data sharing, privacy and social media; 2) improving patient navigation through therapy; 3) promising developments in immunotherapy; 4) and moving bladder cancer research from bench to bedside. Lastly, early career researchers presented their bladder cancer studies and had opportunities to network with leading experts.

Active Early Detection Research Network Grants | Division of Cancer Prevention

Cancer.gov

The Division of Cancer Prevention (DCP) conducts and supports research to determine a person's risk of cancer and to find ways to reduce the risk. This knowledge is critical to making progress against cancer because risk varies over the lifespan as genetic and epigenetic changes can transform healthy tissue into invasive cancer.

NCI Community Oncology Research Program (NCORP) | Division of Cancer Prevention

Cancer.gov

The NCI Community Oncology Research Program (NCORP) is a national network of cancer care investigators, providers, academia, and other organizations that care for diverse populations in health systems. View the list of publications from NCORP. | Clinical Trials network of cancer care professionals who care for diverse populations across the U.S.

NCI Awards 18 Grants to Continue the Early Detection Research Network (EDRN) Biomarkers Effort | Division of Cancer Prevention

Cancer.gov

The NCI has awarded 18 grants to continue the Early Detection Research Network (EDRN), a national infrastructure that supports the integrated development, validation, and clinical application of biomarkers for the early detection of cancer. The awards fund 7 Biomarker Developmental Laboratories, 8 Clinical Validation Centers, 2 Biomarker Reference Laboratories, and a Data

Characterizing mutation-expression network relationships in multiple cancers.

PubMed

Ghazanfar, Shila; Yang, Jean Yee Hwa

2016-08-01

Data made available through large cancer consortia like The Cancer Genome Atlas make for a rich source of information to be studied across and between cancers. In recent years, network approaches have been applied to such data in uncovering the complex interrelationships between mutational and expression profiles, but lack direct testing for expression changes via mutation. In this pan-cancer study we analyze mutation and gene expression information in an integrative manner by considering the networks generated by testing for differences in expression in direct association with specific mutations. We relate our findings among the 19 cancers examined to identify commonalities and differences as well as their characteristics. Using somatic mutation and gene expression information across 19 cancers, we generated mutation-expression networks per cancer. On evaluation we found that our generated networks were significantly enriched for known cancer-related genes, such as skin cutaneous melanoma (p<0.01 using Network of Cancer Genes 4.0). Our framework identified that while different cancers contained commonly mutated genes, there was little concordance between associated gene expression changes among cancers. Comparison between cancers showed a greater overlap of network nodes for cancers with higher overall non-silent mutation load, compared to those with a lower overall non-silent mutation load. This study offers a framework that explores network information through co-analysis of somatic mutations and gene expression profiles. Our pan-cancer application of this approach suggests that while mutations are frequently common among cancer types, the impact they have on the surrounding networks via gene expression changes varies. Despite this finding, there are some cancers for which mutation-associated network behaviour appears to be similar: suggesting a potential framework for uncovering related cancers for which similar therapeutic strategies may be applicable. Our

Training and mobility: a priority for the Organisation of the European Cancer Institutes. How a national mobility initiative could enhance EU cooperation in cancer research contributing to the development of an European Research Area: the example of The Italian Comprehensive Cancer Centers' Network "Alleanza Contro il Cancro".

PubMed

Lombardo, Claudio; Albanese, Daniela; Belardelli, Filippo; d'Alessandro, Francesca; Giacomini, Mauro; Rondanina, Tania; Spagnoli, Luigi G

2008-01-01

It is widely recognized that productivity gains, sustained economic growth and employment are largely determined by technological progress, innovation and human capital. The 2000 Lisbon strategy to make Europe a competitive knowledge-based economy by 2010 and, more specifically, the Barcelona objectives agreed upon in 2002 to increase R&D investment in the EU to approach 3% of GDP, ensuring that there are sufficient human resources for research, are a preliminary step in this direction. If we want to reach this goal we have to succeed in retaining the best researchers, creating the right environment where they can perform their activities and develop their careers. To this aim the Organization of European Cancer Institutes (OECI) has set up a working group on Education and Training with the mandate to encourage continuing education in cancer research and applications and to verify the feasibility to promote mobility programs inside the network and in association with industries. Until now only few OECI training programs have been launched and a full mobility program has not been developed yet due to limited budget resources. The Italian Network of Comprehensive Cancer Centers, Alleanza Contro il Cancro, has planned the launch of a mobility program awarding 70 annual fellowships over a period of 36 months. This program, which will be open to the world research community, could represent a first interaction through mobility among the members of the OECI network also involving industries. The program is a tangible approach to sustain the translational process needed for the development of an European Research Area in the field of cancer and its related biomedical disciplines, thus providing a practical answer to the 2005 renewed Lisbon Strategy.

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

PubMed Central

Acencio, Marcio Luis; Bovolenta, Luiz Augusto; Camilo, Esther; Lemke, Ney

2013-01-01

Cancer has been increasingly recognized as a systems biology disease since many investigators have demonstrated that this malignant phenotype emerges from abnormal protein-protein, regulatory and metabolic interactions induced by simultaneous structural and regulatory changes in multiple genes and pathways. Therefore, the identification of oncogenic interactions and cancer-related signaling networks is crucial for better understanding cancer. As experimental techniques for determining such interactions and signaling networks are labor-intensive and time-consuming, the development of a computational approach capable to accomplish this task would be of great value. For this purpose, we present here a novel computational approach based on network topology and machine learning capable to predict oncogenic interactions and extract relevant cancer-related signaling subnetworks from an integrated network of human genes interactions (INHGI). This approach, called graph2sig, is twofold: first, it assigns oncogenic scores to all interactions in the INHGI and then these oncogenic scores are used as edge weights to extract oncogenic signaling subnetworks from INHGI. Regarding the prediction of oncogenic interactions, we showed that graph2sig is able to recover 89% of known oncogenic interactions with a precision of 77%. Moreover, the interactions that received high oncogenic scores are enriched in genes for which mutations have been causally implicated in cancer. We also demonstrated that graph2sig is potentially useful in extracting oncogenic signaling subnetworks: more than 80% of constructed subnetworks contain more than 50% of original interactions in their corresponding oncogenic linear pathways present in the KEGG PATHWAY database. In addition, the potential oncogenic signaling subnetworks discovered by graph2sig are supported by experimental evidence. Taken together, these results suggest that graph2sig can be a useful tool for investigators involved in cancer research

History of the Rare Cancer Network and Past Research

PubMed Central

Mirimanoff, René-Olivier; Ozsahin, Mahmut; Thariat, Juliette; Ozyar, Enis; Schick, Ulrike; Pehlivan, Berrin; Krengli, Marco; Pellanda, Alessandra Franzetti; Vees, Hansjörg; Cai, Ling; Scandolaro, Luciano; Belkacemi, Yazid; Villà, Salvador; Igdem, Sefik; Lutsyk, Myroslav; Miller, Robert C.

2014-01-01

Approximately, twenty years ago, the Rare Cancer Network (RCN) was formed in Lausanne, Switzerland, to support the study of rare malignancies. The RCN has grown over the years and now includes 130 investigators from twenty-four nations on six continents. The network held its first international symposium in Nice, France, on March 21-22, 2014. The proceedings of that meeting are presented in two companion papers. This manuscript reviews the history of the growth of the RCN and contains the abstracts of fourteen oral presentations made at the meeting of prior RCN studies. From 1993 to 2014, 74 RCN studies have been initiated, of which 54 were completed, 10 are in progress or under analysis, and 9 were stopped due to poor accrual. Forty-four peer reviewed publications have been written on behalf of the RCN. PMID:25276325

The Future of Prostate Cancer Research and Treatment

Cancer.gov

On January 12, 2017 prostate cancer experts William Dahut, M.D. of the National Cancer Institute and Dr. Heather Cheng, M.D. of the University of Washington had a vibrant discussion about current and future research areas and treatment options for prostate cancer. The panel was moderated by Ana Fadich, MPH, CHES Vice President at Men’s Health of the Men's Health Network.

Study reveals potentially prognostic gene, metabolism changes in kidney cancers | Center for Cancer Research

Cancer.gov

The Cancer Genome Atlas Research Network investigators, including CCR scientists, identified genetic and metabolic pathway changes linked to reduced survival of patients within and across subtypes of renal cell carcinoma (RCC), a type of kidney cancer. The study, published April 5, 2018, in Cell Reports, is part of The Cancer Genome Atlas (TCGA) Program, a joint effort of the

Disrupting the Networks of Cancer

PubMed Central

Camacho, Daniel F.; Pienta, Kenneth J.

2014-01-01

Ecosystems are interactive systems involving communities of species and their abiotic environment. Tumors are ecosystems in which cancer cells act as invasive species interacting with native host cell species in an established microenvironment within the larger host biosphere. At its heart, to study ecology is to study interconnectedness. In ecologic science, an ecologic network is a representation of the biotic interactions in an ecosystem in which species (nodes) are connected by pairwise interactions (links). Ecologic networks and signaling network models have been used to describe and compare the structures of ecosystems. It has been shown that disruption of ecologic networks through the loss of species or disruption of interactions between them can lead to the destruction of the ecosystem. Often, the destruction of a single node or link is not enough to disrupt the entire ecosystem. The more complex the network and its interactions, the more difficult it is to cause the extinction of a species, especially without leveraging other aspects of the ecosystem. Similarly, successful treatment of cancer with a single agent is rarely enough to cure a patient without strategically modifying the support systems conducive to survival of cancer. Cancer cells and the ecologic systems they reside in can be viewed as a series of nested networks. The most effective new paradigms for treatment will be developed through application of scaled network disruption. PMID:22442061

Disrupting the networks of cancer.

PubMed

Camacho, Daniel F; Pienta, Kenneth J

2012-05-15

Ecosystems are interactive systems involving communities of species and their abiotic environment. Tumors are ecosystems in which cancer cells act as invasive species interacting with native host cell species in an established microenvironment within the larger host biosphere. At its heart, to study ecology is to study interconnectedness. In ecologic science, an ecologic network is a representation of the biotic interactions in an ecosystem in which species (nodes) are connected by pairwise interactions (links). Ecologic networks and signaling network models have been used to describe and compare the structures of ecosystems. It has been shown that disruption of ecologic networks through the loss of species or disruption of interactions between them can lead to the destruction of the ecosystem. Often, the destruction of a single node or link is not enough to disrupt the entire ecosystem. The more complex the network and its interactions, the more difficult it is to cause the extinction of a species, especially without leveraging other aspects of the ecosystem. Similarly, successful treatment of cancer with a single agent is rarely enough to cure a patient without strategically modifying the support systems conducive to survival of cancer. Cancer cells and the ecologic systems they reside in can be viewed as a series of nested networks. The most effective new paradigms for treatment will be developed through application of scaled network disruption. ©2012 AACR.

Biological Networks for Cancer Candidate Biomarkers Discovery

PubMed Central

Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

2016-01-01

Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field. PMID:27625573

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

Cancer.gov

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

Active Barrett's Esophagus Translational Research Network Grants | Division of Cancer Prevention

Cancer.gov

The Division of Cancer Prevention (DCP) conducts and supports research to determine a person's risk of cancer and to find ways to reduce the risk. This knowledge is critical to making progress against cancer because risk varies over the lifespan as genetic and epigenetic changes can transform healthy tissue into invasive cancer.

Graph Curvature for Differentiating Cancer Networks

PubMed Central

Sandhu, Romeil; Georgiou, Tryphon; Reznik, Ed; Zhu, Liangjia; Kolesov, Ivan; Senbabaoglu, Yasin; Tannenbaum, Allen

2015-01-01

Cellular interactions can be modeled as complex dynamical systems represented by weighted graphs. The functionality of such networks, including measures of robustness, reliability, performance, and efficiency, are intrinsically tied to the topology and geometry of the underlying graph. Utilizing recently proposed geometric notions of curvature on weighted graphs, we investigate the features of gene co-expression networks derived from large-scale genomic studies of cancer. We find that the curvature of these networks reliably distinguishes between cancer and normal samples, with cancer networks exhibiting higher curvature than their normal counterparts. We establish a quantitative relationship between our findings and prior investigations of network entropy. Furthermore, we demonstrate how our approach yields additional, non-trivial pair-wise (i.e. gene-gene) interactions which may be disrupted in cancer samples. The mathematical formulation of our approach yields an exact solution to calculating pair-wise changes in curvature which was computationally infeasible using prior methods. As such, our findings lay the foundation for an analytical approach to studying complex biological networks. PMID:26169480

Cancer Transcriptome Dataset Analysis: Comparing Methods of Pathway and Gene Regulatory Network-Based Cluster Identification.

PubMed

Nam, Seungyoon

2017-04-01

Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets. Network clustering is useful, but depends on the network topology in and of itself. Notably, the performance of different network-generating tools for network cluster (NC) identification has been little investigated to date. Hence, using gastric cancer (GC) transcriptomic datasets, we compared two algorithms for generating pathway versus gene regulatory network-based NCs, showing that the pathway-based approach better agrees with a reference set of cancer-functional contexts. Finally, by applying pathway-based NC identification to GC transcriptome datasets, we describe cancer NCs that associate with candidate therapeutic targets and biomarkers in GC. These observations collectively inform future research on cancer transcriptomics, drug discovery, and rational development of new analysis tools for optimal harnessing of omics data.

Translating research into practice: the role of provider-based research networks in the diffusion of an evidence-based colon cancer treatment innovation.

PubMed

Carpenter, William R; Meyer, Anne-Marie; Wu, Yang; Qaqish, Bahjat; Sanoff, Hanna K; Goldberg, Richard M; Weiner, Bryan J

2012-08-01

Provider-based research networks (PBRNs)--collaborative research partnerships between academic centers and community-based practitioners--are a promising model for accelerating the translation of research into practice; however, empirical evidence of accelerated translation is limited. Oxaliplatin in adjuvant combination chemotherapy is an innovation with clinical trial-proven survival benefit compared with prior therapies. The goal of this study is to examine the diffusion of oxaliplatin into community practice, and whether affiliation with the National Cancer Institute's (NCI's) Community Clinical Oncology Program (CCOP)--a nationwide cancer-focused PBRN--is associated with accelerated innovation adoption. This retrospective observational study used linked Surveillance, Epidemiology, and End Results-Medicare and NCI CCOP data to examine Medicare participants with stage III colon cancer initiating treatment in 2003 through 2006, the years surrounding oxaliplatin's Food and Drug Administration approval. A fixed-effects analysis examined chemotherapy use among patients treated outside academic centers at CCOP-affiliated practices compared with non-CCOP practices. Two-group modeling controlled for multiple levels of clustering, year of chemotherapy initiation, tumor characteristics, patient age, race, comorbidity, Medicaid dual-eligibility status, and education. Of 4055 community patients, 35% received 5-fluoruracil, 20% received oxaliplatin, 7% received another chemotherapy, and 38% received no chemotherapy. Twenty-five percent of CCOP patients received oxaliplatin, compared with 19% of non-CCOP patients. In multivariable analysis, CCOP exposure was associated with higher odds of receiving guideline-concordant treatment in general, and oxaliplatin specifically. These findings contribute to a growing set of evidence linking PBRNs with a greater probability of receiving treatment innovations and high-quality cancer care, with implications for clinical and research

Cancer Research

Cancer.gov

NCI is the nation's leader in cancer research. Learn more about NCI's cancer research areas, key initiatives, progress made in cancer research, and resources for researchers like research tools, specimens and data.

Investigating cellular network heterogeneity and modularity in cancer: a network entropy and unbalanced motif approach.

PubMed

Cheng, Feixiong; Liu, Chuang; Shen, Bairong; Zhao, Zhongming

2016-08-26

Cancer is increasingly recognized as a cellular system phenomenon that is attributed to the accumulation of genetic or epigenetic alterations leading to the perturbation of the molecular network architecture. Elucidation of network properties that can characterize tumor initiation and progression, or pinpoint the molecular targets related to the drug sensitivity or resistance, is therefore of critical importance for providing systems-level insights into tumorigenesis and clinical outcome in the molecularly targeted cancer therapy. In this study, we developed a network-based framework to quantitatively examine cellular network heterogeneity and modularity in cancer. Specifically, we constructed gene co-expressed protein interaction networks derived from large-scale RNA-Seq data across 8 cancer types generated in The Cancer Genome Atlas (TCGA) project. We performed gene network entropy and balanced versus unbalanced motif analysis to investigate cellular network heterogeneity and modularity in tumor versus normal tissues, different stages of progression, and drug resistant versus sensitive cancer cell lines. We found that tumorigenesis could be characterized by a significant increase of gene network entropy in all of the 8 cancer types. The ratio of the balanced motifs in normal tissues is higher than that of tumors, while the ratio of unbalanced motifs in tumors is higher than that of normal tissues in all of the 8 cancer types. Furthermore, we showed that network entropy could be used to characterize tumor progression and anticancer drug responses. For example, we found that kinase inhibitor resistant cancer cell lines had higher entropy compared to that of sensitive cell lines using the integrative analysis of microarray gene expression and drug pharmacological data collected from the Genomics of Drug Sensitivity in Cancer database. In addition, we provided potential network-level evidence that smoking might increase cancer cellular network heterogeneity and

Provider-Based Research Networks Demonstrate Greater Hospice Use for Minority Patients With Lung Cancer

PubMed Central

Penn, Dolly C.; Stitzenberg, Karyn B.; Cobran, Ewan K.; Godley, Paul A.

2014-01-01

Purpose: The Community Clinical Oncology Program (CCOP) and Minority-Based Community Clinical Oncology Program (MBCCOP) are provider-based research networks (PBRN) that improve minority enrollment in cancer-focused clinical trials. We hypothesized that affiliation with a PBRN may also mitigate racial differences in hospice enrollment for patients with lung cancer. Methods: We used the SEER-Medicare data, linked to the National Cancer Institute's CCOP program data, to identify all patients (≥ age 65 years) with lung cancer, diagnosed from 2001 to 2007. We defined clinical treatment settings as CCOP, MBCCOP, academic, or community-affiliated and used multivariable logistic regression analysis to determine factors associated with hospice enrollment. Results: Forty-one thousand eight hundred eighty-five (55.1%) patients with lung cancer enrolled in hospice before death. Approximately 55% of CCOP, 57% of MBCCOP, 57% of academic, and 52% of community patients enrolled. Patients who were more likely to enroll were female (odds ratio [OR], 1.36; 95% CI, 1.31 to 1.40); ≥ age 79 years (OR, 1.11; 95%CI, 1.06 to 1.16); white; lived in more educated areas; had minimal comorbidities; and had distant disease. Asian and black patients in academic (41.1% and 50.4%, respectively) and community practices (35.2% and 43.4%, respectively) were less likely to enroll in hospice compared with white patients (academic, 58.8%; community, 53.1%). However, hospice enrollment was equivalent for black and white patients in MBCCOP (59.5% v 57.2%) and CCOP (52.2% v 56.3%) practices. Conclusion: Minority patients with lung cancer receiving treatment in cancer-focused PBRN- affiliated practices have greater hospice enrollment than those treated in academic and community practices. PMID:24781367

Network information improves cancer outcome prediction.

PubMed

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.

Social Networks Across Common Cancer Types: The Evidence, Gaps, and Areas of Potential Impact.

PubMed

Rice, L J; Halbert, C H

2017-01-01

Although the association between social context and health has been demonstrated previously, much less is known about network interactions by gender, race/ethnicity, and sociodemographic characteristics. Given the variability in cancer outcomes among groups, research on these relationships may have important implications for addressing cancer health disparities. We examined the literature on social networks and cancer across the cancer continuum among adults. Relevant studies (N=16) were identified using two common databases: PubMed and Google Scholar. Most studies used a prospective cohort study design (n=9), included women only (n=11), and were located in the United States (n=14). Seventy-five percent of the studies reviewed used a validated scale or validated items to measure social networks (n=12). Only one study examined social network differences by race, 57.1% (n=8) focused on breast cancer alone, 14.3% (n=2) explored colorectal cancer or multiple cancers simultaneously, and 7.1% (n=1) only prostate cancer. More than half of the studies included multiple ethnicities in the sample, while one study included only low-income subjects. Despite findings of associations between social networks and cancer survival, risk, and screening, none of the studies utilized social networks as a mechanism for reducing health disparities; however, such an approach has been utilized for infectious disease control. Social networks and the support provided within these networks have important implications for health behaviors and ultimately cancer disparities. This review serves as the first step toward dialog on social networks as a missing component in the social determinants of cancer disparities literature that could move the needle upstream to target adverse cancer outcomes among vulnerable populations. © 2017 Elsevier Inc. All rights reserved.

Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps

PubMed Central

Kuperstein, I; Bonnet, E; Nguyen, H-A; Cohen, D; Viara, E; Grieco, L; Fourquet, S; Calzone, L; Russo, C; Kondratova, M; Dutreix, M; Barillot, E; Zinovyev, A

2015-01-01

Cancerogenesis is driven by mutations leading to aberrant functioning of a complex network of molecular interactions and simultaneously affecting multiple cellular functions. Therefore, the successful application of bioinformatics and systems biology methods for analysis of high-throughput data in cancer research heavily depends on availability of global and detailed reconstructions of signalling networks amenable for computational analysis. We present here the Atlas of Cancer Signalling Network (ACSN), an interactive and comprehensive map of molecular mechanisms implicated in cancer. The resource includes tools for map navigation, visualization and analysis of molecular data in the context of signalling network maps. Constructing and updating ACSN involves careful manual curation of molecular biology literature and participation of experts in the corresponding fields. The cancer-oriented content of ACSN is completely original and covers major mechanisms involved in cancer progression, including DNA repair, cell survival, apoptosis, cell cycle, EMT and cell motility. Cell signalling mechanisms are depicted in detail, together creating a seamless ‘geographic-like' map of molecular interactions frequently deregulated in cancer. The map is browsable using NaviCell web interface using the Google Maps engine and semantic zooming principle. The associated web-blog provides a forum for commenting and curating the ACSN content. ACSN allows uploading heterogeneous omics data from users on top of the maps for visualization and performing functional analyses. We suggest several scenarios for ACSN application in cancer research, particularly for visualizing high-throughput data, starting from small interfering RNA-based screening results or mutation frequencies to innovative ways of exploring transcriptomes and phosphoproteomes. Integration and analysis of these data in the context of ACSN may help interpret their biological significance and formulate mechanistic hypotheses

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

PubMed

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.

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

A postdoctoral position is available in Dr. Efsun Arda’s Developmental Genomics Group within the Laboratory of Receptor Biology and Gene Expression Branch at the National Cancer Institute (NCI), National Institutes of Health (NIH). Our research is focused on understanding the regulatory networks that govern pancreas cell identity and function in the context of diabetes and cancer. The lab is highly interdisciplinary and uses state-of-the-art technologies to address outstanding questions in human pancreas biology. The appointment is renewed annually upon performance evaluation for a maximum of five years. The candidate will be fully funded by a competitive intramural Center for Cancer Research (CCR) fellowship. Other fellowship opportunities outside NIH are also available and applications will be supported. CCR provides a highly collaborative, enabling environment for research fellows with more than 40 core facilities ranging from bioinformatics and computing, chemistry and structural biology, flow cytometry, genomics, imaging and microscopy, pharmacology, proteomics and single cell analysis.

Leadership in complex networks: the importance of network position and strategic action in a translational cancer research network.

PubMed

Long, Janet C; Cunningham, Frances C; Wiley, Janice; Carswell, Peter; Braithwaite, Jeffrey

2013-10-11

Leadership behaviour in complex networks is under-researched, and little has been written concerning leadership of translational research networks (TRNs) that take discoveries made 'at the bench' and translate them into practices used 'at the bedside.' Understanding leaders' opportunities and behaviours within TRNs working to solve this key problem in implementing evidence into clinical practice is therefore important. This study explored the network position of governing body members and perceptions of their role in a new TRN in Sydney, Australia. The paper asks three questions: Firstly, do the formal, mandated leaders of this TRN hold key positions of centrality or brokerage in the informal social network of collaborative ties? Secondly, if so, do they recognise the leadership opportunities that their network positions afford them? Thirdly, what activities associated with these key roles do they believe will maximise the TRN's success? Semi-structured interviews of all 14 governing body members conducted in early 2012 explored perceptions of their roles and sought comments on a list of activities drawn from review of successful transdisciplinary collaboratives combined with central and brokerage roles. An on-line, whole network survey of all 68 TRN members sought to understand and map existing collaborative connections. Leaders' positions in the network were assessed using UCInet, and graphs were generated in NetDraw. Social network analysis identified that governing body members had high centrality and high brokerage potential in the informal network of work-related ties. Interviews showed perceived challenges including 'silos' and the mismatch between academic and clinical goals of research. Governing body members recognised their central positions, which would facilitate the leadership roles of leading, making decisions, and providing expert advice necessary for the co-ordination of effort and relevant input across domains. Brokerage potential was recognised

Leadership in complex networks: the importance of network position and strategic action in a translational cancer research network

PubMed Central

2013-01-01

Background Leadership behaviour in complex networks is under-researched, and little has been written concerning leadership of translational research networks (TRNs) that take discoveries made ‘at the bench’ and translate them into practices used ‘at the bedside.’ Understanding leaders’ opportunities and behaviours within TRNs working to solve this key problem in implementing evidence into clinical practice is therefore important. This study explored the network position of governing body members and perceptions of their role in a new TRN in Sydney, Australia. The paper asks three questions: Firstly, do the formal, mandated leaders of this TRN hold key positions of centrality or brokerage in the informal social network of collaborative ties? Secondly, if so, do they recognise the leadership opportunities that their network positions afford them? Thirdly, what activities associated with these key roles do they believe will maximise the TRN’s success? Methods Semi-structured interviews of all 14 governing body members conducted in early 2012 explored perceptions of their roles and sought comments on a list of activities drawn from review of successful transdisciplinary collaboratives combined with central and brokerage roles. An on-line, whole network survey of all 68 TRN members sought to understand and map existing collaborative connections. Leaders’ positions in the network were assessed using UCInet, and graphs were generated in NetDraw. Results Social network analysis identified that governing body members had high centrality and high brokerage potential in the informal network of work-related ties. Interviews showed perceived challenges including ‘silos’ and the mismatch between academic and clinical goals of research. Governing body members recognised their central positions, which would facilitate the leadership roles of leading, making decisions, and providing expert advice necessary for the co-ordination of effort and relevant input across

Mapping the emergence and development of translational cancer research.

PubMed

Cambrosio, Alberto; Keating, Peter; Mercier, Simon; Lewison, Grant; Mogoutov, Andrei

2006-12-01

Cancer research is one of the principal targets of translational research, yet the nature of the relationships between different forms of cancer research remains controversial. The paper examines publications in the cancer field during the 1980-2000 period. A network analysis software program was used to map evolving patterns of inter-citations between cancer publications, their different research levels and the transformation of their relational content. Both inter-citation and content maps provide striking evidence of the consolidation in the 1990s of a translational interface that was practically non existent a few decades before. In 1980, research was polarized according to the allegiance to either a clinical or a laboratory style. This same duality obtains in the year 2000, albeit with the additional presence of a third, biomedical player whose activities are similarly structured by a common orientation, rather than by an exclusive commitment to a specific sub-domain.

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

A postdoctoral position is available in Dr. Efsun Arda’s Developmental Genomics Group within the Laboratory of Receptor Biology and Gene Expression Branch at the National Cancer Institute (NCI), National Institutes of Health (NIH). Our research is focused on understanding the regulatory networks that govern pancreas cell identity and function in the context of diabetes and

ICan: An Integrated Co-Alteration Network to Identify Ovarian Cancer-Related Genes

PubMed Central

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

2015-01-01

Background 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. Results 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). Conclusion 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. PMID:25803614

Differential network entropy reveals cancer system hallmarks

PubMed Central

West, James; Bianconi, Ginestra; Severini, Simone; Teschendorff, Andrew E.

2012-01-01

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network we here demonstrate that cancer cells are characterised by an increase in network entropy. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local network entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local correlation patterns. In particular, we find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in network entropy. These findings may have potential implications for identifying novel drug targets. PMID:23150773

Online Social Networks - Opportunities for Empowering Cancer Patients.

PubMed

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.

A Multi-Method Approach for Proteomic Network Inference in 11 Human Cancers.

PubMed

Şenbabaoğlu, Yasin; Sümer, Selçuk Onur; Sánchez-Vega, Francisco; Bemis, Debra; Ciriello, Giovanni; Schultz, Nikolaus; Sander, Chris

2016-02-01

Protein expression and post-translational modification levels are tightly regulated in neoplastic cells to maintain cellular processes known as 'cancer hallmarks'. The first Pan-Cancer initiative of The Cancer Genome Atlas (TCGA) Research Network has aggregated protein expression profiles for 3,467 patient samples from 11 tumor types using the antibody based reverse phase protein array (RPPA) technology. The resultant proteomic data can be utilized to computationally infer protein-protein interaction (PPI) networks and to study the commonalities and differences across tumor types. In this study, we compare the performance of 13 established network inference methods in their capacity to retrieve the curated Pathway Commons interactions from RPPA data. We observe that no single method has the best performance in all tumor types, but a group of six methods, including diverse techniques such as correlation, mutual information, and regression, consistently rank highly among the tested methods. We utilize the high performing methods to obtain a consensus network; and identify four robust and densely connected modules that reveal biological processes as well as suggest antibody-related technical biases. Mapping the consensus network interactions to Reactome gene lists confirms the pan-cancer importance of signal transduction pathways, innate and adaptive immune signaling, cell cycle, metabolism, and DNA repair; and also suggests several biological processes that may be specific to a subset of tumor types. Our results illustrate the utility of the RPPA platform as a tool to study proteomic networks in cancer.

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

PubMed

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.

A Review of the Accomplishments of the CTD² Network | Office of Cancer Genomics

Cancer.gov

The Office of Cancer Genomics (OCG) Cancer Target Discovery and Development or CTD2 initiative was established by the National Cancer Institute (NCI) to accelerate the “translation” of high-throughput, high-content genomic data to the bedside through functional genomics. The CTD2 initiative is a collaborative network of 13 different research teams, or Centers.

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further

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

PubMed Central

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

2017-01-01

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 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, called 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. PMID:26000852

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

PubMed

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.

Parenclitic Network Analysis of Methylation Data for Cancer Identification

PubMed Central

Karsakov, Alexander; Bartlett, Thomas; Ryblov, Artem; Meyerov, Iosif; Ivanchenko, Mikhail; Zaikin, Alexey

2017-01-01

We make use of ideas from the theory of complex networks to implement a machine learning classification of human DNA methylation data, that carry signatures of cancer development. The data were obtained from patients with various kinds of cancers and represented as parenclictic networks, wherein nodes correspond to genes, and edges are weighted according to pairwise variation from control group subjects. We demonstrate that for the 10 types of cancer under study, it is possible to obtain a high performance of binary classification between cancer-positive and negative samples based on network measures. Remarkably, an accuracy as high as 93−99% is achieved with only 12 network topology indices, in a dramatic reduction of complexity from the original 15295 gene methylation levels. Moreover, it was found that the parenclictic networks are scale-free in cancer-negative subjects, and deviate from the power-law node degree distribution in cancer. The node centrality ranking and arising modular structure could provide insights into the systems biology of cancer. PMID:28107365

Prostate Cancer Biorepository Network (PCBN)

DTIC Science & Technology

2017-10-01

Award Number: W81XWH-14-2-0183 TITLE: Prostate Cancer Biorepository Network (PCBN) PRINCIPAL INVESTIGATOR: Colm Morrissey CONTRACTING...1. REPORT DATE October 2017 2. REPORT TYPE Annual 3. DATES COVERED 09/30/2016 - 09/29/2017 4. TITLE AND SUBTITLE Prostate Cancer Biorepository...DISTRIBUTION / AVAILABILITY STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The Genitourinary Cancer

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

PubMed

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

Sustaining Research Networks: the Twenty-Year Experience of the HMO Research Network

PubMed Central

Steiner, John F.; Paolino, Andrea R.; Thompson, Ella E.; Larson, Eric B.

2014-01-01

Purpose: As multi-institutional research networks assume a central role in clinical research, they must address the challenge of sustainability. Despite its importance, the concept of network sustainability has received little attention in the literature, and the sustainability strategies of durable scientific networks have not been described. Innovation: The Health Maintenance Organization Research Network (HMORN) is a consortium of 18 research departments in integrated health care delivery systems with over 15 million members in the United States and Israel. The HMORN has coordinated federally funded scientific networks and studies since 1994. This case study describes the HMORN approach to sustainability, proposes an operational definition of network sustainability, and identifies 10 essential elements that can enhance sustainability. Credibility: The sustainability framework proposed here is drawn from prior publications on organizational issues by HMORN investigators and from the experience of recent HMORN leaders and senior staff. Conclusion and Discussion: Network sustainability can be defined as (1) the development and enhancement of shared research assets to facilitate a sequence of research studies in a specific content area or multiple areas, and (2) a community of researchers and other stakeholders who reuse and develop those assets. Essential elements needed to develop the shared assets of a network include: network governance; trustworthy data and processes for sharing data; shared knowledge about research tools; administrative efficiency; physical infrastructure; and infrastructure funding. The community of researchers within a network is enhanced by: a clearly defined mission, vision and values; protection of human subjects; a culture of collaboration; and strong relationships with host organizations. While the importance of these elements varies based on the membership and goals of a network, this framework for sustainability can enhance strategic

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

PubMed

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

2015-05-30

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.

Endogenous molecular network reveals two mechanisms of heterogeneity within gastric cancer

PubMed Central

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

[Translation of knowledge on cervical cancer: is there a gap between research on causes and research on patient care?].

PubMed

Fajardo-Ortiz, David; Ochoa, Héctor; García, Luis; Castaño, Víctor

2014-02-01

This article constructs a map on the translation of knowledge concerning cervical cancer, based on citation networks analysis and the use of Gene Ontology terms and Medical Subject Headings. We identified two areas of research that are poorly interconnected and differ in structure, content, and evolution. One focuses on causes of cancer and the other on patient care. The first research area showed a knowledge translation process where basic research and clinical research are communicated through a set of articles that consolidate human papillomavirus infection as the necessary cause of cervical cancer. The first area aims to prevent HPV infection and the development of cervical cancer, while the second aims to stage and treat the disease.

A Review of Barriers to Minorities' Participation in Cancer Clinical Trials: Implications for Future Cancer Research.

PubMed

Salman, Ali; Nguyen, Claire; Lee, Yi-Hui; Cooksey-James, Tawna

2016-04-01

To enhance nurses' awareness and competencies in practice and research by reporting the common barriers to participation of minorities in cancer clinical trials and discussing facilitators and useful strategies for recruitment. Several databases were searched for articles published in peer reviewed journals. Some of the barriers to minorities' participation in clinical trials were identified within the cultural social-context of cancer patients. The involvement of community networking was suggested as the most effective strategy for the recruitment of minorities in cancer clinical trials. Using culturally sensitive approaches to enhance ethnic minorities' participation is important for advancing cancer care and eliminating health disparities. Awareness of barriers and potential facilitators to the enrollment of ethnic minority cancer patients may contribute to enhancing nurses' competencies of recruiting ethnic minorities in nursing research, playing efficient roles in cancer clinical trials team, and providing culturally competent quality care.

Network-based reading system for lung cancer screening CT

NASA Astrophysics Data System (ADS)

Fujino, Yuichi; Fujimura, Kaori; Nomura, Shin-ichiro; Kawashima, Harumi; Tsuchikawa, Megumu; Matsumoto, Toru; Nagao, Kei-ichi; Uruma, Takahiro; Yamamoto, Shinji; Takizawa, Hotaka; Kuroda, Chikazumi; Nakayama, Tomio

2006-03-01

This research aims to support chest computed tomography (CT) medical checkups to decrease the death rate by lung cancer. We have developed a remote cooperative reading system for lung cancer screening over the Internet, a secure transmission function, and a cooperative reading environment. It is called the Network-based Reading System. A telemedicine system involves many issues, such as network costs and data security if we use it over the Internet, which is an open network. In Japan, broadband access is widespread and its cost is the lowest in the world. We developed our system considering human machine interface and security. It consists of data entry terminals, a database server, a computer aided diagnosis (CAD) system, and some reading terminals. It uses a secure Digital Imaging and Communication in Medicine (DICOM) encrypting method and Public Key Infrastructure (PKI) based secure DICOM image data distribution. We carried out an experimental trial over the Japan Gigabit Network (JGN), which is the testbed for the Japanese next-generation network, and conducted verification experiments of secure screening image distribution, some kinds of data addition, and remote cooperative reading. We found that network bandwidth of about 1.5 Mbps enabled distribution of screening images and cooperative reading and that the encryption and image distribution methods we proposed were applicable to the encryption and distribution of general DICOM images via the Internet.

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

PubMed

Erdoğan, Cihat; Kurt, Zeyneb; Diri, Banu

2017-01-01

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.

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

PubMed Central

Kurt, Zeyneb; Diri, Banu

2017-01-01

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. PMID:29145449

Integrated Network Analyses for Functional Genomic Studies in Cancer

PubMed Central

Wilson, Jennifer L.; Hemann, Michael T.; Fraenkel, Ernest; Lauffenburger, Douglas A.

2013-01-01

RNA-interference (RNAi) studies hold great promise for functional investigation of the significance of genetic variations and mutations, as well as potential synthetic lethalities, for understanding and treatment of cancer, yet technical and conceptual issues currently diminish the potential power of this approach. While numerous research groups are usefully employing this kind of functional genomic methodology to identify molecular mediators of disease severity, response, and resistance to treatment, findings are generally confounded by “off-target” effects. These effects arise from a variety of issues beyond non-specific reagent behavior, such as biological cross-talk and feedback processes so thus can occur even with specific perturbation. Interpreting RNAi results in a network framework instead of merely as individual “hits” or “targets” leverages contributions from all hit/target contributions to pathways via their relationships with other network nodes. This interpretation can ameliorate dependence on individual reagent performance and increase confidence in biological validation. Here we provide background on RNAi studies in cancer applications, review key challenges with functional genomics, and motivate the use of network models grounded in pathway analyses. PMID:23811269

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

ERIC Educational Resources Information Center

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…

Implementation of national comprehensive cancer network evidence-based guidelines to prevent and treat cancer-related infections.

PubMed

Wood, Sylvia K; Payne, Judith K

2012-06-01

Clinical practice guidelines are an important result of evidence-based research. However, current clinical practice remains out of step with the rapid pace of research advancements. Often, decades pass before research is translated into clinical practice. The National Comprehensive Cancer Network (NCCN) has created evidence-based clinical guidelines to promote effective clinical practice. Formerly, the NCCN established guidelines to reduce cancer-related infections only for neutropenic patients; however, they have expanded their guidelines beyond neutropenia to prevent and treat cancer-related infections. Implementing scientific evidence into clinical practice is challenging and complex, and healthcare professionals should understand barriers to implementing clinical practice guidelines to ensure successful translation into practice. This article provides a brief review of NCCN guidelines and describes common barriers encountered during implementation. In addition, a conceptual framework is offered to help identify and address potential concerns before and after adoption of guidelines.

IT behind a platform for Translational Cancer Research - concept and objectives.

PubMed

Steffens, Michael; Husmann, Gabriele; Koca, Mithat; Lablans, Martin; Komor, Martina; Zeissig, Sylke; Emrich, Katharina; Brandts, Christian; Serve, Hubert; Blettner, Maria; Uckert, Frank

2012-01-01

The German Consortium for Translational Cancer Research (DKTK) and the Rhine-Main Translational Cancer Research Network (RM-TCRN) are designed to exploit large population cohorts of cancer patients for the purpose of bio-banking, clinical trials, and clinical cancer registration. Hence, the success of these platforms is heavily dependent on the close interlinking of clinical data from cancer patients, information from study registries, and data from bio-banking systems of different laboratories and scientific institutions. This article referring to the poster discusses the main challenges of the platforms from an information technology point of view, legal and data security issues, and outlines an integrative IT-concept concerning a decentralized, distributed search approach where data management and search is in compliance with existing legislative rules.

United States-Latin America Cancer Research Network (US-LA CRN)

Cancer.gov

The US–LA CRN was established in 2009 to increase cancer research capacity in Latin America. NCI formalized bilateral agreements with the governments of Argentina, Brazil, Chile, Colombia, Mexico, Peru, Puerto Rico, and Uruguay, to facilitate interactions at the government, institution, and investigator levels.

Medical education practice-based research networks: Facilitating collaborative research.

PubMed

Schwartz, Alan; Young, Robin; Hicks, Patricia J

2016-01-01

Research networks formalize and institutionalize multi-site collaborations by establishing an infrastructure that enables network members to participate in research, propose new studies, and exploit study data to move the field forward. Although practice-based clinical research networks are now widespread, medical education research networks are rapidly emerging. In this article, we offer a definition of the medical education practice-based research network, a brief description of networks in existence in July 2014 and their features, and a more detailed case study of the emergence and early growth of one such network, the Association of Pediatric Program Directors Longitudinal Educational Assessment Research Network (APPD LEARN). We searched for extant networks through peer-reviewed literature and the world-wide web. We identified 15 research networks in medical education founded since 2002 with membership ranging from 8 to 120 programs. Most focus on graduate medical education in primary care or emergency medicine specialties. We offer four recommendations for the further development and spread of medical education research networks: increasing faculty development, obtaining central resources, studying networks themselves, and developing networks of networks.

Creating Community–Academic Partnerships for Cancer Disparities Research and Health Promotion

PubMed Central

Meade, Cathy D.; Menard, Janelle M.; Luque, John S.; Martinez-Tyson, Dinorah; Gwede, Clement K.

2010-01-01

To effectively attenuate cancer disparities in multiethnic, medically underserved populations, interventions must be developed collaboratively through solid community–academic partnerships and driven by community-based participatory research (CBPR). The Tampa Bay Community Cancer Network (TBCCN) has been created to identify and implement interventions to address local cancer disparities in partnership with community-based nonprofit organizations, faith-based groups, community health centers, local media, and adult literacy and education organizations. TBCCN activities and research efforts are geared toward addressing critical information and access issues related to cancer control and prevention in diverse communities in the Tampa Bay area. Such efforts include cross-cultural health promotion, screening, and awareness activities in addition to applied research projects that are rooted in communities and guided by CBPR methods. This article describes these activities as examples of partnership building to positively affect cancer disparities, promote community health, and set the stage for community-based research partnerships. PMID:19822724

Network regularised Cox regression and multiplex network models to predict disease comorbidities and survival of cancer.

PubMed

Xu, Haoming; Moni, Mohammad Ali; Liò, Pietro

2015-12-01

In cancer genomics, gene expression levels provide important molecular signatures for all types of cancer, and this could be very useful for predicting the survival of cancer patients. However, the main challenge of gene expression data analysis is high dimensionality, and microarray is characterised by few number of samples with large number of genes. To overcome this problem, a variety of penalised Cox proportional hazard models have been proposed. We introduce a novel network regularised Cox proportional hazard model and a novel multiplex network model to measure the disease comorbidities and to predict survival of the cancer patient. Our methods are applied to analyse seven microarray cancer gene expression datasets: breast cancer, ovarian cancer, lung cancer, liver cancer, renal cancer and osteosarcoma. Firstly, we applied a principal component analysis to reduce the dimensionality of original gene expression data. Secondly, we applied a network regularised Cox regression model on the reduced gene expression datasets. By using normalised mutual information method and multiplex network model, we predict the comorbidities for the liver cancer based on the integration of diverse set of omics and clinical data, and we find the diseasome associations (disease-gene association) among different cancers based on the identified common significant genes. Finally, we evaluated the precision of the approach with respect to the accuracy of survival prediction using ROC curves. We report that colon cancer, liver cancer and renal cancer share the CXCL5 gene, and breast cancer, ovarian cancer and renal cancer share the CCND2 gene. Our methods are useful to predict survival of the patient and disease comorbidities more accurately and helpful for improvement of the care of patients with comorbidity. Software in Matlab and R is available on our GitHub page: https://github.com/ssnhcom/NetworkRegularisedCox.git. Copyright © 2015. Published by Elsevier Ltd.

Network perturbation by recurrent regulatory variants in cancer

PubMed Central

Cho, Ara; Lee, Insuk; Choi, Jung Kyoon

2017-01-01

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. PMID:28333928

Review of mass spectrometry-based metabolomics in cancer research

PubMed Central

Liesenfeld, David B.; Habermann, Nina; Owen, Robert W.; Scalbert, Augustin; Ulrich, Cornelia M.

2014-01-01

Metabolomics, the systematic investigation of all metabolites present within a biological system, is used in biomarker development for many human diseases, including cancer. In this review we investigate the current role of mass spectrometry-based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case-control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including <100 patients. Standardization is required especially concerning sample preparation and data analysis. In a second part of this review, we reconstructed a metabolic network of cancer patients by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed. PMID:24096148

Medical education practice-based research networks: Facilitating collaborative research

PubMed Central

Schwartz, Alan; Young, Robin; Hicks, Patricia J.; APPD LEARN, For

2016-01-01

Abstract Background: Research networks formalize and institutionalize multi-site collaborations by establishing an infrastructure that enables network members to participate in research, propose new studies, and exploit study data to move the field forward. Although practice-based clinical research networks are now widespread, medical education research networks are rapidly emerging. Aims: In this article, we offer a definition of the medical education practice-based research network, a brief description of networks in existence in July 2014 and their features, and a more detailed case study of the emergence and early growth of one such network, the Association of Pediatric Program Directors Longitudinal Educational Assessment Research Network (APPD LEARN). Methods: We searched for extant networks through peer-reviewed literature and the world-wide web. Results: We identified 15 research networks in medical education founded since 2002 with membership ranging from 8 to 120 programs. Most focus on graduate medical education in primary care or emergency medicine specialties. Conclusions: We offer four recommendations for the further development and spread of medical education research networks: increasing faculty development, obtaining central resources, studying networks themselves, and developing networks of networks. PMID:25319404

Health Communications Specialist | Center for Cancer Research

Cancer.gov

Here’s an exciting opportunity for a talented communicator to be part of the effort to find cures for rare cancers and join our multidisciplinary team launching the My Pediatric and Adult Rare Tumor Network (MyPART). The mission of MyPART is to increase patient and patient family involvement in rare tumor research and develop new therapies for rare pediatric and adult solid

Towards a Quantitative Endogenous Network Theory of Cancer Genesis and Progression: beyond ``cancer as diseases of genome''

NASA Astrophysics Data System (ADS)

Ao, Ping

2011-03-01

There has been a tremendous progress in cancer research. However, it appears the current dominant cancer research framework of regarding cancer as diseases of genome leads impasse. Naturally questions have been asked that whether it is possible to develop alternative frameworks such that they can connect both to mutations and other genetic/genomic effects and to environmental factors. Furthermore, such framework can be made quantitative and with predictions experimentally testable. In this talk, I will present a positive answer to this calling. I will explain on our construction of endogenous network theory based on molecular-cellular agencies as dynamical variable. Such cancer theory explicitly demonstrates a profound connection to many fundamental concepts in physics, as such stochastic non-equilibrium processes, ``energy'' landscape, metastability, etc. It suggests that neneath cancer's daunting complexity may lie a simplicity that gives grounds for hope. The rationales behind such theory, its predictions, and its initial experimental verifications will be presented. Supported by USA NIH and China NSF.

A basis for translational cancer research on aetiology, pathogenesis and prognosis: Guideline for standardised and population-based linkages of biobanks to cancer registries.

PubMed

Dillner, Joakim

2015-06-01

Population-based cancer research is paramount for controlling cancer. Cancer research is increasingly dependent on access to biospecimens from subjects that have been followed-up for future health outcomes. This is achieved using longitudinal follow-up of cohorts and biobanks using cancer registry linkages. All over the world, more and more large population-based cohorts and advanced biobanking facilities are established. International standardisation and networking in the linkage of cohorts and biobanks to cancer registries is required in order to enable international cancer research and comparability of research results. An international operating procedure and standard minimum dataset for linkages of biobanks, cohorts and cancer registries is proposed. An internationally comparable provision of well characterised study bases for molecular cancer research will be an essential prerequisite for the success of translational medicine. Copyright © 2013 Elsevier Ltd. All rights reserved.

Requirements for data integration platforms in biomedical research networks: a reference model

PubMed Central

Knaup, Petra

2015-01-01

Biomedical research networks need to integrate research data among their members and with external partners. To support such data sharing activities, an adequate information technology infrastructure is necessary. To facilitate the establishment of such an infrastructure, we developed a reference model for the requirements. The reference model consists of five reference goals and 15 reference requirements. Using the Unified Modeling Language, the goals and requirements are set into relation to each other. In addition, all goals and requirements are described textually in tables. This reference model can be used by research networks as a basis for a resource efficient acquisition of their project specific requirements. Furthermore, a concrete instance of the reference model is described for a research network on liver cancer. The reference model is transferred into a requirements model of the specific network. Based on this concrete requirements model, a service-oriented information technology architecture is derived and also described in this paper. PMID:25699205

Requirements for data integration platforms in biomedical research networks: a reference model.

PubMed

Ganzinger, Matthias; Knaup, Petra

2015-01-01

Biomedical research networks need to integrate research data among their members and with external partners. To support such data sharing activities, an adequate information technology infrastructure is necessary. To facilitate the establishment of such an infrastructure, we developed a reference model for the requirements. The reference model consists of five reference goals and 15 reference requirements. Using the Unified Modeling Language, the goals and requirements are set into relation to each other. In addition, all goals and requirements are described textually in tables. This reference model can be used by research networks as a basis for a resource efficient acquisition of their project specific requirements. Furthermore, a concrete instance of the reference model is described for a research network on liver cancer. The reference model is transferred into a requirements model of the specific network. Based on this concrete requirements model, a service-oriented information technology architecture is derived and also described in this paper.

Lessons Learned from the Young Breast Cancer Survivorship Network.

PubMed

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.

Ovarian Cancer Differential Interactome and Network Entropy Analysis Reveal New Candidate Biomarkers.

PubMed

Ayyildiz, Dilara; Gov, Esra; Sinha, Raghu; Arga, Kazim Yalcin

2017-05-01

Ovarian cancer is one of the most common cancers and has a high mortality rate due to insidious symptoms and lack of robust diagnostics. A hitherto understudied concept in cancer pathogenesis may offer new avenues for innovation in ovarian cancer biomarker development. Cancer cells are characterized by an increase in network entropy, and several studies have exploited this concept to identify disease-associated gene and protein modules. We report in this study the changes in protein-protein interactions (PPIs) in ovarian cancer within a differential network (interactome) analysis framework utilizing the entropy concept and gene expression data. A compendium of six transcriptome datasets that included 140 samples from laser microdissected epithelial cells of ovarian cancer patients and 51 samples from healthy population was obtained from Gene Expression Omnibus, and the high confidence human protein interactome (31,465 interactions among 10,681 proteins) was used. The uncertainties of the up- or downregulation of PPIs in ovarian cancer were estimated through an entropy formulation utilizing combined expression levels of genes, and the interacting protein pairs with minimum uncertainty were identified. We identified 105 proteins with differential PPI patterns scattered in 11 modules, each indicating significantly affected biological pathways in ovarian cancer such as DNA repair, cell proliferation-related mechanisms, nucleoplasmic translocation of estrogen receptor, extracellular matrix degradation, and inflammation response. In conclusion, we suggest several PPIs as biomarker candidates for ovarian cancer and discuss their future biological implications as potential molecular targets for pharmaceutical development as well. In addition, network entropy analysis is a concept that deserves greater research attention for diagnostic innovation in oncology and tumor pathogenesis.

Research Nurse | Center for Cancer Research

Cancer.gov

We are looking for a Research Nurse (Accrual Site Coordinator) to join our neuro-oncology clinical team to help us provide administrative and coordination support for the Brain Tumor Trials Collaborative (BTTC). Duties include, but are not limited to, monitoring and overseeing activities pertaining to clinical protocols and administrative operations supporting the BTTC, with limited interaction with study participants.  Be part of our mission to solve the most important, challenging and neglected problems in modern cancer research and patient care. The National Cancer Institute’s Center for Cancer Research is a world-leading cancer research organization working toward scientific breakthroughs at medicine’s cutting edge. Our scientists can’t do it alone. It takes an extraordinary team of researchers, clinical experts and administrators to improve the lives of cancer patients and answer the most important questions in cancer biology and treatment.

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

PubMed

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.

Systematic Identification of Druggable Epithelial-Stromal Crosstalk Signaling Networks in Ovarian Cancer.

PubMed

Yeung, Tsz-Lun; Sheng, Jianting; Leung, Cecilia S; Li, Fuhai; Kim, Jaeyeon; Ho, Samuel Y; Matzuk, Martin M; Lu, Karen H; Wong, Stephen T C; Mok, Samuel C

2018-05-31

Bulk tumor tissue samples are used for generating gene expression profiles in most research studies, making it difficult to decipher the stroma-cancer crosstalk networks. In the present study, we describe the use of microdissected transcriptome profiles for the identification of cancer-stroma crosstalk networks with prognostic value, which presents a unique opportunity for developing new treatment strategies for ovarian cancer. Transcriptome profiles from microdissected ovarian cancer-associated fibroblasts (CAFs) and ovarian cancer cells from patients with high-grade serous ovarian cancer (n = 70) were used as input data for the computational systems biology program CCCExplorer to uncover crosstalk networks between various cell types within the tumor microenvironment. The crosstalk analysis results were subsequently used for discovery of new indications for old drugs in ovarian cancer by computational ranking of candidate agents. Survival analysis was performed on ovarian tumor-bearing Dicer/Pten double-knockout mice treated with calcitriol, a US Food and Drug Administration-approved agent that suppresses the Smad signaling cascade, or vehicle control (9-11 mice per group). All statistical tests were two-sided. Activation of TGF-β-dependent and TGF-β-independent Smad signaling was identified in a particular subtype of CAFs and was associated with poor patient survival (patients with higher levels of Smad-regulated gene expression by CAFs: median overall survival = 15 months, 95% confidence interval [CI] = 12.7 to 17.3 months; vs patients with lower levels of Smad-regulated gene expression: median overall survival = 26 months, 95% CI = 15.9 to 36.1 months, P = .02). In addition, the activated Smad signaling identified in CAFs was found to be targeted by repositioning calcitriol. Calcitriol suppressed Smad signaling in CAFs, inhibited tumor progression in mice, and prolonged the median survival duration of ovarian cancer-bearing mice from 36 to 48 weeks (P = .04

Hypothesis generation using network structures on community health center cancer-screening performance.

PubMed

Carney, Timothy Jay; Morgan, Geoffrey P; Jones, Josette; McDaniel, Anna M; Weaver, Michael T; Weiner, Bryan; Haggstrom, David A

2015-10-01

Nationally sponsored cancer-care quality-improvement efforts have been deployed in community health centers to increase breast, cervical, and colorectal cancer-screening rates among vulnerable populations. Despite several immediate and short-term gains, screening rates remain below national benchmark objectives. Overall improvement has been both difficult to sustain over time in some organizational settings and/or challenging to diffuse to other settings as repeatable best practices. Reasons for this include facility-level changes, which typically occur in dynamic organizational environments that are complex, adaptive, and unpredictable. This study seeks to understand the factors that shape community health center facility-level cancer-screening performance over time. This study applies a computational-modeling approach, combining principles of health-services research, health informatics, network theory, and systems science. To investigate the roles of knowledge acquisition, retention, and sharing within the setting of the community health center and to examine their effects on the relationship between clinical decision support capabilities and improvement in cancer-screening rate improvement, we employed Construct-TM to create simulated community health centers using previously collected point-in-time survey data. Construct-TM is a multi-agent model of network evolution. Because social, knowledge, and belief networks co-evolve, groups and organizations are treated as complex systems to capture the variability of human and organizational factors. In Construct-TM, individuals and groups interact by communicating, learning, and making decisions in a continuous cycle. Data from the survey was used to differentiate high-performing simulated community health centers from low-performing ones based on computer-based decision support usage and self-reported cancer-screening improvement. This virtual experiment revealed that patterns of overall network symmetry, agent

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

Cancer.gov

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

Effective recruitment strategies and community-based participatory research: Community Networks Program Centers’ recruitment in cancer prevention studies

PubMed Central

Greiner, K. Allen; Friedman, Daniela B.; Adams, Swann Arp; Gwede, Clement K.; Cupertino, Paula; Engelman, Kimberly K.; Meade, Cathy D.; Hébert, James R.

2014-01-01

Background Community-based participatory research (CBPR) approaches that involve community and academic partners in activities ranging from protocol design through dissemination of study findings can increase recruitment of medically underserved and underrepresented racial/ethnic minority populations into biomedical research. Settings/Methods Five cancer screening and prevention trials in three NCI-funded Community Networks Program Centers (CNPCs); in Florida, Kansas and South Carolina, were conducted across diverse populations. Data were collected on total time period of recruitment, ratios of participants enrolled over potential participants approached, selected CBPR strategies, capacity-building development, and systematic procedures for community stakeholder involvement. Findings Community-engaged approaches employed included establishing co-learning opportunities, participatory procedures for community-academic involvement, and community and clinical capacity building. A relatively large proportion of individuals identified for recruitment were actually approached (between 50% and 100%). The proportion of subjects who were eligible among all those approached ranged from 25% to over 70% (in the community setting). Recruitment rates were very high (78%–100% of eligible individuals approached) and the proportion who refused or who were not interested among those approached was very low (5%–11%). Conclusions Recruitment strategies used by the CNPCs were associated with low refusal and high enrollment ratios of potential subjects. Adherence to CBPR principles in the spectrum of research activities; from strategic planning to project implementation has significant potential to increase involvement in biomedical research and improve our ability to make appropriate recommendations for cancer prevention and control programming in underrepresented diverse populations. Impact CBPR strategies should be more widely implemented to enhance study recruitment. PMID

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

PubMed

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.

Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures.

PubMed

Li, Yongsheng; Sahni, Nidhi; Yi, Song

2016-11-29

Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.

Singapore Cancer Network (SCAN) Guidelines for Adjuvant Chemotherapy in Resected Non-Small Cell Lung Cancer.

PubMed

2015-10-01

The SCAN lung cancer workgroup aimed to develop Singapore Cancer Network (SCAN) clinical practice guidelines for the use of adjuvant systemic therapy for non-small cell lung cancer 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 Comprehensive Cancer Network (2014), European Society of Medical Oncology (2014), National Institute of Clinical Excellence (2012), Scottish Intercollegiate Guidelines Network (2014), and the Cancer Care Council Australia (2012). Recommendations on the selection of patients, chemotherapy regimen, treatment for stage I disease, treatment for positive margins and treatment options for pN2 disease with negative margins were produced. These adapted guidelines form the SCAN Guidelines 2015 for adjuvant systemic therapy of non-small cell lung cancer.

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

PubMed

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.

Recruiting Young Adult Cancer Survivors for Behavioral Research

PubMed Central

Horowitz, Santina; Marcus, Bess

2012-01-01

Young adults have been dramatically underrepresented in cancer survivorship research. One contributing factor is the difficulty recruiting this population. To identify effective recruitment strategies, the current study assessed the yield of strategies used to recruit young survivors for an exercise intervention including: clinic-based recruitment, recruitment at cancer-related events, mailings, telephone-based recruitment, advertising on the internet, radio, television and social networking media, distributing brochures and word-of-mouth referrals. When taking into account the strategies for which we could track the number of survivors approached, recruitment at an oncology clinic was the most productive: 38 % of those approached were screened and 8 % enrolled. When evaluating which strategy yielded the greatest percentage of the sample, however, mailings were the most productive. Given widespread use of the internet and social networking by young adults, investigators should also consider these low-cost recruitment strategies. PMID:22810954

Recruiting young adult cancer survivors for behavioral research.

PubMed

Rabin, Carolyn; Horowitz, Santina; Marcus, Bess

2013-03-01

Young adults have been dramatically underrepresented in cancer survivorship research. One contributing factor is the difficulty recruiting this population. To identify effective recruitment strategies, the current study assessed the yield of strategies used to recruit young survivors for an exercise intervention including: clinic-based recruitment, recruitment at cancer-related events, mailings, telephone-based recruitment, advertising on the internet, radio, television and social networking media, distributing brochures and word-of-mouth referrals. When taking into account the strategies for which we could track the number of survivors approached, recruitment at an oncology clinic was the most productive: 38 % of those approached were screened and 8 % enrolled. When evaluating which strategy yielded the greatest percentage of the sample, however, mailings were the most productive. Given widespread use of the internet and social networking by young adults, investigators should also consider these low-cost recruitment strategies.

The kidney cancer research priority-setting partnership: Identifying the top 10 research priorities as defined by patients, caregivers, and expert clinicians.

PubMed

Jones, Jennifer; Bhatt, Jaimin; Avery, Jonathan; Laupacis, Andreas; Cowan, Katherine; Basappa, Naveen; Basiuk, Joan; Canil, Christina; Al-Asaaed, Sohaib; Heng, Daniel; Wood, Lori; Stacey, Dawn; Kollmannsberger, Christian; Jewett, Michael A S

2017-12-01

It is critically important to define disease-specific research priorities to better allocate limited resources. There is growing recognition of the value of involving patients and caregivers, as well as expert clinicians in this process. To our knowledge, this has not been done this way for kidney cancer. Using the transparent and inclusive process established by the James Lind Alliance, the Kidney Cancer Research Network of Canada (KCRNC) sponsored a collaborative consensus-based priority-setting partnership (PSP) to identify research priorities in the management of kidney cancer. The final result was identification of 10 research priorities for kidney cancer, which are discussed in the context of current initiatives and gaps in knowledge. This process provided a systematic and effective way to collaboratively establish research priorities with patients, caregivers, and clinicians, and provides a valuable resource for researchers and funding agencies.

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

PubMed

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 (<7) and high (≥7) Gleason grade tumors. A comparison of their major hubs with those of the network for normal samples identified two types of changes associated with disease: (i) Some hub genes increased their degree in the tumor network compared to their degree in the normal network, suggesting that these genes are associated with gain of regulatory control in 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

Epidemiologic research topics in Germany: a keyword network analysis of 2014 DGEpi conference presentations.

PubMed

Peter, Raphael Simon; Brehme, Torben; Völzke, Henry; Muche, Rainer; Rothenbacher, Dietrich; Büchele, Gisela

2016-06-01

Knowledge of epidemiologic research topics as well as trends is useful for scientific societies, researchers and funding agencies. In recent years researchers recognized the usefulness of keyword network analysis for visualizing and analyzing scientific research topics. Therefore, we applied keyword network analysis to present an overview of current epidemiologic research topics in Germany. Accepted submissions to the 9th annual congress of the German Society for Epidemiology (DGEpi) in 2014 were used as data source. Submitters had to choose one of 19 subject areas, and were ask to provide a title, structured abstract, names of authors along with their affiliations, and a list of freely selectable keywords. Keywords had been provided for 262 (82 %) submissions, 1030 keywords in total. Overall the most common keywords were: "migration" (18 times), "prevention" (15 times), followed by "children", "cohort study", "physical activity", and "secondary data analysis" (11 times each). Some keywords showed a certain concentration under one specific subject area, e.g. "migration" with 8 of 18 in social epidemiology or "breast cancer" with 4 of 7 in cancer epidemiology. While others like "physical activity" were equally distributed over multiple subject areas (cardiovascular & metabolic diseases, ageing, methods, paediatrics, prevention & health service research). This keyword network analysis demonstrated the high diversity of epidemiologic research topics with a large number of distinct keywords as presented at the annual conference of the DGEpi.

Identifying causal networks linking cancer processes and anti-tumor immunity using Bayesian network inference and metagene constructs.

PubMed

Kaiser, Jacob L; Bland, Cassidy L; Klinke, David J

2016-03-01

Cancer arises from a deregulation of both intracellular and intercellular networks that maintain system homeostasis. Identifying the architecture of these networks and how they are changed in cancer is a pre-requisite for designing drugs to restore homeostasis. Since intercellular networks only appear in intact systems, it is difficult to identify how these networks become altered in human cancer using many of the common experimental models. To overcome this, we used the diversity in normal and malignant human tissue samples from the Cancer Genome Atlas (TCGA) database of human breast cancer to identify the topology associated with intercellular networks in vivo. To improve the underlying biological signals, we constructed Bayesian networks using metagene constructs, which represented groups of genes that are concomitantly associated with different immune and cancer states. We also used bootstrap resampling to establish the significance associated with the inferred networks. In short, we found opposing relationships between cell proliferation and epithelial-to-mesenchymal transformation (EMT) with regards to macrophage polarization. These results were consistent across multiple carcinomas in that proliferation was associated with a type 1 cell-mediated anti-tumor immune response and EMT was associated with a pro-tumor anti-inflammatory response. To address the identifiability of these networks from other datasets, we could identify the relationship between EMT and macrophage polarization with fewer samples when the Bayesian network was generated from malignant samples alone. However, the relationship between proliferation and macrophage polarization was identified with fewer samples when the samples were taken from a combination of the normal and malignant samples. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:470-479, 2016. © 2016 American Institute of Chemical Engineers.

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

PubMed Central

Creixell, Pau; Schoof, Erwin M.; Simpson, Craig D.; Longden, James; Miller, Chad J.; Lou, Hua Jane; Perryman, Lara; Cox, Thomas R.; Zivanovic, Nevena; Palmeri, Antonio; Wesolowska-Andersen, Agata; Helmer-Citterich, Manuela; Ferkinghoff-Borg, Jesper; Itamochi, Hiroaki; Bodenmiller, Bernd; Erler, Janine T.; Turk, Benjamin E.; Linding, Rune

2015-01-01

Summary 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 rewiring, and the genesis and extinction of phosphorylation sites. We developed a computational platform (ReKINect) to identify NAMs and systematically interpreted the exomes and quantitative (phospho-)proteomes of five ovarian cancer cell lines and the global cancer genome repository. We identified 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-inactivating hotspots in cancer. Our method pinpoints functional NAMs, scales with the complexity of cancer genomes and cell signaling, and may enhance our capability to therapeutically target tumor-specific networks. PMID:26388441

Types of Cancer Research

Cancer.gov

An infographic from the National Cancer Institute (NCI) describing the four broad categories of cancer research: basic research, clinical research, population-based research, and translational research.

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

PubMed

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

Visual gene-network analysis reveals the cancer gene co-expression in human endometrial cancer

PubMed Central

2014-01-01

Background Endometrial cancers (ECs) are the most common form of gynecologic malignancy. Recent studies have reported that ECs reveal distinct markers for molecular pathogenesis, which in turn is linked to the various histological types of ECs. To understand further the molecular events contributing to ECs and endometrial tumorigenesis in general, a more precise identification of cancer-associated molecules and signaling networks would be useful for the detection and monitoring of malignancy, improving clinical cancer therapy, and personalization of treatments. Results ECs-specific gene co-expression networks were constructed by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Important pathways and putative cancer hub genes contribution to tumorigenesis of ECs were identified. An elastic-net regularized classification model was built using the cancer hub gene signatures to predict the phenotypic characteristics of ECs. The 19 cancer hub gene signatures had high predictive power to distinguish among three key principal features of ECs: grade, type, and stage. Intriguingly, these hub gene networks seem to contribute to ECs progression and malignancy via cell-cycle regulation, antigen processing and the citric acid (TCA) cycle. Conclusions The results of this study provide a powerful biomarker discovery platform to better understand the progression of ECs and to uncover potential therapeutic targets in the treatment of ECs. This information might lead to improved monitoring of ECs and resulting improvement of treatment of ECs, the 4th most common of cancer in women. PMID:24758163

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

PubMed

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.

How Can We Treat Cancer Disease Not Cancer Cells?

PubMed

Kim, Kyu-Won; Lee, Su-Jae; Kim, Woo-Young; Seo, Ji Hae; Lee, Ho-Young

2017-01-01

Since molecular biology studies began, researches in biological science have centered on proteins and genes at molecular level of a single cell. Cancer research has also focused on various functions of proteins and genes that distinguish cancer cells from normal cells. Accordingly, most contemporary anticancer drugs have been developed to target abnormal characteristics of cancer cells. Despite the great advances in the development of anticancer drugs, vast majority of patients with advanced cancer have shown grim prognosis and high rate of relapse. To resolve this problem, we must reevaluate our focuses in current cancer research. Cancer should be considered as a systemic disease because cancer cells undergo a complex interaction with various surrounding cells in cancer tissue and spread to whole body through metastasis under the control of the systemic modulation. Human body relies on the cooperative interaction between various tissues and organs, and each organ performs its specialized function through tissue-specific cell networks. Therefore, investigation of the tumor-specific cell networks can provide novel strategy to overcome the limitation of current cancer research. This review presents the limitations of the current cancer research, emphasizing the necessity of studying tissue-specific cell network which could be a new perspective on treating cancer disease, not cancer cells.

Switching the poles in sexual and reproductive health research: implementing a research capacity-strengthening network in West and North Africa.

PubMed

Dossou, Jean-Paul; Assarag, Bouchra; Delamou, Alexandre; Van der Veken, Karen; Belaid, Loubna; Ouédraogo, Moctar; Khalfallah, Sonia; Aouras, Hayet; Diadhiou, Mohamed; Fassassi, Raïmi; Delvaux, Thérèse

2016-08-08

Health research capacities have been improved in Africa but still remain weak as compared to other regions of the World. To strengthen these research capacities, international collaboration and networking for knowledge and capacity transfer are needed. In this commentary, we present the Network for Scientific Support in the field of Sexual and Reproductive Health in West and North Africa, its priority research topics and discuss its implementation process. Established in January 2014, the Network aims at generating human rights and gender-based research fully carried out and driven by South based institutions. It is composed of 12 institutions including the Institute of Tropical Medicine of Antwerp (Belgium) and 11 institutions from eight Francophone West and North African countries. The key areas of interest of this network are health policies analysis and health system research in family planning, HIV prevention among vulnerable groups, quality of care and breast cancers. Since it started, seventeen research proposals based on locally relevant research questions have been developed. Among the seventeen proposals, eleven have been implemented. Several research institutions enhanced linkages with local representations of international partners such as UNFPA. The network is committed to strengthening methodological research capacities and soft skills such as fundraising, advocacy and leadership. Such competencies are strongly needed for developing an effective South-based leadership in Sexual and Reproductive Health research, and for achieving the Sustainable Development Goals.

[Sex- and gender-sensitive research in epidemiology and medicine: how can this be achieved? Aims and first results of the network "Sex-/Gender-Sensitive Research in Epidemiology, Neurosciences and Genetics/Cancer Research"].

PubMed

Jahn, I; Gansefort, D; Kindler-Röhrborn, A; Pfleiderer, B

2014-09-01

It is considered general knowledge among physicians and epidemiologists that biological and social aspects associated with being male or female have a strong influence on health and disease. Integrating these aspects into research is necessary to counteract the problems--including ethical problems--resulting from a different evidence basis for men and women. From January 2011 to June 2014 the Federal Ministry of Education and Research supported the network "Sex-/Gender-Sensitive Research in Epidemiology, Neuroscience and Genetics/Cancer Research" with three subprojects, which aimed to promote gender-sensitive research practices. The concepts and results are presented in this article. The subproject gathered data (literature analyses, questionnaires) and offered programs for young scientists. Experiences and results were collected and generalized, for instance, in the form of definitions of terms. 50 young scientists have taken part in the training program, identifying associations and barriers in sex-/gender-sensitive research. Among others, a working definition for "sex-/gender-sensitive research" was developed, as well as definitions for the terms "sex-specific" (for biological characteristics that are specific to men or women) and "sex-/gender-dependent" or "sex-/gender-associated" (for biological and social factors, for which the extent of occurrence differs between the sexes). The concepts realized by the network are well suited to stimulate further development and discussions. The definition of terms is an important base for a productive and high-yielding interdisciplinary collaboration.

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

PubMed

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.

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

PubMed Central

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

TP53 mutations, expression and interaction networks in human cancers

PubMed Central

Wang, Xiaosheng; Sun, Qingrong

2017-01-01

Although the associations of p53 dysfunction, p53 interaction networks and oncogenesis have been widely explored, a systematic analysis of TP53 mutations and its related interaction networks in various types of human cancers is lacking. Our study explored the associations of TP53 mutations, gene expression, clinical outcomes, and TP53 interaction networks across 33 cancer types using data from The Cancer Genome Atlas (TCGA). We show that TP53 is the most frequently mutated gene in a number of cancers, and its mutations appear to be early events in cancer initiation. We identified genes potentially repressed by p53, and genes whose expression correlates significantly with TP53 expression. These gene products may be especially important nodes in p53 interaction networks in human cancers. This study shows that while TP53-truncating mutations often result in decreased TP53 expression, other non-truncating TP53 mutations result in increased TP53 expression in some cancers. Survival analyses in a number of cancers show that patients with TP53 mutations are more likely to have worse prognoses than TP53-wildtype patients, and that elevated TP53 expression often leads to poor clinical outcomes. We identified a set of candidate synthetic lethal (SL) genes for TP53, and validated some of these SL interactions using data from the Cancer Cell Line Project. These predicted SL genes are promising candidates for experimental validation and the development of personalized therapeutics for patients with TP53-mutated cancers. PMID:27880943

TP53 mutations, expression and interaction networks in human cancers.

PubMed

Wang, Xiaosheng; Sun, Qingrong

2017-01-03

Although the associations of p53 dysfunction, p53 interaction networks and oncogenesis have been widely explored, a systematic analysis of TP53 mutations and its related interaction networks in various types of human cancers is lacking. Our study explored the associations of TP53 mutations, gene expression, clinical outcomes, and TP53 interaction networks across 33 cancer types using data from The Cancer Genome Atlas (TCGA). We show that TP53 is the most frequently mutated gene in a number of cancers, and its mutations appear to be early events in cancer initiation. We identified genes potentially repressed by p53, and genes whose expression correlates significantly with TP53 expression. These gene products may be especially important nodes in p53 interaction networks in human cancers. This study shows that while TP53-truncating mutations often result in decreased TP53 expression, other non-truncating TP53 mutations result in increased TP53 expression in some cancers. Survival analyses in a number of cancers show that patients with TP53 mutations are more likely to have worse prognoses than TP53-wildtype patients, and that elevated TP53 expression often leads to poor clinical outcomes. We identified a set of candidate synthetic lethal (SL) genes for TP53, and validated some of these SL interactions using data from the Cancer Cell Line Project. These predicted SL genes are promising candidates for experimental validation and the development of personalized therapeutics for patients with TP53-mutated cancers.

Establishing Reliable miRNA-Cancer Association Network Based on Text-Mining Method

PubMed Central

Yang, Zhaowan; Fang, Ming; Zhang, Libin; Zhou, Yanhong

2014-01-01

Associating microRNAs (miRNAs) with cancers is an important step of understanding the mechanisms of cancer pathogenesis and finding novel biomarkers for cancer therapies. In this study, we constructed a miRNA-cancer association network (miCancerna) based on more than 1,000 miRNA-cancer associations detected from millions of abstracts with the text-mining method, including 226 miRNA families and 20 common cancers. We further prioritized cancer-related miRNAs at the network level with the random-walk algorithm, achieving a relatively higher performance than previous miRNA disease networks. Finally, we examined the top 5 candidate miRNAs for each kind of cancer and found that 71% of them are confirmed experimentally. miCancerna would be an alternative resource for the cancer-related miRNA identification. PMID:24895499

Cancer Survivors Day | Center for Cancer Research

Cancer.gov

CCR Celebrates Cancer Survivors #NCSD2016 At the Center for Cancer Research, we are home to an extraordinary group of practicing physicians and scientists who passionately explore the boundaries of research to unlock the mysteries of cancer, a disease that touches nearly every American.

Using Organizational Network Analysis to Plan Cancer Screening Programs for Vulnerable Populations

PubMed Central

Carothers, Bobbi J.; Lofters, Aisha K.

2014-01-01

Objectives. We examined relationships among organizations in a cancer screening network to inform the development of interventions to improve cancer screening for South Asians living in the Peel region of Ontario. Methods. From April to July 2012, we surveyed decision-makers, program managers, and program staff in 22 organizations in the South Asian cancer screening network in the Peel region. We used a network analytic approach to evaluate density (range = 0%–100%, number of ties among organizations in the network expressed as a percentage of all possible ties), centralization (range = 0–1, the extent of variability in centrality), and node characteristics for the communication, collaboration, and referral networks. Results. Density was similar across communication (15%), collaboration (17%), and referral (19%) networks. Centralization was greater in the collaboration network (0.30) than the communication network (0.24), and degree centralization was greater in the inbound (0.42) than the outbound (0.37) referral network. Diverse organizations were central to the networks. Conclusions. Certain organizations were unexpectedly important to the South Asian cancer screening network. Program planning was informed by identifying opportunities to strengthen linkages between key organizations and to leverage existing ties. PMID:24328613

Using organizational network analysis to plan cancer screening programs for vulnerable populations.

PubMed

Lobb, Rebecca; Carothers, Bobbi J; Lofters, Aisha K

2014-02-01

We examined relationships among organizations in a cancer screening network to inform the development of interventions to improve cancer screening for South Asians living in the Peel region of Ontario. From April to July 2012, we surveyed decision-makers, program managers, and program staff in 22 organizations in the South Asian cancer screening network in the Peel region. We used a network analytic approach to evaluate density (range = 0%-100%, number of ties among organizations in the network expressed as a percentage of all possible ties), centralization (range = 0-1, the extent of variability in centrality), and node characteristics for the communication, collaboration, and referral networks. Density was similar across communication (15%), collaboration (17%), and referral (19%) networks. Centralization was greater in the collaboration network (0.30) than the communication network (0.24), and degree centralization was greater in the inbound (0.42) than the outbound (0.37) referral network. Diverse organizations were central to the networks. Certain organizations were unexpectedly important to the South Asian cancer screening network. Program planning was informed by identifying opportunities to strengthen linkages between key organizations and to leverage existing ties.

Major clinical research advances in gynecologic cancer in 2013.

PubMed

Suh, Dong Hoon; Kim, Jae-Weon; Kang, Sokbom; Kim, Hak Jae; Lee, Kyung-Hun

2014-07-01

In 2013, 10 topics were selected for major clinical research advances in gynecologic oncology; these included three topics regarding cervical cancer, three regarding ovarian cancer, two regarding endometrial cancer, and one each regarding breast cancer and radiation oncology. For cervical cancer, bevacizumab was first demonstrated to exhibit outstanding clinical efficacy in a recurrent, metastatic setting. Regarding cervical cancer screening, visual inspections with acetic acid in low-resource settings, p16/Ki-67 double staining, and the follow-up results of four randomized controlled trials of human papillomavirus-based screening methods were reviewed. Laparoscopic para-aortic lymphadenectomy before chemoradiation for locally advanced cervical cancer was the final topic for cervical cancer. Regarding front-line ovarian cancer therapies, dose-dense paclitaxel and carboplatin, intraperitoneal chemotherapy, and other targeted agents administered according to combination or maintenance schedules were discussed. Regarding recurrent ovarian cancer treatment, cediranib, olaparib, and farletuzumab were discussed for platinum-sensitive disease. The final overall survival data associated with a combination of bevacizumab and chemotherapy for platinum-resistant disease were briefly summarized. For endometrial cancer, the potential clinical efficacy of metformin, an antidiabetic drug, in obese patients was followed by integrated genomic analyses from the Cancer Genome Atlas Research Network. For breast cancer, three remarkable advances were reviewed: the long-term effects of continued adjuvant tamoxifen for 10 years, the effects of 2-year versus 1-year adjuvant trastuzumab for human epidermal growth factor receptor 2-positive disease, and the approval of pertuzumab in a neoadjuvant setting with a pathologic complete response as the surrogate endpoint. Finally, the recent large studies of intensity-modulated radiotherapy for gynecologic cancer were briefly summarized.

SEER Cancer Registry Biospecimen Research: Yesterday and Tomorrow

PubMed Central

Altekruse, Sean F.; Rosenfeld, Gabriel E.; Carrick, Danielle M.; Pressman, Emilee J.; Schully, Sheri D.; Mechanic, Leah E.; Cronin, Kathleen A.; Hernandez, Brenda Y.; Lynch, Charles F.; Cozen, Wendy; Khoury, Muin J.; Penberthy, Lynne T.

2014-01-01

The National Cancer Institute's (NCI) Surveillance, Epidemiology, and End Results (SEER) registries have been a source of biospecimens for cancer research for decades. Recently, registry-based biospecimen studies have become more practical, with the expansion of electronic networks for pathology and medical record reporting. Formalin-fixed paraffin-embedded specimens are now used for next-generation sequencing and other molecular techniques. These developments create new opportunities for SEER biospecimen research. We evaluated 31 research articles published during 2005–2013 based on author confirmation that these studies involved linkage of SEER data to biospecimens. Rather than providing an exhaustive review of all possible articles, our intent was to indicate the breadth of research made possible by such a resource. We also summarize responses to a 2012 questionnaire that was broadly distributed to the NCI intra- and extramural biospecimen research community. This included responses from 30 investigators who had used SEER biospecimens in their research. The survey was not intended to be a systematic sample, but instead to provide anecdotal insight on strengths, limitations, and the future of SEER biospecimen research. Identified strengths of this research resource include biospecimen availability, cost, and annotation of data, including demographic information, stage, and survival. Shortcomings include limited annotation of clinical attributes such as detailed chemotherapy history and recurrence, and timeliness of turnaround following biospecimen requests. A review of selected SEER biospecimen articles, investigator feedback, and technological advances reinforced our view that SEER biospecimen resources should be developed. This would advance cancer biology, etiology, and personalized therapy research. PMID:25472677

Non-coding RNA networks in cancer.

PubMed

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.

The effects of individual- and network-level factors on discussion of cancer experiences: Survivors of childhood cancer in Korea.

PubMed

Kim, Min Ah; Yi, Jaehee; Prince, Kort C; Nagelhout, Elizabeth; Wu, Yelena P

2018-01-01

This study aimed to identify young adult Korean cancer survivors' individual- (psychological distress, stigma, sociodemographic variables, and cancer-related variables) and network-level factors (relationship type, social support type) that influence discussion of their cancer experiences. Sixty-eight survivors of childhood cancer who were recruited using snowball sampling nominated 245 individuals from their networks, including family and intimate partners (40%) and friends and acquaintances (60%), as people with whom they most frequently interacted. Results of multilevel modeling analysis indicated that higher levels of internalized shame were a prominent individual-level factor associated with a lack of discussion of cancer experiences. Relationship type and support type at the network-level were also significant correlates of discussion of cancer experiences. Programs for reducing the survivors' shame, improving illness identity, and providing professional training for building social relationships that are intimate and in which they could exchange reciprocal support may help Korean childhood cancer survivors to openly share their cancer experiences with others in their social network and to be successful in the journey of cancer survivorship.

Understanding cancer complexome using networks, spectral graph theory and multilayer framework

NASA Astrophysics Data System (ADS)

Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K.; Chowdhury, Rajdeep; Jalan, Sarika

2017-02-01

Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

Understanding cancer complexome using networks, spectral graph theory and multilayer framework.

PubMed

Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K; Chowdhury, Rajdeep; Jalan, Sarika

2017-02-03

Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

Fred Hutch's Paulovich Laboratory to Lead Protein Assay Work for National Beau Biden Cancer Moonshot | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network, which is a partnership among the National Cancer Institute, Department of Defense, and Department of Veterans Affairs, has tapped the Paulovich Laboratory at Fred Hutchinson Cancer Research Center to create a panel of tests to measure key proteins that can serve as markers for tumors. The effort could ultimately lead to treatments that are more specifically targeted to a patient’s distinct type of cancer.  

Identification of critical regulatory genes in cancer signaling network using controllability analysis

NASA Astrophysics Data System (ADS)

Ravindran, Vandana; Sunitha, V.; Bagler, Ganesh

2017-05-01

Cancer is characterized by a complex web of regulatory mechanisms which makes it difficult to identify features that are central to its control. Molecular integrative models of cancer, generated with the help of data from experimental assays, facilitate use of control theory to probe for ways of controlling the state of such a complex dynamic network. We modeled the human cancer signaling network as a directed graph and analyzed it for its controllability, identification of driver nodes and their characterization. We identified the driver nodes using the maximum matching algorithm and classified them as backbone, peripheral and ordinary based on their role in regulatory interactions and control of the network. We found that the backbone driver nodes were key to driving the regulatory network into cancer phenotype (via mutations) as well as for steering into healthy phenotype (as drug targets). This implies that while backbone genes could lead to cancer by virtue of mutations, they are also therapeutic targets of cancer. Further, based on their impact on the size of the set of driver nodes, genes were characterized as indispensable, dispensable and neutral. Indispensable nodes within backbone of the network emerged as central to regulatory mechanisms of control of cancer. In addition to probing the cancer signaling network from the perspective of control, our findings suggest that indispensable backbone driver nodes could be potentially leveraged as therapeutic targets. This study also illustrates the application of structural controllability for studying the mechanisms underlying the regulation of complex diseases.

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

PubMed

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.

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

PubMed

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.

LTAR linkages with other research networks: Capitalizing on network interconnections

USDA-ARS?s Scientific Manuscript database

The USDA ARS Research Unit based at the Jornada Experimental Range outside of Las Cruces, NM, is a member of the USDA’s Long Term Agro-ecosystem Research (LTAR) Network, the National Science Foundation’s Long Term Ecological Research (LTER) Network, the National Ecological Observation Network (NEON)...

Leveraging health social networking communities in translational research.

PubMed

Webster, Yue W; Dow, Ernst R; Koehler, Jacob; Gudivada, Ranga C; Palakal, Mathew J

2011-08-01

Health social networking communities are emerging resources for translational research. We have designed and implemented a framework called HyGen, which combines Semantic Web technologies, graph algorithms and user profiling to discover and prioritize novel associations across disciplines. This manuscript focuses on the key strategies developed to overcome the challenges in handling patient-generated content in Health social networking communities. Heuristic and quantitative evaluations were carried out in colorectal cancer. The results demonstrate the potential of our approach to bridge silos and to identify hidden links among clinical observations, drugs, genes and diseases. In Amyotrophic Lateral Sclerosis case studies, HyGen has identified 15 of the 20 published disease genes. Additionally, HyGen has highlighted new candidates for future investigations, as well as a scientifically meaningful connection between riluzole and alcohol abuse. Copyright © 2011 Elsevier Inc. All rights reserved.

Noncoding RNA:RNA Regulatory Networks in Cancer

PubMed Central

Chan, Jia Jia; Tay, Yvonne

2018-01-01

Noncoding RNAs (ncRNAs) constitute the majority of the human transcribed genome. This largest class of RNA transcripts plays diverse roles in a multitude of cellular processes, and has been implicated in many pathological conditions, especially cancer. The different subclasses of ncRNAs include microRNAs, a class of short ncRNAs; and a variety of long ncRNAs (lncRNAs), such as lincRNAs, antisense RNAs, pseudogenes, and circular RNAs. Many studies have demonstrated the involvement of these ncRNAs in competitive regulatory interactions, known as competing endogenous RNA (ceRNA) networks, whereby lncRNAs can act as microRNA decoys to modulate gene expression. These interactions are often interconnected, thus aberrant expression of any network component could derail the complex regulatory circuitry, culminating in cancer development and progression. Recent integrative analyses have provided evidence that new computational platforms and experimental approaches can be harnessed together to distinguish key ceRNA interactions in specific cancers, which could facilitate the identification of robust biomarkers and therapeutic targets, and hence, more effective cancer therapies and better patient outcome and survival. PMID:29702599

[Epidemiology of cancer in Italy: from real data to the need for cancer networks.

PubMed

Pinto, Carmine; Mangone, Lucia

2016-10-01

The Italian Association of Medical Oncology (AIOM) and the Italian Association of Cancer Registries (AIRTUM) provide a reliable estimation of the incidence of cancer in Italy. The most outstanding data point to the steadily increasing efficacy of novel therapies, allowing patients to live longer and have a better quality of life, and the number of citizens being diagnosed with cancer - more than three million people, 4.9% of the population. Over the last years, a significant reduction in cancer incidence has been recorded among men with an opposite tendency among women. However, decreased mortality rates are observed in both sexes as a result of primary prevention measures and the promotion of large-scale national screening programs. In this scenario, cancer networks may play a key role. Quality of care could be substantially improved only if regional cancer networks are implemented on the basis of shared pathways, so as to guarantee equity of access in every phase of the disease.

Selective impairment of attention networks in breast cancer patients receiving chemotherapy treatment.

PubMed

Chen, Xingui; Li, Jingjing; Ren, Jing; Hu, Xinglong; Zhu, Chunyan; Tian, Yanghua; Hu, Panpan; Ma, Huijuan; Yu, Fengqiong; Wang, Kai

2014-10-01

Complaints about attention disorders are common among breast cancer survivors who have undergone chemotherapy treatment. However, it is not known whether these complaints indicate a global attention deficit or the selective impairment of attention networks. This study sought to investigate the attentional abilities of breast cancer patients after chemotherapy treatment using the attention network test (ANT). The participants included breast cancer patients who had undergone chemotherapy (CT, N = 58), patients who had not undergone chemotherapy (non-CT, N = 53), and matched healthy controls (HC, N = 55). All participants completed the ANT, which provides measures of three independent attention networks (alerting, orienting, and executive control) and neuropsychological background tests. Our results indicated that the chemotherapy-treated breast cancer patients had significant deficits in the alerting and executive control networks but not in the orienting network. The CT group scored significantly lower in several cognitive tasks, including attention, memory, and information processing tasks, relative to the other two groups. Additionally, significant correlations were found between information processing and the efficiency of the executive control network within the CT group. These results suggest that the three attention networks were selectively impaired following chemotherapy treatment, which affected different brain areas in the breast cancer survivors. Copyright © 2014 John Wiley & Sons, Ltd.

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

PubMed

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.

Secretary | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research programs in basic or applied molecular biology, immunology, retrovirology, cancer biology, or human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick national Laboratory for Cancer Research (FNLCR). The BSP Office provides

Identifying module biomarkers from gastric cancer by differential correlation network

PubMed Central

Liu, Xiaoping; Chang, Xiao

2016-01-01

Gastric cancer (stomach cancer) is a severe disease caused by dysregulation of many functionally correlated genes or pathways instead of the mutation of individual genes. Systematic identification of gastric cancer biomarkers can provide insights into the mechanisms underlying this deadly disease and help in the development of new drugs. In this paper, we present a novel network-based approach to predict module biomarkers of gastric cancer that can effectively distinguish the disease from normal samples. Specifically, by assuming that gastric cancer has mainly resulted from dysfunction of biomolecular networks rather than individual genes in an organism, the genes in the module biomarkers are potentially related to gastric cancer. Finally, we identified a module biomarker with 27 genes, and by comparing the module biomarker with known gastric cancer biomarkers, we found that our module biomarker exhibited a greater ability to diagnose the samples with gastric cancer. PMID:27703371

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

PubMed

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.

Detection and characterization of translational research in cancer and cardiovascular medicine

PubMed Central

2011-01-01

Background Scientists and experts in science policy have become increasingly interested in strengthening translational research. Efforts to understand the nature of translational research and monitor policy interventions face an obstacle: how can translational research be defined in order to facilitate analysis of it? We describe methods of scientometric analysis that can do this. Methods We downloaded bibliographic and citation data from all articles published in 2009 in the 75 leading journals in cancer and in cardiovascular medicine (roughly 15,000 articles for each field). We calculated citation relationships between journals and between articles and we extracted the most prevalent natural language concepts. Results Network analysis and mapping revealed polarization between basic and clinical research, but with translational links between these poles. The structure of the translational research in cancer and cardiac medicine is, however, quite different. In the cancer literature the translational interface is composed of different techniques (e.g., gene expression analysis) that are used across the various subspecialties (e.g., specific tumor types) within cancer research and medicine. In the cardiac literature, the clinical problems are more disparate (i.e., from congenital anomalies to coronary artery disease); although no distinctive translational interface links these fields, translational research does occur in certain subdomains, especially in research on atherosclerosis and hypertension. Conclusions These techniques can be used to monitor the continuing evolution of translational research in medicine and the impact of interventions designed to enhance it. PMID:21569299

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

PubMed

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

Network pharmacology of cancer: From understanding of complex interactomes to the design of multi-target specific therapeutics from nature.

PubMed

Poornima, Paramasivan; Kumar, Jothi Dinesh; Zhao, Qiaoli; Blunder, Martina; Efferth, Thomas

2016-09-01

Despite massive investments in drug research and development, the significant decline in the number of new drugs approved or translated to clinical use raises the question, whether single targeted drug discovery is the right approach. To combat complex systemic diseases that harbour robust biological networks such as cancer, single target intervention is proved to be ineffective. In such cases, network pharmacology approaches are highly useful, because they differ from conventional drug discovery by addressing the ability of drugs to target numerous proteins or networks involved in a disease. Pleiotropic natural products are one of the promising strategies due to their multi-targeting and due to lower side effects. In this review, we discuss the application of network pharmacology for cancer drug discovery. We provide an overview of the current state of knowledge on network pharmacology, focus on different technical approaches and implications for cancer therapy (e.g. polypharmacology and synthetic lethality), and illustrate the therapeutic potential with selected examples green tea polyphenolics, Eleutherococcus senticosus, Rhodiola rosea, and Schisandra chinensis). Finally, we present future perspectives on their plausible applications for diagnosis and therapy of cancer. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling Signaling Networks to Advance New Cancer Therapies.

PubMed

Saez-Rodriguez, Julio; MacNamara, Aidan; Cook, Simon

2015-01-01

Cell signaling pathways control cells' responses to their environment through an intricate network of proteins and small molecules partitioned by intracellular structures, such as the cytoskeleton and nucleus. Our understanding of these pathways has been revised recently with the advent of more advanced experimental techniques; no longer are signaling pathways viewed as linear cascades of information flowing from membrane-bound receptors to the nucleus. Instead, such pathways must be understood in the context of networks, and studying such networks requires an integration of computational and experimental approaches. This understanding is becoming more important in designing novel therapies for diseases such as cancer. Using the MAPK (mitogen-activated protein kinase) and PI3K (class I phosphoinositide-3' kinase) pathways as case studies of cellular signaling, we give an overview of these pathways and their functions. We then describe, using a number of case studies, how computational modeling has aided in understanding these pathways' deregulation in cancer, and how such understanding can be used to optimally tailor current therapies or help design new therapies against cancer.

Analysis of metastasis associated signal regulatory network in colorectal cancer.

PubMed

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.

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

PubMed

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.

Research, practice, and policy partnerships in pan-Canadian coalitions for cancer and chronic disease prevention.

PubMed

Manafò, Elizabeth; Petermann, Lisa; Lobb, Rebecca; Keen, Deb; Kerner, Jon

2011-01-01

To describe the development stages of the Coalitions Linking Action and Science for Prevention (CLASP) initiative of the Canadian Partnership Against Cancer to support research, practice, and policy coalitions focused on cancer and chronic disease prevention in Canada. Coalitions Linking Action and Science for Prevention was implemented in 3 stages. This article describes Stage 1 that consisted of an online concept-mapping consultation process, 3 topic specific networking and consultation workshops, and 3 context-specific networking, coalition development, and planning meetings. These were all completed using a participatory engagement approach to encourage knowledge exchange across jurisdictions and sectors in Canada. Toronto, Ontario; Calgary, Alberta; Montreal, Québec; and Ottawa, Ontario. More than 500 researchers, practitioners, and policy specialists were invited to take part in the first stage activities. (1) Participant-identified high-priority opportunities for strategic collaboration; (2) Cross-jurisdictional and cross-sector representation; and (3) Participant feedback on the CLASP processes and activities. Participants from Stage 1 activities were distributed across all provinces/territories; 3 jurisdictional levels; and research, practice, and policy sectors. Ninety priority opportunities for strategic collaboration were identified across all 3 workshops. Participants provided detailed feedback about transparency of the RFP (Request for Proposals) application process, support needed to level the playing field for potential applicants, and valuable suggestions for the adjudication process. Coalitions Linking Action and Science for Prevention engaged hundreds of research, practice, and policy experts across Canada focusing social-behavioral, clinical, and environmental and occupational opportunities for cancer and chronic disease prevention. Given the extent of expert and jurisdictional engagement, the substantial Partnership investment in a

The Prevention Research Centers Healthy Aging Research Network.

PubMed

Lang, Jason E; Anderson, Lynda; LoGerfo, James; Sharkey, Joseph; Belansky, Elaine; Bryant, Lucinda; Prohaska, Tom; Altpeter, Mary; Marshall, Victor; Satariano, William; Ivey, Susan; Bayles, Constance; Pluto, Delores; Wilcox, Sara; Goins, R Turner; Byrd, Robert C

2006-01-01

The Prevention Research Centers Healthy Aging Research Network (PRC-HAN), funded by the Centers for Disease Control and Prevention's (CDC's) Healthy Aging program, was created in 2001 to help develop partnerships and create a research agenda that promotes healthy aging. The nine universities that participate in the network use their expertise in aging research to collaborate with their communities and other partners to develop and implement health promotion interventions for older adults at the individual, organizational, environmental, and policy levels. The population of older adults in the United States is growing rapidly; approximately 20% of Americans will be aged 65 years or older by 2030. The health and economic impact of an aging society compel the CDC and the public health community to place increased emphasis on preventing unnecessary disease, disability, and injury among older Americans. The PRC-HAN has a broad research agenda that addresses health-promoting skills and behaviors, disease and syndrome topics, and knowledge domains. The network chose physical activity for older adults as its initial focus for research and has initiated two networkwide projects: a comprehensive, multisite survey that collected information on the capacity, content, and accessibility of physical activity programs for older adults and a peer-reviewed publication that describes the role of public health in promoting physical activity among older adults. In addition to participating in the core research area, each network member works independently with its community committee on PRC-HAN activities. As a result, the network is 1) expanding prevention research for older adults and their communities; 2) promoting the translation and dissemination of findings to key stakeholders; 3) strengthening PRC-HAN capacity through partnerships and expanded funding; and 4) stimulating the adoption of policies and programs by engaging policymakers, planners, and practitioners. In 2003, the PRC

Cancer research priorities and gaps in Iran: the influence of cancer burden on cancer research outputs between 1997 and 2014.

PubMed

Majidi, A; Salimzadeh, H; Beiki, O; Delavari, F; Majidi, S; Delavari, A; Malekzadeh, R

2017-03-01

As a developing country, Iran is experiencing the increasing burden of cancers, which are currently the third leading cause of mortality in Iran. This study aims to demonstrate that cancer research in Iran concentrates on the cancer research priorities based on the global burden of disease (GBD) reports. Descriptive evaluation of all cancers disability-adjusted life years (DALYs) was performed using GBD data. Also a comprehensive search was conducted using cancer-associated keywords to obtain all cancer-related publications from Iran, indexed in Web of Science. Multiple regression analysis and correlation coefficients (R 2 ) were used to evaluate the possible associations between cancer research publications and GBD. During 1996-2014, the majority of cancer-related publications in Iran focused on breast cancer, leukaemia and stomach cancer, respectively. This study found hypothetical correlations between cancer publications in Iran in line with the burden of cancer as reported by GBD. Particularly, correlations between years lived with disability (YLD) and cancer-related publications were more obvious. This study introduces a new outline in setting cancer research priorities in the region. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Artificial intelligence techniques for colorectal cancer drug metabolism: ontology and complex network.

PubMed

Martínez-Romero, Marcos; Vázquez-Naya, José M; Rabuñal, Juan R; Pita-Fernández, Salvador; Macenlle, Ramiro; Castro-Alvariño, Javier; López-Roses, Leopoldo; Ulla, José L; Martínez-Calvo, Antonio V; Vázquez, Santiago; Pereira, Javier; Porto-Pazos, Ana B; Dorado, Julián; Pazos, Alejandro; Munteanu, Cristian R

2010-05-01

Colorectal cancer is one of the most frequent types of cancer in the world and generates important social impact. The understanding of the specific metabolism of this disease and the transformations of the specific drugs will allow finding effective prevention, diagnosis and treatment of the colorectal cancer. All the terms that describe the drug metabolism contribute to the construction of ontology in order to help scientists to link the correlated information and to find the most useful data about this topic. The molecular components involved in this metabolism are included in complex network such as metabolic pathways in order to describe all the molecular interactions in the colorectal cancer. The graphical method of processing biological information such as graphs and complex networks leads to the numerical characterization of the colorectal cancer drug metabolic network by using invariant values named topological indices. Thus, this method can help scientists to study the most important elements in the metabolic pathways and the dynamics of the networks during mutations, denaturation or evolution for any type of disease. This review presents the last studies regarding ontology and complex networks of the colorectal cancer drug metabolism and a basic topology characterization of the drug metabolic process sub-ontology from the Gene Ontology.

Research Programs & Initiatives

Cancer.gov

CGH develops international initiatives and collaborates with other NCI divisions, NCI-designated Cancer Centers, and other countries to support cancer control planning, encourage capacity building, and support cancer research and research networks.

Research of ad hoc network based on SINCGARS network

NASA Astrophysics Data System (ADS)

Nie, Hao; Cai, Xiaoxia; Chen, Hong; Chen, Jian; Weng, Pengfei

2016-03-01

In today's world, science and technology make a spurt of progress, so society has entered the era of information technology, network. Only the comprehensive use of electronic warfare and network warfare means can we maximize their access to information and maintain the information superiority. Combined with the specific combat mission and operational requirements, the research design and construction in accordance with the actual military which are Suitable for the future of information technology needs of the tactical Adhoc network, tactical internet, will greatly improve the operational efficiency of the command of the army. Through the study of the network of the U.S. military SINCGARS network, it can explore the routing protocol and mobile model, to provide a reference for the research of our army network.

Role of practice-based research networks in comparative effectiveness research.

PubMed

Hartung, Daniel M; Guise, Jeanne-Marie; Fagnan, Lyle J; Davis, Melinda M; Stange, Kurt C

2012-01-01

Comparative effectiveness research fundamentally reorients how clinical evidence is generated and used with the goal of providing actionable information to decision-makers. To achieve this, it is vital that decision-makers and the research enterprise are engaged from research inception, to evidence generation and translation. Practice-based research networks are affiliated clinicians in diverse communities with the goal of conducting research to improve care. Practice-based research networks have the potential to advance all phases of the comparative effectiveness research cycle. The aim of this paper is to explore current and potential roles of practice-based research networks in conducting comparative effectiveness research.

‘Imi Hale – The Native Hawaiian Cancer Awareness, Research, and Training Network: Second-Year Status Report

PubMed Central

Braun, Kathryn L.; Tsark, JoAnn; Ann Santos, Lorrie; Abrigo, Lehua

2010-01-01

Purpose The purpose of this paper is to describe ‘Imi Hale, a program developed and managed by Native Hawaiians to increase cancer awareness and research capacity among Native Hawaiians. This US subgroup of indigenous people of the Hawaiian islands has disproportionately high rates of cancer mortality and low rates of participation in health and research careers. Methods As a community-based research project, ‘Imi Hale spent its first year gathering data from Native Hawaiians about their cancer awareness and research priorities. These findings guide ‘Imi Hale’s community and scientific advisors, a community-based Institutional Review Board, Na Liko Noelo (budding researchers), and staff in developing and carrying out projects that address these priority areas. Emphasis is placed on transferring skills and resources to Native Hawaiians through training, technical assistance, and mentorship. A biennial survey assesses the extent to which community-based participatory research principles are being followed. Principal Findings By the end of the second year, statewide and island-specific awareness plans were produced, and 9 funded awareness projects are supporting the development and dissemination of Hawaiian health education materials. Research accomplishments include the enrollment of 42 Native Hawaiian Na Liko Noelo (budding researchers), 22 of which are involved in 14 funded research projects. The biennial evaluation survey found that 92% of our advisors felt that ‘Imi Hale was promoting scientifically rigorous research that was culturally appropriate and respectful of Native Hawaiian beliefs, and 96% felt that ‘Imi Hale was following its own principles of community-based participatory research. Conclusion ‘Imi Hale’s community-based approach to promoting cancer awareness will result in a sustainable infrastructure for reducing the cancer burden on Native Hawaiians. PMID:15352771

Building partnership in oral cancer research in a developing country: processes and barriers.

PubMed

Zain, Rosnah Binti; Ghani, Wan Maria Nabillah; Razak, Ishak Abdul; Latifah, Raja Jallaludin Raja; Samsuddin, Abdul Rani; Cheong, Sok Ching; Abdullah, Norlida; Ismail, Abdul Rashid; Hussaini, Haizal Bin; Talib, Norain Abu; Jallaludin, Amin

2009-01-01

The rising burden of cancer in the developing world calls for a re-evaluation of the treatment strategies employed to improve patient management, early detection and understanding of the disease. There is thus an increasing demand for interdisciplinary research that integrates two or more disciplines of what may seemed to be highly unrelated and yet very much needed as strategies for success in research. This paper presents the processes and barriers faced in building partnerships in oral cancer research in a developing country. A case study was undertaken in a developing country (Malaysia) to assess the strengths and weaknesses of the situation leading to the formation of a multidisciplinary research partnership in oral cancer. Following the formalization of the partnership, further evaluation was undertaken to identify measures that can assist in sustaining the partnership. The group identifies its strength as the existence of academia, research-intensive NGOs and good networking of clinicians via the existence of the government's network of healthcare provider system who are the policy makers. The major weaknesses identified are the competing interest between academia and NGOs to justify their existence due to the lack of funding sources and well trained human resources. With the growing partnership, the collaborative group recognizes the need to develop standard operating procedures (SOPs) and guidelines for the sharing and usage of resources in order to safeguard the interest of the original partners while also attending to the needs of the new partners.

Research in network management techniques for tactical data communications networks

NASA Astrophysics Data System (ADS)

Boorstyn, R.; Kershenbaum, A.; Maglaris, B.; Sarachik, P.

1982-09-01

This is the final technical report for work performed on network management techniques for tactical data networks. It includes all technical papers that have been published during the control period. Research areas include Packet Network modelling, adaptive network routing, network design algorithms, network design techniques, and local area networks.

Networking of differentially expressed genes in human cancer cells resistant to methotrexate

PubMed Central

2009-01-01

Background The need for an integrated view of data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed biological association networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). Methods Seven cell lines representative of different types of cancer, including colon cancer (HT29 and Caco2), breast cancer (MCF-7 and MDA-MB-468), pancreatic cancer (MIA PaCa-2), erythroblastic leukemia (K562) and osteosarcoma (Saos-2), were used. The differential expression pattern between sensitive and MTX-resistant cells was determined by whole human genome microarrays and analyzed with the GeneSpring GX software package. Genes deregulated in common between the different cancer cell lines served to generate biological association networks using the Pathway Architect software. Results Dikkopf homolog-1 (DKK1) is a highly interconnected node in the network generated with genes in common between the two colon cancer cell lines, and functional validations of this target using small interfering RNAs (siRNAs) showed a chemosensitization toward MTX. Members of the UDP-glucuronosyltransferase 1A (UGT1A) family formed a network of genes differentially expressed in the two breast cancer cell lines. siRNA treatment against UGT1A also showed an increase in MTX sensitivity. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) was overexpressed among the pancreatic cancer, leukemia and osteosarcoma cell lines, and siRNA treatment against EEF1A1 produced a chemosensitization toward MTX. Conclusions Biological association networks identified DKK1, UGT1As and EEF1A1 as important gene nodes in MTX-resistance. Treatments using siRNA technology against these three genes showed chemosensitization toward MTX. PMID:19732436

Use and taxonomy of social media in cancer-related research: a systematic review.

PubMed

Koskan, Alexis; Klasko, Lynne; Davis, Stacy N; Gwede, Clement K; Wells, Kristen J; Kumar, Ambuj; Lopez, Natalia; Meade, Cathy D

2014-07-01

Little is known about how social media are used in cancer care. We conducted a systematic review of the use and taxonomy of social media in cancer-related studies, in PubMed, Web of Knowledge, CINAHL, and Google Scholar. We located 1350 articles published through October 2013; 69 met study inclusion criteria. Early research (1996-2007) was predominantly descriptive studies of online forums. Later, researchers began analyzing blogs, videos shared on YouTube, and social networking sites. Most studies (n = 62) were descriptive, and only 7 reported intervention studies published since 2010. Future research should include more intervention studies to determine how social media can influence behavior, and more empirical research is needed on how social media may be used to reduce health disparities.

Differential Connectivity in Colorectal Cancer Gene Expression Network

PubMed

Izadi, Fereshteh

2018-05-30

Colorectal cancer (CRC) is one of the challenging types of cancers; thus, exploring effective biomarkers related to colorectal could lead to significant progresses toward the treatment of this disease. In the present study, CRC gene expression datasets have been reanalyzed. Mutual differentially expressed genes across 294 normal mucosa and adjacent tumoral samples were then utilized in order to build two independent transcriptional regulatory networks. By analyzing the networks topologically, genes with differential global connectivity related to cancer state were determined for which the potential transcriptional regulators including transcription factors were identified. The majority of differentially connected genes (DCGs) were up-regulated in colorectal transcriptome experiments. Moreover, a number of these genes have been experimentally validated as cancer or CRC-associated genes. The DCGs, including GART, TGFB1, ITGA2, SLC16A5, SOX9, and MMP7, were investigated across 12 cancer types. Functional enrichment analysis followed by detailed data mining exhibited that these candidate genes could be related to CRC by mediating in metastatic cascade in addition to shared pathways with 12 cancer types by triggering the inflammatory events Our study uncovered correlated alterations in gene expression related to CRC susceptibility and progression that the potent candidate biomarkers could provide a link to disease.

Role of practice-based research networks in comparative effectiveness research

PubMed Central

Hartung, Daniel M; Guise, Jeanne-Marie; Fagnan, Lyle J; Davis, Melinda M; Stange, Kurt C

2012-01-01

Comparative effectiveness research fundamentally reorients how clinical evidence is generated and used with the goal of providing actionable information to decision-makers. To achieve this, it is vital that decision-makers and the research enterprise are engaged from research inception, to evidence generation and translation. Practice-based research networks are affiliated clinicians in diverse communities with the goal of conducting research to improve care. Practice-based research networks have the potential to advance all phases of the comparative effectiveness research cycle. The aim of this paper is to explore current and potential roles of practice-based research networks in conducting comparative effectiveness research. PMID:23105964

Why I Do Cancer Research

Cancer.gov

World Cancer Research Day is recognized on September 24, 2017. This day presents an opportunity for all of us to remind the world of the critically important roles research and cancer researchers play in reducing the global burden of cancer. Together with ten other global partners, NCI participated in the planning and launch of this initiative, highlighting the amplified impact of international cooperation in the clinical research arena.

Detection of gene communities in multi-networks reveals cancer drivers

NASA Astrophysics Data System (ADS)

Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

2015-12-01

We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.

[The Coordinating Centers for Clinical Trials (KKS) and the KKS Network: competence for clinical research].

PubMed

Ohmann, Christian; Bruns, Insa; Wolff, Stephanie

2010-01-01

The Network of the Coordination Centers for Clinical Trials (CTCs; Koordinierungszentren für Klinische Studien(KKS)) comprises 17 institutions working as scientific service provider for universities, study groups, the pharmaceutical and medical devices industry as well as additional clients associated with clinical research. The CTCs have established planning and conduct of clinical trials according to Good Clinical Practice (GCP) guidelines,with a wide range of study support in academia. One focus according to indications is cancer. Expertise in hematological/oncological research can be requested nationwide and cross-institutional. The KKS network currently cooperates with medical societies and other, even European networks in 20 countries and has been established as a strong platform for oncological trials. Copyright © 2010 S. Karger AG, Basel.

MUFFINN: cancer gene discovery via network analysis of somatic mutation data.

PubMed

Cho, Ara; Shim, Jung Eun; Kim, Eiru; Supek, Fran; Lehner, Ben; Lee, Insuk

2016-06-23

A major challenge for distinguishing cancer-causing driver mutations from inconsequential passenger mutations is the long-tail of infrequently mutated genes in cancer genomes. Here, we present and evaluate a method for prioritizing cancer genes accounting not only for mutations in individual genes but also in their neighbors in functional networks, MUFFINN (MUtations For Functional Impact on Network Neighbors). This pathway-centric method shows high sensitivity compared with gene-centric analyses of mutation data. Notably, only a marginal decrease in performance is observed when using 10 % of TCGA patient samples, suggesting the method may potentiate cancer genome projects with small patient populations.

A human functional protein interaction network and its application to cancer data analysis

PubMed Central

2010-01-01

Background One challenge facing biologists is to tease out useful information from massive data sets for further analysis. A pathway-based analysis may shed light by projecting candidate genes onto protein functional relationship networks. We are building such a pathway-based analysis system. Results We have constructed a protein functional interaction network by extending curated pathways with non-curated sources of information, including protein-protein interactions, gene coexpression, protein domain interaction, Gene Ontology (GO) annotations and text-mined protein interactions, which cover close to 50% of the human proteome. By applying this network to two glioblastoma multiforme (GBM) data sets and projecting cancer candidate genes onto the network, we found that the majority of GBM candidate genes form a cluster and are closer than expected by chance, and the majority of GBM samples have sequence-altered genes in two network modules, one mainly comprising genes whose products are localized in the cytoplasm and plasma membrane, and another comprising gene products in the nucleus. Both modules are highly enriched in known oncogenes, tumor suppressors and genes involved in signal transduction. Similar network patterns were also found in breast, colorectal and pancreatic cancers. Conclusions We have built a highly reliable functional interaction network upon expert-curated pathways and applied this network to the analysis of two genome-wide GBM and several other cancer data sets. The network patterns revealed from our results suggest common mechanisms in the cancer biology. Our system should provide a foundation for a network or pathway-based analysis platform for cancer and other diseases. PMID:20482850

Working to Eliminate Cancer Health Disparities from Tobacco: A Review of the National Cancer Institute's Community Networks Program.

PubMed

Tong, Elisa K; Fagan, Pebbles; Cooper, Leslie; Canto, Maria; Carroll, William; Foster-Bey, John; Hébert, James R; Lopez-Class, Maria; Ma, Grace X; Nez Henderson, Patricia; Pérez-Stable, Eliseo J; Santos, LorrieAnn; Smith, Justin H; Tan, Yin; Tsoh, Janice; Chu, Kenneth

2015-08-01

In 2005, the National Cancer Institute funded the Community Networks Program (CNP), which aimed to reduce cancer health disparities in minority racial/ethnic and underserved groups through community-based participatory research, education, and training. The purpose of this study was to describe the CNP model and their tobacco-related work in community-based research, education, and training using a tobacco disparities research framework. We conducted a comprehensive review of the CNP tobacco-related activities including publications, published abstracts, research activities, trainee pilot studies, policy-related activities, educational outreach, and reports produced from 2005-2009. Two authors categorized the tobacco-related activities and publications within the framework. Although there was no mandate to address tobacco, the CNPs produced 103 tobacco-related peer-reviewed publications, which reflects the largest proportion (12%) of all CNP cancer-related publications. Selected publications and research activities were most numerous under the framework areas "Psychosocial Research," "Surveillance," "Epidemiology," and "Treatment of Nicotine Addiction." Thirteen CNPs participated in tobacco control policymaking in mainstream efforts that affected their local community and populations, and 24 CNPs conducted 1147 tobacco-related educational outreach activities. CNP activities that aimed to build research and infrastructure capacity included nine tobacco-related pilot projects representing 16% of all CNP cancer-related pilot projects, and 17 publications acknowledging leveraged partnerships with other organizations, a strategy encouraged by the CNP. The CNP is a promising academic-community model for working to eliminate tobacco-related health disparities. Future efforts may address scientific gaps, consider collaboration across groups, assess the extent of operationalizing community-based participatory research, and improve common tracking measures. © The Author

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

PubMed

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

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

PubMed Central

2012-01-01

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 encourage nurses and other health

Researchers studying alternative to bladder removal for bladder cancer patients | Center for Cancer Research

Cancer.gov

A new phase I clinical trial conducted by researchers at the Center for Cancer Research (CCR) is evaluating the safety and tolerability, or the degree to which any side effects can be tolerated by patients, of a two-drug combination as a potential alternative to bladder removal for bladder cancer patients. The trial targets patients with non-muscle invasive bladder cancer (NMIBC) whose cancers have stopped responding to traditional therapies. Read more...

Cancer systems biology: signal processing for cancer research

PubMed Central

Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei

2011-01-01

In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts. PMID:21439242

Research Priorities in Networking and Communications.

ERIC Educational Resources Information Center

National Science Foundation, Washington, DC.

A workshop focused on major research issues in networking and communications. This report defines the context for research priorities and initiatives and deals with issues in networking and communications. Fifteen major research priorities and four research specific initiatives were identified by participants as areas that should be pursued over…

Transcriptional master regulator analysis in breast cancer genetic networks.

PubMed

Tovar, Hugo; García-Herrera, Rodrigo; Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique

2015-12-01

Gene regulatory networks account for the delicate mechanisms that control gene expression. Under certain circumstances, gene regulatory programs may give rise to amplification cascades. Such transcriptional cascades are events in which activation of key-responsive transcription factors called master regulators trigger a series of gene expression events. The action of transcriptional master regulators is then important for the establishment of certain programs like cell development and differentiation. However, such cascades have also been related with the onset and maintenance of cancer phenotypes. Here we present a systematic implementation of a series of algorithms aimed at the inference of a gene regulatory network and analysis of transcriptional master regulators in the context of primary breast cancer cells. Such studies were performed in a highly curated database of 880 microarray gene expression experiments on biopsy-captured tissue corresponding to primary breast cancer and healthy controls. Biological function and biochemical pathway enrichment analyses were also performed to study the role that the processes controlled - at the transcriptional level - by such master regulators may have in relation to primary breast cancer. We found that transcription factors such as AGTR2, ZNF132, TFDP3 and others are master regulators in this gene regulatory network. Sets of genes controlled by these regulators are involved in processes that are well-known hallmarks of cancer. This kind of analyses may help to understand the most upstream events in the development of phenotypes, in particular, those regarding cancer biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Working to Eliminate Cancer Health Disparities from Tobacco: A Review of the National Cancer Institute’s Community Networks Program

PubMed Central

Fagan, Pebbles; Cooper, Leslie; Canto, Maria; Carroll, William; Foster-Bey, John; Hébert, James R.; Lopez-Class, Maria; Ma, Grace X.; Nez Henderson, Patricia; Pérez-Stable, Eliseo J.; Santos, LorrieAnn; Smith, Justin H.; Tan, Yin; Tsoh, Janice; Chu, Kenneth

2015-01-01

Introduction: In 2005, the National Cancer Institute funded the Community Networks Program (CNP), which aimed to reduce cancer health disparities in minority racial/ethnic and underserved groups through community-based participatory research, education, and training. The purpose of this study was to describe the CNP model and their tobacco-related work in community-based research, education, and training using a tobacco disparities research framework. Methods: We conducted a comprehensive review of the CNP tobacco-related activities including publications, published abstracts, research activities, trainee pilot studies, policy-related activities, educational outreach, and reports produced from 2005–2009. Two authors categorized the tobacco-related activities and publications within the framework. Results: Although there was no mandate to address tobacco, the CNPs produced 103 tobacco-related peer-reviewed publications, which reflects the largest proportion (12%) of all CNP cancer-related publications. Selected publications and research activities were most numerous under the framework areas “Psychosocial Research,” “Surveillance,” “Epidemiology,” and “Treatment of Nicotine Addiction.” Thirteen CNPs participated in tobacco control policymaking in mainstream efforts that affected their local community and populations, and 24 CNPs conducted 1147 tobacco-related educational outreach activities. CNP activities that aimed to build research and infrastructure capacity included nine tobacco-related pilot projects representing 16% of all CNP cancer-related pilot projects, and 17 publications acknowledging leveraged partnerships with other organizations, a strategy encouraged by the CNP. Conclusions: The CNP is a promising academic-community model for working to eliminate tobacco-related health disparities. Future efforts may address scientific gaps, consider collaboration across groups, assess the extent of operationalizing community-based participatory

Use and Taxonomy of Social Media in Cancer-Related Research: A Systematic Review

PubMed Central

Klasko, Lynne; Davis, Stacy N.; Gwede, Clement K.; Wells, Kristen J.; Kumar, Ambuj; Lopez, Natalia; Meade, Cathy D.

2014-01-01

Little is known about how social media are used in cancer care. We conducted a systematic review of the use and taxonomy of social media in cancer-related studies, in PubMed, Web of Knowledge, CINAHL, and Google Scholar. We located 1350 articles published through October 2013; 69 met study inclusion criteria. Early research (1996–2007) was predominantly descriptive studies of online forums. Later, researchers began analyzing blogs, videos shared on YouTube, and social networking sites. Most studies (n = 62) were descriptive, and only 7 reported intervention studies published since 2010. Future research should include more intervention studies to determine how social media can influence behavior, and more empirical research is needed on how social media may be used to reduce health disparities. PMID:24832403

Establishment of apoptotic regulatory network for genetic markers of colorectal cancer.

PubMed

Hao, Yibin; Shan, Guoyong; Nan, Kejun

2017-03-01

Our purpose is to screen out genetic markers applicable to early diagnosis for colorectal cancer and to establish apoptotic regulatory network model for colorectal cancer, thereby providing theoretical evidence and targeted therapy for early diagnosis of colorectal cancer. Taking databases including CNKI, VIP, Wanfang data, Pub Med, and MEDLINE as main sources of literature retrieval, literatures associated with genetic markers applied to early diagnosis of colorectal cancer were searched to perform comprehensive and quantitative analysis by Meta analysis, hence screening genetic markers used in early diagnosis of colorectal cancer. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were employed to establish apoptotic regulatory network model based on screened genetic markers, and then verification experiment was conducted. Through Meta analysis, seven genetic markers were screened out, including WWOX, K-ras, COX-2, p53, APC, DCC and PTEN, among which DCC shows highest diagnostic efficiency. GO analysis of genetic markers found that six genetic markers played role in biological process, molecular function and cellular component. It was indicated in apoptotic regulatory network built by KEGG analysis and verification experiment that WWOX could promote tumor cell apoptotic in colorectal cancer and elevate expression level of p53. The apoptotic regulatory model of colorectal cancer established in this study provides clinically theoretical evidence and targeted therapy for early diagnosis of colorectal cancer.

Towards a privacy preserving cohort discovery framework for clinical research networks.

PubMed

Yuan, Jiawei; Malin, Bradley; Modave, François; Guo, Yi; Hogan, William R; Shenkman, Elizabeth; Bian, Jiang

2017-02-01

The last few years have witnessed an increasing number of clinical research networks (CRNs) focused on building large collections of data from electronic health records (EHRs), claims, and patient-reported outcomes (PROs). Many of these CRNs provide a service for the discovery of research cohorts with various health conditions, which is especially useful for rare diseases. Supporting patient privacy can enhance the scalability and efficiency of such processes; however, current practice mainly relies on policy, such as guidelines defined in the Health Insurance Portability and Accountability Act (HIPAA), which are insufficient for CRNs (e.g., HIPAA does not require encryption of data - which can mitigate insider threats). By combining policy with privacy enhancing technologies we can enhance the trustworthiness of CRNs. The goal of this research is to determine if searchable encryption can instill privacy in CRNs without sacrificing their usability. We developed a technique, implemented in working software to enable privacy-preserving cohort discovery (PPCD) services in large distributed CRNs based on elliptic curve cryptography (ECC). This technique also incorporates a block indexing strategy to improve the performance (in terms of computational running time) of PPCD. We evaluated the PPCD service with three real cohort definitions: (1) elderly cervical cancer patients who underwent radical hysterectomy, (2) oropharyngeal and tongue cancer patients who underwent robotic transoral surgery, and (3) female breast cancer patients who underwent mastectomy) with varied query complexity. These definitions were tested in an encrypted database of 7.1 million records derived from the publically available Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS). We assessed the performance of the PPCD service in terms of (1) accuracy in cohort discovery, (2) computational running time, and (3) privacy afforded to the underlying records during PPCD. The

Researchers studying alternative to bladder removal for bladder cancer patients | Center for Cancer Research

Cancer.gov

A new phase I clinical trial conducted by researchers at the Center for Cancer Research (CCR) is evaluating the safety and tolerability, or the degree to which any side effects can be tolerated by patients, of a two-drug combination as a potential alternative to bladder removal for bladder cancer patients. The trial targets patients with non-muscle invasive bladder cancer

Integration of Network Biology and Imaging to Study Cancer Phenotypes and Responses.

PubMed

Tian, Ye; Wang, Sean S; Zhang, Zhen; Rodriguez, Olga C; Petricoin, Emanuel; Shih, Ie-Ming; Chan, Daniel; Avantaggiati, Maria; Yu, Guoqiang; Ye, Shaozhen; Clarke, Robert; Wang, Chao; Zhang, Bai; Wang, Yue; Albanese, Chris

2014-01-01

Ever growing "omics" data and continuously accumulated biological knowledge provide an unprecedented opportunity to identify molecular biomarkers and their interactions that are responsible for cancer phenotypes that can be accurately defined by clinical measurements such as in vivo imaging. Since signaling or regulatory networks are dynamic and context-specific, systematic efforts to characterize such structural alterations must effectively distinguish significant network rewiring from random background fluctuations. Here we introduced a novel integration of network biology and imaging to study cancer phenotypes and responses to treatments at the molecular systems level. Specifically, Differential Dependence Network (DDN) analysis was used to detect statistically significant topological rewiring in molecular networks between two phenotypic conditions, and in vivo Magnetic Resonance Imaging (MRI) was used to more accurately define phenotypic sample groups for such differential analysis. We applied DDN to analyze two distinct phenotypic groups of breast cancer and study how genomic instability affects the molecular network topologies in high-grade ovarian cancer. Further, FDA-approved arsenic trioxide (ATO) and the ND2-SmoA1 mouse model of Medulloblastoma (MB) were used to extend our analyses of combined MRI and Reverse Phase Protein Microarray (RPMA) data to assess tumor responses to ATO and to uncover the complexity of therapeutic molecular biology.

Pigment network-based skin cancer detection.

PubMed

Alfed, Naser; Khelifi, Fouad; Bouridane, Ahmed; Seker, Huseyin

2015-08-01

Diagnosing skin cancer in its early stages is a challenging task for dermatologists given the fact that the chance for a patient's survival is higher and hence the process of analyzing skin images and making decisions should be time efficient. Therefore, diagnosing the disease using automated and computerized systems has nowadays become essential. This paper proposes an efficient system for skin cancer detection on dermoscopic images. It has been shown that the statistical characteristics of the pigment network, extracted from the dermoscopic image, could be used as efficient discriminating features for cancer detection. The proposed system has been assessed on a dataset of 200 dermoscopic images of the `Hospital Pedro Hispano' [1] and the results of cross-validation have shown high detection accuracy.

Eurocan plus report: feasibility study for coordination of national cancer research activities.

PubMed

2008-01-01

, becoming the common voice of the cancer research community and serving as an interface between the cancer research community and European citizens, patients' organizations, European institutions, Member States, industry and small and medium enterprises (SMEs), putting into practice solutions aimed at alleviating barriers to collaboration and coordination of cancer research activities in the European Union, and dealing with legal and regulatory issues. The development of an effective ECI will require time, but this entity should be established immediately. As an initial step, coordination efforts should be directed towards the creation of a platform on translational research that could encompass (1) coordination between basic, clinical and epidemiological research; (2) formal agreements of co-operation between comprehensive cancer centres and basic research laboratories throughout Europe and (3) networking between funding bodies at the European level.The European Parliament and its instruments have had a major influence in cancer control in Europe, notably in tobacco control and in the implementation of effective population-based screening. To make further progress there is a need for novelty and innovation in cancer research and prevention in Europe, and having a platform such as the ECI, where those involved in all aspects of cancer research can meet, discuss and interact, is a decisive development for Europe.

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

PubMed

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

About the Cancer Biomarkers Research Group | Division of Cancer Prevention

Cancer.gov

The Cancer Biomarkers Research Group promotes research to identify, develop, and validate biological markers for early cancer detection and cancer risk assessment. Activities include development and validation of promising cancer biomarkers, collaborative databases and informatics systems, and new technologies or the refinement of existing technologies. NCI DCP News Note

What's New in Bone Cancer Research and Treatment?

MedlinePlus

... Cancer Research? Bone Cancer About Bone Cancer What’s New in Bone Cancer Research? Research on bone cancer ... treat these cancers. Chemotherapy Some studies are testing new chemo drugs. Researchers are also looking for new, ...

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed Central

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-01-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. PMID:21666777

Fostering Cooperation in Cancer Research

Cancer.gov

Thursday, June 25, 2015 Memorandum of Understanding (MoU) was signed between US National Cancer Institute and three agencies of the Indian government - the Department of Biotechnology, the Indian Council of Medical Research, and the Indian National Cancer Institute, a part of the All India Institute of Medical Sciences to foster cooperation in cancer research.

The Oncogenic Palmitoyl-Protein Network in Prostate Cancer

DTIC Science & Technology

2011-03-31

network is vulnerable to a diet and drug intervention that will employ a Food and Drug Administration-approved cholesterol-reducing agent ( ezetimibe ...therapeutic value of ezetimibe . 15. SUBJECT TERMS castrate-resistant prostate cancer, palmitoylation, signal transduction, S-acylation 16...that this network might be sensitive to pharmacologic targeting of cholesterol using the cholesterol-lowering drug, ezetimibe . Our hypothesis is that

Building Research Collaboration Networks--An Interpersonal Perspective for Research Capacity Building

ERIC Educational Resources Information Center

Huang, Jun Song

2014-01-01

While collaboration is increasingly recognized to be important for research, researchers' collaboration networks are still not adequately recognized as a form of research capacity in the literature. Research is a knowledge creation activity and interpersonal research collaboration networks are important for knowledge cross-fertilization and…

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

PubMed

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

2015-04-28

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.

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

PubMed Central

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

Immunomediated Pan-cancer Regulation Networks are Dominant Fingerprints After Treatment of Cell Lines with Demethylation.

PubMed

El Baroudi, Mariama; Cinti, Caterina; Capobianco, Enrico

2016-01-01

Pan-cancer studies are particularly relevant not only for addressing the complexity of the inherently observed heterogeneity but also for identifying clinically relevant features that may be common to the cancer types. Immune system regulations usually reveal synergistic modulation with other cancer mechanisms and in combination provide insights on possible advances in cancer immunotherapies. Network inference is a powerful approach to decipher pan-cancer systems dynamics. The methodology proposed in this study elucidates the impacts of epigenetic treatment on the drivers of complex pan-cancer regulation circuits involving cell lines of five cancer types. These patterns were observed from differential gene expression measurements following demethylation with 5-azacytidine. Networks were built to establish associations of phenotypes at molecular level with cancer hallmarks through both transcriptional and post-transcriptional regulation mechanisms. The most prominent feature that emerges from our integrative network maps, linking pathway landscapes to disease and drug-target associations, refers primarily to a mosaic of immune-system crosslinked influences. Therefore, characteristics initially evidenced in single cancer maps become motifs well summarized by network cores and fingerprints.

Research priorities in cancer cachexia: The University of Rochester Cancer Center NCI Community Oncology Research Program Research Base Symposium on Cancer Cachexia and Sarcopenia.

PubMed

Dunne, Richard F; Mustian, Karen M; Garcia, Jose M; Dale, William; Hayward, Reid; Roussel, Breton; Buschmann, Mary M; Caan, Bette J; Cole, Calvin L; Fleming, Fergal J; Chakkalakal, Joe V; Linehan, David C; Hezel, Aram F; Mohile, Supriya G

2017-12-01

Cancer cachexia remains understudied and there are no standard treatments available despite the publication of an international consensus definition and the completion of several large phase III intervention trials in the past 6 years. In September 2015, The University of Rochester Cancer Center NCORP Research Base led a Symposium on Cancer Cachexia and Sarcopenia with goals of reviewing the state of the science, identifying knowledge gaps, and formulating research priorities in cancer cachexia through active discussion and consensus. Research priorities that emerged from the discussion included the implementation of morphometrics into clinical decision making, establishing specific diagnostic criteria for the stages of cachexia, expanding patient selection in intervention trials, identifying clinically meaningful trial endpoints, and the investigation of exercise as an intervention for cancer cachexia. Standardizing how we define and measure cancer cachexia, targeting its complex biologic mechanisms, enrolling patients early in their disease course, and evaluating exercise, either alone or in combination, were proposed as initiatives that may ultimately result in the improved design of cancer cachexia therapeutic trials.

Global cancer research initiative

PubMed Central

Love, Richard R

2010-01-01

Cancer is an increasing problem for low- and middle-income countries undergoing an epidemiologic transition from dominantly acute communicable disease to more frequent chronic disease with increased public health successes in the former domain. Progress against cancer in high-income countries has been modest and has come at enormous expense. There are several well-conceived global policy and planning initiatives which, with adequate political will, can favorably impact the growing global cancer challenges. Most financial resources for cancer, however, are spent on diagnosis and management of patients with disease in circumstances where specific knowledge about effective approaches is significantly limited, and the majority of interventions, other than surgery, are not cost-effective in resource-limited countries by global standards. In summary, how to intervene effectively on a global scale for the majority of citizens who develop cancer is poorly defined. In contrast to technology-transfer approaches, markedly increased clinical research activities are more likely to benefit cancer sufferers. In these contexts, a global cancer research initiative is proposed, and mechanisms for realizing such an effort are suggested. PMID:21188101

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

PubMed

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.

Senior Computational Scientist | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP),

A CXCL1 paracrine network links cancer chemoresistance and metastasis

PubMed Central

Acharyya, Swarnali; Oskarsson, Thordur; Vanharanta, Sakari; Malladi, Srinivas; Kim, Juliet; Morris, Patrick G.; Manova-Todorova, Katia; Leversha, Margaret; Hogg, Nancy; Seshan, Venkatraman E.; Norton, Larry; Brogi, Edi; Massagué, Joan

2012-01-01

Metastasis and chemoresistance in cancer are linked phenomena but the molecular basis for this link is unknown. We uncovered a network of paracrine signals between carcinoma, myeloid and endothelial cells that drives both processes in breast cancer. Cancer cells that overexpress CXCL1 and 2 by transcriptional hyperactivation or 4q21 amplification are primed for survival in metastatic sites. CXCL1/2 attract CD11b+Gr1+ myeloid cells into the tumor, which produce chemokines including S100A8/9 that enhance cancer cell survival. While chemotherapeutic agents kill cancer cells, these treatments trigger a parallel stromal reaction leading to TNF-α production by endothelial and other stromal cells. TNF-α heightens the expression of CXCL1/2 in cancer cells, thus amplifying the CXCL1/2-S100A8/9 loop and causing chemoresistance. CXCR2 blockers break this cycle, augmenting the efficacy of chemotherapy against breast tumors and particularly against metastasis. This network of endothelial-carcinoma-myeloid signaling interactions provides a mechanism linking chemoresistance and metastasis, with opportunities for intervention. PMID:22770218

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

Cancer.gov

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 features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified.

Social Network Analysis of Biomedical Research Collaboration Networks in a CTSA Institution

PubMed Central

Bian, Jiang; Xie, Mengjun; Topaloglu, Umit; Hudson, Teresa; Eswaran, Hari; Hogan, William

2014-01-01

BACKGROUND The popularity of social networks has triggered a number of research efforts on network analyses of research collaborations in the Clinical and Translational Science Award (CTSA) community. Those studies mainly focus on the general understanding of collaboration networks by measuring common network metrics. More fundamental questions about collaborations still remain unanswered such as recognizing “influential” nodes and identifying potential new collaborations that are most rewarding. METHODS We analyzed biomedical research collaboration networks (RCNs) constructed from a dataset of research grants collected at a CTSA institution (i.e. University of Arkansas for Medical Sciences (UAMS)) in a comprehensive and systematic manner. First, our analysis covers the full spectrum of a RCN study: from network modeling to network characteristics measurement, from key nodes recognition to potential links (collaborations) suggestion. Second, our analysis employs non-conventional model and techniques including a weighted network model for representing collaboration strength, rank aggregation for detecting important nodes, and Random Walk with Restart (RWR) for suggesting new research collaborations. RESULTS By applying our models and techniques to RCNs at UAMS prior to and after the CTSA, we have gained valuable insights that not only reveal the temporal evolution of the network dynamics but also assess the effectiveness of the CTSA and its impact on a research institution. We find that collaboration networks at UAMS are not scale-free but small-world. Quantitative measures have been obtained to evident that the RCNs at UAMS are moving towards favoring multidisciplinary research. Moreover, our link prediction model creates the basis of collaboration recommendations with an impressive accuracy (AUC: 0.990, MAP@3: 1.48 and MAP@5: 1.522). Last but not least, an open-source visual analytical tool for RCNs is being developed and released through Github. CONCLUSIONS

Creating a "culture of research" in a community hospital: Strategies and tools from the National Cancer Institute Community Cancer Centers Program.

PubMed

Dimond, Eileen P; St Germain, Diane; Nacpil, Lianne M; Zaren, Howard A; Swanson, Sandra M; Minnick, Christopher; Carrigan, Angela; Denicoff, Andrea M; Igo, Kathleen E; Acoba, Jared D; Gonzalez, Maria M; McCaskill-Stevens, Worta

2015-06-01

identify and collect. The model requires a strong emphasis on outreach that challenges hospitals to improve and expand their reach, particularly into underrepresented populations and catchment areas. These efforts build on trust and a referral pipeline within the community which take time and significant commitment to establish. The National Cancer Institute Community Cancer Centers Program experience provides a relevant model to broadly address creating a culture of research in community hospitals that are increasingly networked via systems and consortiums. The strategies used align well with the National Cancer Institute-American Society of Clinical Oncology Accrual Symposium recommendations for patient-/community-, physician-/provider-, and site-/organizational-level approaches to clinical trials; they helped sites achieve organizational culture shifts that enhanced their cancer research programs. The National Cancer Institute Community Cancer Centers Program hospitals reported that the strategies were challenging to implement yet proved valuable as they provided useful metrics for programmatic assessment, planning, reporting, and growth. While focused on oncology trials, these concepts may be useful within other disease-focused research as well. © The Author(s) 2015.

Breast Cancer Research at NASA

NASA Technical Reports Server (NTRS)

1998-01-01

Dr. Harry Mahtani analyzes the gas content of nutrient media from Bioreactor used in research on human breast cancer. NASA's Marshall Space Flight Center (MSFC) is sponsoring research with Bioreactors, rotating wall vessels designed to grow tissue samples in space, to understand how breast cancer works. This ground-based work studies the growth and assembly of human mammary epithelial cells (HMEC) from breast cancer susceptible tissue. Radiation can make the cells cancerous, thus allowing better comparisons of healthy vs. tunourous tissues.

Key factors of clinical research network capacity building.

PubMed

Li, Guowei; Wu, Qianyu; Jin, Yanling; Vanniyasingam, Thuva; Thabane, Lehana

2018-01-01

In general, clinical research network capacity building refers to programs aimed at enhancing networks of researchers to conduct clinical research. Although in the literature there is a large body of research on how to develop and build capacity in clinical research networks, the conceptualizations and implementations remain controversial and challenging. Moreover, the experiences learnt from the past accomplishments and failures can assist in the future capacity building efforts to be more practical, effective and efficient. In this paper, we aim to provide an overview of capacity building in clinical research network by (1) identifying the key barriers to clinical research network capacity building, (2) providing insights into how to overcome those obstacles, and (3) sharing our experiences in collaborating with national and international partners to build capacity in clinical research networks. In conclusion, we have provided some insight into how to address the key factors of clinical research network capacity building and shared some empirical experiences. A successful capacity building practice requires a joint endeavor to procure sufficient resources and support from the relevant stakeholders, to ensure its efficiency, cost-effectiveness, and sustainability.

Research on NGN network control technology

NASA Astrophysics Data System (ADS)

Li, WenYao; Zhou, Fang; Wu, JianXue; Li, ZhiGuang

2004-04-01

Nowadays NGN (Next Generation Network) is the hotspot for discussion and research in IT section. The NGN core technology is the network control technology. The key goal of NGN is to realize the network convergence and evolution. Referring to overlay network model core on Softswitch technology, circuit switch network and IP network convergence realized. Referring to the optical transmission network core on ASTN/ASON, service layer (i.e. IP layer) and optical transmission convergence realized. Together with the distributing feature of NGN network control technology, on NGN platform, overview of combining Softswitch and ASTN/ASON control technology, the solution whether IP should be the NGN core carrier platform attracts general attention, and this is also a QoS problem on NGN end to end. This solution produces the significant practical meaning on equipment development, network deployment, network design and optimization, especially on realizing present network smooth evolving to the NGN. This is why this paper puts forward the research topic on the NGN network control technology. This paper introduces basics on NGN network control technology, then proposes NGN network control reference model, at the same time describes a realizable network structure of NGN. Based on above, from the view of function realization, NGN network control technology is discussed and its work mechanism is analyzed.

Pathway and network analysis of cancer genomes.

PubMed

Creixell, Pau; Reimand, Jüri; Haider, Syed; Wu, Guanming; Shibata, Tatsuhiro; Vazquez, Miguel; Mustonen, Ville; Gonzalez-Perez, Abel; Pearson, John; Sander, Chris; Raphael, Benjamin J; Marks, Debora S; Ouellette, B F Francis; Valencia, Alfonso; Bader, Gary D; Boutros, Paul C; Stuart, Joshua M; Linding, Rune; Lopez-Bigas, Nuria; Stein, Lincoln D

2015-07-01

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 large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations.

Exploring Practice-Research Networks for Critical Professional Learning

ERIC Educational Resources Information Center

Appleby, Yvon; Hillier, Yvonne

2012-01-01

This paper discusses the contribution that practice-research networks can make to support critical professional development in the Learning and Skills sector in England. By practice-research networks we mean groups or networks which maintain a connection between research and professional practice. These networks stem from the philosophy of…

The OncoPPi network of cancer-focused protein-protein interactions to inform biological insights and therapeutic strategies* | Office of Cancer Genomics

Cancer.gov

As genomics advances reveal the cancer gene landscape, a daunting task is to understand how these genes contribute to dysregulated oncogenic pathways. Integration of cancer genes into networks offers opportunities to reveal protein–protein interactions (PPIs) with functional and therapeutic significance. Here, we report the generation of a cancer-focused PPI network, termed OncoPPi, and identification of >260 cancer-associated PPIs not in other large-scale interactomes.

Delphi Study to Determine Rehabilitation Research Priorities for Older Adults With Cancer.

PubMed

Lyons, Kathleen Doyle; Radomski, Mary Vining; Alfano, Catherine M; Finkelstein, Marsha; Sleight, Alix G; Marshall, Timothy F; McKenna, Raymond; Fu, Jack B

2017-05-01

To solicit expert opinions and develop consensus around the research that is needed to improve cancer rehabilitation for older adults. Delphi methods provided a structured process to elicit and prioritize research questions from national experts. National, Web-based survey. Members (N=32) of the American Congress of Rehabilitation Medicine completed at least 1 of 3 investigator-developed surveys. Not applicable. In the first survey, participants identified up to 5 research questions that needed to be answered to improve cancer rehabilitation for older adults. In 2 subsequent surveys, participants viewed the compilation of questions, rated the importance of each question, and identified the 5 most important questions. This generated priority scores for each question. Consensus scores were created to describe the degree of agreement around the priority of each question. Highest priority research concerns the epidemiology and measurement of function and disability in older adult cancer survivors; the effects of cancer rehabilitation interventions on falls, disability, participation, survival, costs, quality of care, and health care utilization; and testing models of care that facilitate referrals from oncology to rehabilitation providers as part of coordinated, multicomponent care. A multipronged approach is needed to fill these gaps, including targeted funding opportunities developed with an advisory panel of cancer rehabilitation experts, development of a research network to facilitate novel collaborations and grant proposals, and coordinated efforts of clinical groups to advocate for funding, practice change, and policy change. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Training the Cancer Research Workforce

Cancer.gov

The National Cancer Institute (NCI) builds up the nation's cancer research workforce through training and career development grants, as well as intramural research experiences at the NIH Clinical Center and NCI offices and laboratories in Maryland.

Lymphatic Education & Research Network

MedlinePlus

Lymphatic Education & Research Network Donate Now Become a Supporting Member X Living with LYMPHEDEMA AND Lymphatic Disease FAQs About ... December 8, 2017 11.08.2017 The Lymphatic Education & Research Network… Read More > ASRM LE&RN Combined ...

Network Penetration Testing and Research

NASA Technical Reports Server (NTRS)

Murphy, Brandon F.

2013-01-01

This paper will focus the on research and testing done on penetrating a network for security purposes. This research will provide the IT security office new methods of attacks across and against a company's network as well as introduce them to new platforms and software that can be used to better assist with protecting against such attacks. Throughout this paper testing and research has been done on two different Linux based operating systems, for attacking and compromising a Windows based host computer. Backtrack 5 and BlackBuntu (Linux based penetration testing operating systems) are two different "attacker'' computers that will attempt to plant viruses and or NASA USRP - Internship Final Report exploits on a host Windows 7 operating system, as well as try to retrieve information from the host. On each Linux OS (Backtrack 5 and BlackBuntu) there is penetration testing software which provides the necessary tools to create exploits that can compromise a windows system as well as other operating systems. This paper will focus on two main methods of deploying exploits 1 onto a host computer in order to retrieve information from a compromised system. One method of deployment for an exploit that was tested is known as a "social engineering" exploit. This type of method requires interaction from unsuspecting user. With this user interaction, a deployed exploit may allow a malicious user to gain access to the unsuspecting user's computer as well as the network that such computer is connected to. Due to more advance security setting and antivirus protection and detection, this method is easily identified and defended against. The second method of exploit deployment is the method mainly focused upon within this paper. This method required extensive research on the best way to compromise a security enabled protected network. Once a network has been compromised, then any and all devices connected to such network has the potential to be compromised as well. With a compromised

A proposed international watershed research network

USGS Publications Warehouse

Osterkamp, W.R.; Gray, J.R.

2003-01-01

An “International Watershed Research Network” is to be an initial project of the Sino-U. S. Centers for Soil and Water Conservation and Environmental Protection. The Network will provide a fundamental database for research personnel of the Centers, as well as of the global research community, and is viewed as an important resource for their successful operation. Efforts are under way to (a) identify and select candidate watersheds, (b) develop standards and protocols for data collection and dissemination, and (c) specify other data sources on erosion, sediment transport, hydrology, and ancillary information of probable interest and use to participants of the Centers. The initial focus of the Network will be on water-deficient areas. Candidate watersheds for the Network are yet to be determined although likely selections include the Ansai Research Station, northern China, and the Walnut Gulch Experimental Watershed, Arizona, USA. The Network is to be patterned after the Vigil Network, an open-ended group of global sites and small drainage basins for which Internet-accessible geomorphic, hydrologic, and biological data are periodically collected or updated. Some types of data, using similar instruments and observation methods, will be collected at all watersheds selected for the Network. Other data from the watersheds that may reflect individual watershed characteristics and research objectives will be collected as well.

About the Breast and Gynecologic Cancer Research Group | Division of Cancer Prevention

Cancer.gov

The Breast and Gynecologic Cancer Research Group conducts and fosters the development of research on the prevention and early detection of breast cancer, cervix and human papillomavirus (HPV)-related cancers, endometrial cancers, ovarian cancers, and precursor conditions related to these cancers. |

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-06-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. © 2011 Elsevier Ltd. All rights reserved.

How does investment in research training affect the development of research networks and collaborations?

PubMed

Paina, Ligia; Ssengooba, Freddie; Waswa, Douglas; M'imunya, James M; Bennett, Sara

2013-05-20

Whether and how research training programs contribute to research network development is underexplored. The Fogarty International Center (FIC) has supported overseas research training programs for over two decades. FIC programs could provide an entry point in the development of research networks and collaborations. We examine whether FIC's investment in research training contributed to the development of networks and collaborations in two countries with longstanding FIC investments - Uganda and Kenya - and the factors which facilitated this process. As part of two case studies at Uganda's Makerere University and Kenya's University of Nairobi, we conducted 53 semi-structured in-depth interviews and nine focus group discussions. To expand on our case study findings, we conducted a focused bibliometric analysis on two purposively selected topic areas to examine scientific productivity and used online network illustration tools to examine the resulting network structures. FIC support made important contributions to network development. Respondents from both Uganda and Kenya confirmed that FIC programs consistently provided trainees with networking skills and exposure to research collaborations, primarily within the institutions implementing FIC programs. In both countries, networks struggled with inclusiveness, particularly in HIV/AIDS research. Ugandan respondents perceived their networks to be more cohesive than Kenyan respondents did. Network cohesiveness was positively correlated with the magnitude and longevity of FIC's programs. Support from FIC grants to local and regional research network development and networking opportunities, such as conferences, was rare. Synergies between FIC programs and research grants helped to solidify and maintain research collaborations. Networks developed where FIC's programs focused on a particular institution, there was a critical mass of trainees with similar interests, and investments for network development were available from

Systematical analysis of lncRNA-mRNA competing endogenous RNA network in breast cancer subtypes.

PubMed

Zhou, Shunheng; Wang, Lihong; Yang, Qian; Liu, Haizhou; Meng, Qianqian; Jiang, Leiming; Wang, Shuyuan; Jiang, Wei

2018-06-01

Breast cancer is one of the most common solid tumors in women involving multiple subtypes. However, the mechanism for subtypes of breast cancer is still complicated and unclear. Recently, several studies indicated that long non-coding RNAs (lncRNAs) could act as sponges to compete miRNAs with mRNAs, participating in various biological processes. We concentrated on the competing interactions between lncRNAs and mRNAs in four subtypes of breast cancer (basal-like, HER2+, luminal A and luminal B), and analyzed the impacts of competing endogenous RNAs (ceRNAs) on each subtype systematically. We constructed four breast cancer subtype-related lncRNA-mRNA ceRNA networks by integrating the miRNA target information and the expression data of lncRNAs, miRNAs and mRNAs. We constructed the ceRNA network for each breast cancer subtype. Functional analysis revealed that the subtype-related ceRNA networks were enriched in cancer-related pathways in KEGG, such as pathways in cancer, miRNAs in cancer, and PI3k-Akt signaling pathway. In addition, we found three common lncRNAs across the four subtype-related ceRNA networks, NEAT1, OPI5-AS1 and AC008124.1, which played specific roles in each subtype through competing with diverse mRNAs. Finally, the potential drugs for treatment of basal-like subtype could be predicted through reversing the differentially expressed lncRNA in the ceRNA network. This study provided a novel perspective of lncRNA-involved ceRNA network to dissect the molecular mechanism for breast cancer.

Research Associate | Center for Cancer Research

Cancer.gov

PROGRAM DESCRIPTION The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). KEY ROLES/RESPONSIBILITIES - Research Associate III Dr. Zbigniew Dauter is the head investigator of the Synchrotron Radiation Research Section (SRRS) of CCR’s Macromolecular Crystallography Laboratory. The Synchrotron Radiation Research Section is located at Argonne National Laboratory, Argonne, Illinois; this is the site of the largest U.S. synchrotron facility. The SRRS uses X-ray diffraction technique to solve crystal structures of various proteins and nucleic acids of biological and medical relevance. The section is also specializing in analyzing crystal structures at extremely high resolution and accuracy and in developing methods of effective diffraction data collection and in using weak anomalous dispersion effects to solve structures of macromolecules. The areas of expertise are: Structural and molecular biology Macromolecular crystallography Diffraction data collection Dr. Dauter requires research support in these areas, and the individual will engage in the purification and preparation of samples, crystallize proteins using various techniques, and derivatize them with heavy atoms/anomalous scatterers, and establish conditions for cryogenic freezing. Individual will also participate in diffraction data collection at the Advanced Photon Source. In addition, the candidate will perform spectroscopic and chromatographic analyses of protein and nucleic acid samples in the context of their purity, oligomeric state and photophysical properties.

Compliance with National Comprehensive Cancer Network anti-emesis guidelines in a Community Hospital Cancer Center.

PubMed

Daniel, Divya; Waddell, Aubrey

2016-02-01

Nausea and vomiting are common adverse events exhibited by patients receiving chemotherapy. Prophylactic use of anti-emetic agents has been shown to reduce chemotherapy-induced nausea and vomiting. Compliance with the National Comprehensive Cancer Network anti-emesis guidelines (Version 1.2013) by practitioners in a community out-patient hospital (Blount Memorial Hospital) has been reviewed and the results are presented herein. Retrospective study of patients receiving their first cycle of chemotherapy. A total of 487 patients were reviewed from January 2005 to July 2012. In total, 70 patients were categorized in the high-risk category, 292 patients were categorized in the moderate-risk category, 60 patients were categorized in the low-risk category, and 65 patients were categorized in the minimal-risk category as per the National Comprehensive Cancer Network guidelines. Included patients were being administered the first cycle of their first treatment at Blount Memorial Hospital. Data were collected retrospectively from patient chemotherapy dispensing folders. In all, 63% of the patients received appropriate anti-emetic prophylaxis medications as per the National Comprehensive Cancer Network guidelines. Post-comparison between outcomes based on the risk category showed that patients in the moderate-risk category were most likely (91%) and patients in the low-risk category were least likely (6.67%) to receive appropriate anti-emetic prophylaxis as per the National Comprehensive Cancer Network guidelines. Overall compliance with guidelines is acceptable. Patients in the moderate risk category are most likely to receive appropriate anti-emetic prophylaxis. © The Author(s) 2014.

Conditional robustness analysis for fragility discovery and target identification in biochemical networks and in cancer systems biology.

PubMed

Bianconi, Fortunato; Baldelli, Elisa; Ludovini, Vienna; Luovini, Vienna; Petricoin, Emanuel F; Crinò, Lucio; Valigi, Paolo

2015-10-19

The study of cancer therapy is a key issue in the field of oncology research and the development of target therapies is one of the main problems currently under investigation. This is particularly relevant in different types of tumor where traditional chemotherapy approaches often fail, such as lung cancer. We started from the general definition of robustness introduced by Kitano and applied it to the analysis of dynamical biochemical networks, proposing a new algorithm based on moment independent analysis of input/output uncertainty. The framework utilizes novel computational methods which enable evaluating the model fragility with respect to quantitative performance measures and parameters such as reaction rate constants and initial conditions. The algorithm generates a small subset of parameters that can be used to act on complex networks and to obtain the desired behaviors. We have applied the proposed framework to the EGFR-IGF1R signal transduction network, a crucial pathway in lung cancer, as an example of Cancer Systems Biology application in drug discovery. Furthermore, we have tested our framework on a pulse generator network as an example of Synthetic Biology application, thus proving the suitability of our methodology to the characterization of the input/output synthetic circuits. The achieved results are of immediate practical application in computational biology, and while we demonstrate their use in two specific examples, they can in fact be used to study a wider class of biological systems.

Science Writer | Center for Cancer Research

Cancer.gov

The Center for Cancer Research (CCR) is seeking a science writer to help us tell our stories of cancer research discoveries, clinical advances and our patients, who are participating in clinical trials.  CCR is the National Cancer Institute’s internal cancer center located on campuses in Bethesda and Frederick, Maryland.  The writing supports communications for our website,

Cancer Core Europe: a consortium to address the cancer care-cancer research continuum challenge.

PubMed

Eggermont, Alexander M M; Caldas, Carlos; Ringborg, Ulrik; Medema, René; Tabernero, Josep; Wiestler, Otmar

2014-11-01

European cancer research for a transformative initiative by creating a consortium of six leading excellent comprehensive cancer centres that will work together to address the cancer care-cancer research continuum. Prerequisites for joint translational and clinical research programs are very demanding. These require the creation of a virtual single 'e-hospital' and a powerful translational platform, inter-compatible clinical molecular profiling laboratories with a robust underlying computational biology pipeline, standardised functional and molecular imaging, commonly agreed Standard Operating Procedures (SOPs) for liquid and tissue biopsy procurement, storage and processing, for molecular diagnostics, 'omics', functional genetics, immune-monitoring and other assessments. Importantly also it requires a culture of data collection and data storage that provides complete longitudinal data sets to allow for: effective data sharing and common database building, and to achieve a level of completeness of data that is required for conducting outcome research, taking into account our current understanding of cancers as communities of evolving clones. Cutting edge basic research and technology development serve as an important driving force for innovative translational and clinical studies. Given the excellent track records of the six participants in these areas, Cancer Core Europe will be able to support the full spectrum of research required to address the cancer research- cancer care continuum. Cancer Core Europe also constitutes a unique environment to train the next generation of talents in innovative translational and clinical oncology. Copyright © 2014. Published by Elsevier Ltd.

Evaluation of Treatment- and Disease-Related Symptoms in Advanced Head and Neck Cancer: Validation of the National Comprehensive Cancer Network-Functional Assessment of Cancer Therapy-Head and Neck Cancer Symptom Index-22 (NFHNSI-22)

PubMed Central

Pearman, Timothy P.; Beaumont, Jennifer L.; Paul, Diane; Abernethy, Amy P.; Jacobsen, Paul B.; Syrjala, Karen L.; Von Roenn, Jamie; Cella, David

2018-01-01

-to-strong correlations with the existing Functional Assessment of Chronic Illness Therapy measure. Conclusion The National Comprehensive Cancer Network-Functional Assessment of Cancer Therapy-Head and Neck Cancer Symptom Index-22 adequately reflects symptom and side effect concerns of advanced HCN patients as well as oncology physicians. This instrument can be used to evaluate the most important disease-related symptoms, treatment side effects, and function/well-being in patients with advanced HCNs in clinical practice and research. PMID:23017622

Research on cancer diagnosis in Malaysia: current status.

PubMed

Looi, L M; Zubaidah, Z; Cheah, P L; Cheong, S K; Gudum, H R; Iekhsan, O; Ikram, S I; Jamal, R; Mak, J W; Othman, N H; Puteri, J N; Rosline, H; Sabariah, A R; Seow, H F; Sharifah, N A

2004-06-01

Cancer is a major morbidity and mortality concern in Malaysia. Based on National Cancer Registry data, the Malaysian population is estimated to bear a cancer burden of about 40,000 new cases per year, and a cumulative lifetime risk of about 1:4. Cancer research in Malaysia has to consider needs relevant to our population, and resources constraints. Hence, funding bodies prioritise cancers of high prevalence, unique to our community and posing specific clinical problems. Cancer diagnosis is crucial to cancer management. While cancer diagnosis research largely aims at improvements in diagnostic information towards more appropriate therapy, it also impacts upon policy development and other areas of cancer management. The scope of cancer diagnosis upon which this paper is based, and their possible impact on other R&D areas, has been broadly categorized into: (1) identification of aetiological agents and their linkages to the development of precancer and cancer (impact on policy development, cancer prevention and treatment), (2) cancer biology and pathogenesis (impact on cancer prevention, treatment strategies and product development), (3) improvements in accuracy, sensitivity and specificity in cancer detection, monitoring and classification (impact on technology development) and (4) prognostic and predictive parameters (impact on treatment strategies). This paper is based on data collected by the Working Group on Cancer Diagnosis Research for the First National Conference on Cancer Research Coordination in April 2004. Data was collated from the databases of Institutions/Universities where the authors are employed, the Ministry of Science, Technology and Innovation (MOSTI) and targeted survey feedback from key cancer researchers. Under the 7th Malaysia Plan, 76 cancer projects were funded through the Intensified Research in Priority Areas (IRPA) scheme of MOSTI, amounting to almost RM15 million of grant money. 47(61.8%) of these projects were substantially in cancer

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

PubMed Central

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

Developing an Open Source, Reusable Platform for Distributed Collaborative Information Management in the Early Detection Research Network

NASA Technical Reports Server (NTRS)

Hart, Andrew F.; Verma, Rishi; Mattmann, Chris A.; Crichton, Daniel J.; Kelly, Sean; Kincaid, Heather; Hughes, Steven; Ramirez, Paul; Goodale, Cameron; Anton, Kristen;

Dr. Ted Trimble: Why I Do Cancer Research

Cancer.gov

In a video, Dr. Ted Trimble talks about the importance of cancer research. World Cancer Research Day commemorates the important role research and cancer researchers play in reducing the global burden of cancer.

Customizing Therapies for Lung Cancer | Center for Cancer Research

Cancer.gov

Lung cancer is the leading cause of cancer-related death in both men and women. Although there have been modest improvements in short-term survival over the last few decades, five-year survival rates for lung cancer remain low at only 16 percent. Treatment for lung cancer depends on the stage of the disease at diagnosis, but generally consists of some combination of surgery, chemotherapy, and radiation therapy. Increasing attention has been paid in recent years to customizing therapies based on the molecular characteristics of patients’ tumors. Some of these targeted regimens have already been integrated into the treatment arsenal for lung cancer and others are still being studied in clinical trials, including several being conducted by researchers at NCI’s Center for Cancer Research.

Patient-powered research networks aim to improve patient care and health research.

PubMed

Fleurence, Rachael L; Beal, Anne C; Sheridan, Susan E; Johnson, Lorraine B; Selby, Joe V

2014-07-01

The era of big data, loosely defined as the development and analysis of large or complex data sets, brings new opportunities to empower patients and their families to generate, collect, and use their health information for both clinical and research purposes. In 2013 the Patient-Centered Outcomes Research Institute launched a large national research network, PCORnet, that includes both clinical and patient-powered research networks. This article describes these networks, their potential uses, and the challenges they face. The networks are engaging patients, family members, and caregivers in four key ways: contributing data securely, with privacy protected; including diverse and representative groups of patients in research; prioritizing research questions, participating in research, and disseminating results; and participating in the leadership and governance of patient-powered research networks. If technical, regulatory, and organizational challenges can be overcome, PCORnet will allow research to be conducted more efficiently and cost-effectively and results to be disseminated quickly back to patients, clinicians, and delivery systems to improve patient health. Project HOPE—The People-to-People Health Foundation, Inc.

Physician Assistant | Center for Cancer Research

Cancer.gov

We are looking for a Physician Assistant to join our clinical team to help us provide continuity of care for patients enrolled in clinical trials. Duties include, but are not limited to, participating in clinical rounds and conferences, performing comprehensive health care assessments and examinations, and supporting inpatient and outpatient care of subjects enrolled in clinical trials.  Be part of our mission to solve the most important, challenging and neglected problems in modern cancer research and patient care.  The National Cancer Institute’s Center for Cancer Research is a world-leading cancer research organization working toward scientific breakthroughs at medicine’s cutting edge.   Our scientists can’t do it alone. It takes an extraordinary team of researchers, clinical experts and administrators to improve the lives of cancer patients and answer the most important questions in cancer biology and treatment.

Research in Network Management Techniques for Tactical Data Communications Network.

DTIC Science & Technology

1982-09-01

the control period. Research areas include Packet Network modelling, adaptive network routing, network design algorithms, network design techniques...contro!lers are designed to perform their limited tasks optimally. For the dynamic routing problem considered here, the local controllers are node...feedback to finding in optimum stead-o-state routing (static strategies) under non - control which can be easily implemented in real time. congested

Latest discoveries and trends in translational cancer research: highlights of the 2008 Annual Meeting of the American Association for Cancer Research.

PubMed

Cho, William C S

2008-08-01

The Annual Meeting of the American Association for Cancer Research (AACR) is the world's largest and most comprehensive gathering of cancer researchers. At the 2008 AACR Annual Meeting, innovative research approaches, novel technologies, potentially life-saving therapies in the pipeline, late-breaking clinical trial findings, and new approaches to cancer prevention were presented by top scientists. Reflecting the global state of cancer research with an eye toward future trends, several areas of great science and discovery in the cancer field were shared in this report, which include cancer biomarkers, the role of microRNAs in cancer research, cancer stem cells, tumor microenvironment, targeted therapy, and cancer prevention. This article presents an overview of hot topics discussed at the 2008 AACR Annual Meeting and recapitulates some scientific sessions geared toward new technologies, recent progress, and current challenges reported by cancer researchers. For those who did not attend the meeting, this report may serve as a highlight of this important international cancer research meeting.

Regional Research Networking: A Stimulus to Research Collaboration and Research Productivity.

ERIC Educational Resources Information Center

McElmurry, Beverly J.; Minckley, Barbara B.

1986-01-01

Models for collegial networking as a means of increasing the participants' scholarly productivity are presented. A Midwestern historical methodology research interest group is described as an example of the long-term benefits of forming networks of scholars. (MSE)

The physical therapy clinical research network (PTClinResNet): methods, efficacy, and benefits of a rehabilitation research network.

PubMed

Winstein, Carolee; Pate, Patricia; Ge, Tingting; Ervin, Carolyn; Baurley, James; Sullivan, Katherine J; Underwood, Samantha J; Fowler, Eileen G; Mulroy, Sara; Brown, David A; Kulig, Kornelia; Gordon, James; Azen, Stanley P

2008-11-01

This article describes the vision, methods, and implementation strategies used in building the infrastructure for PTClinResNet, a clinical research network designed to assess outcomes for health-related mobility associated with evidence-based physical therapy interventions across and within four different disability groups. Specific aims were to (1) create the infrastructure necessary to develop and sustain clinical trials research in rehabilitation, (2) generate evidence to evaluate the efficacy of resistance exercise-based physical interventions designed to improve muscle performance and movement skills, and (3) provide education and training opportunities for present and future clinician-researchers and for the rehabilitation community at-large in its support of evidence-based practice. We present the network's infrastructure, development, and several examples that highlight the benefits of a clinical research network. We suggest that the network structure is ideal for building research capacity and fostering multisite, multiinvestigator clinical research projects designed to generate evidence for the efficacy of rehabilitation interventions.

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

PubMed

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.

Adapting to stress - chaperome networks in cancer.

PubMed

Joshi, Suhasini; Wang, Tai; Araujo, Thaís L S; Sharma, Sahil; Brodsky, Jeffrey L; Chiosis, Gabriela

2018-05-23

In this Opinion article, we aim to address how cells adapt to stress and the repercussions chronic stress has on cellular function. We consider acute and chronic stress-induced changes at the cellular level, with a focus on a regulator of cellular stress, the chaperome, which is a protein assembly that encompasses molecular chaperones, co-chaperones and other co-factors. We discuss how the chaperome takes on distinct functions under conditions of stress that are executed in ways that differ from the one-on-one cyclic, dynamic functions exhibited by distinct molecular chaperones. We argue that through the formation of multimeric stable chaperome complexes, a state of chaperome hyperconnectivity, or networking, is gained. The role of these chaperome networks is to act as multimolecular scaffolds, a particularly important function in cancer, where they increase the efficacy and functional diversity of several cellular processes. We predict that these concepts will change how we develop and implement drugs targeting the chaperome to treat cancer.

Geographical variation in cancer survival in England, 1991–2006: an analysis by Cancer Network

PubMed Central

Quaresma, Manuela; Coleman, Michel P; Gordon, Emma; Forman, David; Rachet, Bernard

2011-01-01

Background Reducing geographical inequalities in cancer survival in England was a key aim of the Calman–Hine Report (1995) and the NHS Cancer Plan (2000). This study assesses whether geographical inequalities changed following these policy developments by analysing the trend in 1-year relative survival in the 28 cancer networks of England. Methods Population-based age-standardised relative survival at 1 year is estimated for 1.4 million patients diagnosed with cancer of the oesophagus, stomach, colon, lung, breast (women) or cervix in England during 1991–2006 and followed up to 2007. Regional and deprivation-specific life tables are built to adjust survival estimates for differences in background mortality. Analysis is divided into three calendar periods: 1991–5, 1996–2000 and 2001–6. Funnel plots are used to assess geographical variation in survival over time. Results One-year relative survival improved for all cancers except cervical cancer. There was a wide geographical variation in survival with generally lower estimates in northern England. This north–south divide became less marked over time, although the overall number of cancer networks that were lower outliers compared with the England value remained stable. Breast cancer was the only cancer for which there was a marked reduction in geographical inequality in survival over time. Conclusion Policy changes over the past two decades coincided with improved relative survival, without an increase in geographical variation. The north–south divide in relative survival became less pronounced over time but geographical inequalities persist. The reduction in geographical inequality in breast cancer survival may be followed by a similar trend for other cancers, provided government recommendations are implemented similarly. PMID:21321064

Cross-platform method for identifying candidate network biomarkers for prostate cancer.

PubMed

Jin, G; Zhou, X; Cui, K; Zhang, X-S; Chen, L; Wong, S T C

2009-11-01

Discovering biomarkers using mass spectrometry (MS) and microarray expression profiles is a promising strategy in molecular diagnosis. Here, the authors proposed a new pipeline for biomarker discovery that integrates disease information for proteins and genes, expression profiles in both genomic and proteomic levels, and protein-protein interactions (PPIs) to discover high confidence network biomarkers. Using this pipeline, a total of 474 molecules (genes and proteins) related to prostate cancer were identified and a prostate-cancer-related network (PCRN) was derived from the integrative information. Thus, a set of candidate network biomarkers were identified from multiple expression profiles composed by eight microarray datasets and one proteomics dataset. The network biomarkers with PPIs can accurately distinguish the prostate patients from the normal ones, which potentially provide more reliable hits of biomarker candidates than conventional biomarker discovery methods.

Electron Microscopist | Center for Cancer Research

Cancer.gov

PROGRAM DESCRIPTION The Cancer Research Technology Program (CRTP) develops and implements emerging technology, cancer biology expertise and research capabilities to accomplish NCI research objectives. The CRTP is an outward-facing, multi-disciplinary hub purposed to enable the external cancer research community and provides dedicated support to NCI’s intramural Center for Cancer Research (CCR). The dedicated units provide electron microscopy, protein characterization, protein expression, optical microscopy and genetics. These research efforts are an integral part of CCR at the Frederick National Laboratory for Cancer Research (FNLCR). CRTP scientists also work collaboratively with intramural NCI investigators to provide research technologies and expertise. KEY ROLES/RESPONSIBILITIES - THIS POSITION IS CONTINGENT UPON FUNDING APPROVAL The Electron Microscopist will: Operate ultramicrotomes (Leica) and other instrumentation related to the preparation of embedded samples for EM (TEM and SEM) Operate TEM microscopes, (specifically Hitachi, FEI T20 and FEI T12) as well as SEM microscopes (Hitachi); task will include loading samples, screening, and performing data collection for a variety of samples: from cells to proteins Manage maintenance for the TEM and SEM microscopes Provide technical advice to investigators on sample preparation and data collection

Prediction and Testing of Biological Networks Underlying Intestinal Cancer

PubMed Central

Mariadason, John M.; Wang, Donghai; Augenlicht, Leonard H.; Chance, Mark R.

2010-01-01

Colorectal cancer progresses through an accumulation of somatic mutations, some of which reside in so-called “driver” genes that provide a growth advantage to the tumor. To identify points of intersection between driver gene pathways, we implemented a network analysis framework using protein interactions to predict likely connections – both precedented and novel – between key driver genes in cancer. We applied the framework to find significant connections between two genes, Apc and Cdkn1a (p21), known to be synergistic in tumorigenesis in mouse models. We then assessed the functional coherence of the resulting Apc-Cdkn1a network by engineering in vivo single node perturbations of the network: mouse models mutated individually at Apc (Apc1638N+/−) or Cdkn1a (Cdkn1a−/−), followed by measurements of protein and gene expression changes in intestinal epithelial tissue. We hypothesized that if the predicted network is biologically coherent (functional), then the predicted nodes should associate more specifically with dysregulated genes and proteins than stochastically selected genes and proteins. The predicted Apc-Cdkn1a network was significantly perturbed at the mRNA-level by both single gene knockouts, and the predictions were also strongly supported based on physical proximity and mRNA coexpression of proteomic targets. These results support the functional coherence of the proposed Apc-Cdkn1a network and also demonstrate how network-based predictions can be statistically tested using high-throughput biological data. PMID:20824133

Research Networks, Mentorship and Sustainability Knowledge

NASA Astrophysics Data System (ADS)

Kafle, A.; Mukhopadhyay, P.; Nepal, M.; Shyamsundar, P.

2015-12-01

In South Asia, a majority of institutions are ill-equipped to undertake research on multi-disciplinary environmental problems, though these problems are increasing at a fast rate and connected to the region's poverty and growth objectives. In this context, the South Asian Network for Development and Environmental Economics (SANDEE) tries to fill a research, training and knowledge gap by building skills in the area of Environment and Development Economics. In this paper, the authors argue that research networks contribute to the growth of sustainability knowledge through (a) knowledge creation, (b) knowledge transfer and (c) knowledge deepening. The paper tries to show the relationship between capacity building, mentorship and research scholarship. It demonstrates that researchers, by associating with the network and its multiple training and mentoring processes, are able to build skills, change curricula and deliver useful knowledge products. The paper discusses the need for interdisciplinary research and the challenges of bridging the gap between research outputs and policy reforms.

Social Network Analysis of a Scientist-Practitioner Research Initiative Established to Facilitate Science Dissemination and Implementation within States and Communities

ERIC Educational Resources Information Center

Ginexi, Elizabeth M.; Huang, Grace; Steketee, Michael; Tsakraklides, Sophia; MacAllum, Keith; Bromberg, Julie; Huffman, Amanda; Luke, Douglas A.; Leischow, Scott J.; Okamoto, Janet M.; Rogers, Todd

2017-01-01

This article presents a case study of a scientist-practitioner research network established by the National Cancer Institute's State and Community Tobacco Control Research Initiative. While prior programs have focused on collaboration among scientists, a goal here was to encourage collaborations with non-university, practice-based partners. Two…

The National Clinical Trials Network: Conducting Successful Clinical Trials of New Therapies for Rare Cancers

PubMed Central

Schott, Anne F.; Welch, John J.; Verschraegen, Claire F.; Kurzrock, Razelle

2015-01-01

Rare cancers account for 27% of neoplasms diagnosed each year, and 25% of cancer-related deaths in the United States. However, rare cancers show some of the highest response rates to targeted therapies, probably due to identification of oncogenic drivers with little inter-patient variability. Although the low incidence of rare cancers make large scale randomized trials involving single histologies difficult to perform, drugs have been successfully developed in rare cancers utilizing clinical trial designs that combine microscopic anatomies. Such trials are being pursued within the National Clinical Trials Network (NCTN), which possesses unique qualifications to perform widespread molecular screening of tumors for patient enrollment onto therapeutic clinical trials. When larger clinical trials are needed to determine optimum treatment strategies in rare cancers, the NCTN's broad reach in North America and internationally, and ability to partner with both US-based and international research organizations, can make these challenging studies feasible. PMID:26433554

Secretary | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research programs in basic or applied molecular biology, immunology, retrovirology, cancer biology, or human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick national Laboratory for Cancer Research (FNLCR). The BSP Office provides procurement and logistical assistance in support of the research activities of the Center for Cancer Research.KEY ROLES/RESPONSIBILITIES The Secretary III will: Provide heavy-volume procurement support to a large customer base of laboratory staff, both Leidos Biomed and CCR (gov’t), using blanket orders, purchase requisitions, credit card, and online warehouse system Data entry into appropriate financial system component (CostPoint, Cor360), status checks on orders, maintenance of orders log, reconciliation of credit card transactions, maintenance of electronic filing systems Providing logistical support for the facilitation of travel packages (both pre-travel and post travel) for Leidos Biomed employees, as well as the coordination of seminar speakers and subsequent reimbursements Composing and answering emails/correspondence Communicating with all levels of personnel, both verbally and in writing, to gather and clearly convey information

Nutrition and Cancer Prevention Research Practicum | Division of Cancer Prevention

Cancer.gov

The Nutritional Science Research Group in the Division of Cancer Prevention at the National Cancer Institute, National Institutes of Health and the Department of Nutrition at the Clinical Center, National Institutes of Health are offering a one week educational opportunity in "Nutrition and Cancer Prevention Research" for individuals with a sustained commitment to nutrition

Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content

PubMed Central

Kling, Teresia; Johansson, Patrik; Sanchez, José; Marinescu, Voichita D.; Jörnsten, Rebecka; Nelander, Sven

2015-01-01

Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool (cancerlandscapes.org), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets. PMID:25953855

Cancer Genetics and Signaling | Center for Cancer Research

Cancer.gov

The Cancer, Genetics, and Signaling (CGS) Group at the National Cancer Institute at Frederick  offers a competitive postdoctoral training and mentoring program focusing on molecular and genetic aspects of cancer. The CGS Fellows Program is designed to attract and train exceptional postdoctoral fellows interested in pursuing independent research career tracks. CGS Fellows

Patient Care Coordinator | Center for Cancer Research

Cancer.gov

We are looking for a Patient Care Coordinator to join our clinical team to help us coordinate care for patients enrolled on our clinical research protocols. Duties include scheduling appointments, coordinating new patients, obtaining patient records, attending weekly clinic meetings, and data base entry. Be part of our mission to solve the most important, challenging and neglected problems in modern cancer research and patient care.  The National Cancer Institute’s Center for Cancer Research is a world-leading cancer research organization working toward scientific breakthroughs at medicine’s cutting edge.   Our scientists can’t do it alone. It takes an extraordinary team of researchers, clinical experts and administrators to improve the lives of cancer patients and answer the most important questions in cancer biology and treatment.

Fighting liver cancer with combination immunotherapies | Center for Cancer Research

Cancer.gov

A new clinical trial testing the effectiveness of immunotherapy treatment combinations against liver cancer is enrolling patients at the NIH Clinical Center in Bethesda, Maryland. Individually, immunotherapy drugs harness the power of the human immune system to better identify and kill cancer cells. Now, researchers at the NIH’s Center for Cancer Research have begun to find

Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends.

PubMed

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.

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

PubMed

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

O8.10A MODEL FOR RESEARCH INITIATIVES FOR RARE CANCERS: THE COLLABORATIVE EPENDYMOMA RESEARCH NETWORK (CERN)

PubMed Central

Armstrong, T.S.; Aldape, K.; Gajjar, A.; Haynes, C.; Hirakawa, D.; Gilbertson, R.; Gilbert, M.R.

2014-01-01

Ependymoma represents less than 5% of adult central nervous system (CNS) tumors and a higher percentage of pediatric CNS tumors, but it remains an orphan disease. The majority of the laboratory-based research and clinical trials have been conducted in the pediatric setting, a reflection of the relative incidence and funding opportunities. CERN, created in 2006, was designed to establish a collaborative effort between laboratory and clinical research and pediatric and adult investigators. The organization of CERN is based on integration and collaboration among five projects. Project 1 contains the clinical trials network encompassing both adult and pediatric centers. This group has completed 2 clinical trials with more underway. Project 2 is focused on molecular classification of human ependymoma tumor tissues and also contains the tumor repository which has now collected over 600 fully clinically annotated CNS ependymomas from adults and children. Project 3 is focused on drug discovery utilizing robust laboratory models of ependymoma to perform high throughput screening of drug libraries, then taking promising agents through extensive preclinical testing including monitoring of drug delivery to tumor using state of the art microdialysis. Project 4 contains the basic research efforts evaluating the molecular pathogenesis of ependymoma and has successfully translated these findings by generating the first mouse models of ependymoma that are employed in preclinical drug development in Project 3. Project 5 studies patient outcomes, including the incorporation of these measures in the clinical trials. This project also contains an online Ependymoma Outcomes survey, collecting data on the consequences of the disease and its treatment. These projects have been highly successful and collaborative. For example, the serial measurement of symptom burden (Project 5) has greatly contributed to the evaluation of treatment efficacy of a clinical trial (Project 1) and

GenePattern Notebooks for Cancer Research | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The goal is to use the GenePattern computational genomics platform, which has served the cancer community since 2004, as the foundation for a new electronic notebook environment to provide cancer research community a way to easily collaborate on, document, capture, and share their work, from conception through analysis to publication.

Patient Care Coordinator | Center for Cancer Research

Cancer.gov

We are looking for a Patient Care Coordinator to join our thoracic and gastrointestinal oncology clinical team to help us coordinate care for patients enrolled on our clinical research protocols. Duties include scheduling appointments, coordinating new patients, obtaining patient records, attending weekly clinic meetings, and data base entry.  Be part of our mission to solve the most important, challenging and neglected problems in modern cancer research and patient care.  The National Cancer Institute’s Center for Cancer Research is a world-leading cancer research organization working toward scientific breakthroughs at medicine’s cutting edge.  Our scientists can’t do it alone. It takes an extraordinary team of researchers, clinical experts and administrators to improve the lives of cancer patients and answer the most important questions in cancer biology and treatment.

Creatiing a Collaborative Research Network for Scientists

NASA Astrophysics Data System (ADS)

Gunn, W.

2012-12-01

This abstract proposes a discussion of how professional science communication and scientific cooperation can become more efficient through the use of modern social network technology, using the example of Mendeley. Mendeley is a research workflow and collaboration tool which crowdsources real-time research trend information and semantic annotations of research papers in a central data store, thereby creating a "social research network" that is emergent from the research data added to the platform. We describe how Mendeley's model can overcome barriers for collaboration by turning research papers into social objects, making academic data publicly available via an open API, and promoting more efficient collaboration. Central to the success of Mendeley has been the creation of a tool that works for the researcher without the requirement of being part of an explicit social network. Mendeley automatically extracts metadata from research papers, and allows a researcher to annotate, tag and organize their research collection. The tool integrates with the paper writing workflow and provides advanced collaboration options, thus significantly improving researchers' productivity. By anonymously aggregating usage data, Mendeley enables the emergence of social metrics and real-time usage stats on top of the articles' abstract metadata. In this way a social network of collaborators, and people genuinely interested in content, emerges. By building this research network around the article as the social object, a social layer of direct relevance to academia emerges. As science, particularly Earth sciences with their large shared resources, become more and more global, the management and coordination of research is more and more dependent on technology to support these distributed collaborations.

Assessing Breast Cancer Risk with an Artificial Neural Network

PubMed

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

The power and promise of "rewiring" the mitogen-activated protein kinase network in prostate cancer therapeutics.

PubMed

Papatsoris, Athanasios G; Karamouzis, Michalis V; Papavassiliou, Athanasios G

2007-03-01

Prostate cancer is the most frequently diagnosed cancer among men and the second leading cause of male cancer deaths. Initially, tumor growth is androgen dependent and thus responsive to pharmacologic androgen deprivation, but there is a high rate of treatment failure because the disease evolves in an androgen-independent state. Growing evidence suggests that the Ras/mitogen-activated protein kinase (MAPK) signaling cascade represents a pivotal molecular circuitry participating directly or indirectly in prostate cancer evolution. The crucial role of the protein elements comprising this complex signal transduction network makes them potential targets for pharmacologic interference. Here, we will delineate the current knowledge regarding the involvement of the Ras/MAPK pathway in prostate carcinogenesis, spotlight ongoing research concerning the development of novel targeted agents such as the Ras/MAPK inhibitors in prostate cancer, and discuss the future perspectives of their therapeutic efficacy.

Adherence to the World Cancer Research Fund/American Institute for Cancer Research recommendations and breast cancer risk.

PubMed

Harris, Holly R; Bergkvist, Leif; Wolk, Alicja

2016-06-01

The World Cancer Research Fund/American Association for Cancer Research (WCRF/AICR) has published eight nutrition-related recommendations for the prevention of cancer. However, few prospective studies have examined these recommendations by breast cancer hormone receptor subtype and only one case-control study has included the dietary supplements recommendation in their evaluation. We investigated whether adherence to the WCRF/AICR cancer prevention recommendations was associated with breast cancer incidence, overall and by hormone receptor subtype, in the Swedish Mammography Cohort. Among 31,514 primarily postmenopausal women diet and lifestyle factors were assessed with a self-administered food frequency questionnaire. A score was constructed based on adherence to the recommendations for body fatness, physical activity, energy density, plant foods, animal foods, alcoholic drinks and dietary supplements (score range 0-7). Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (95% CIs). During 15 years of follow-up 1,388 cases of breast cancer were identified. Women who met six to seven recommendations had a 51% decreased risk of breast cancer compared to women meeting only zero to two recommendations (95% CI = 0.35-0.70). The association between each additional recommendation met and breast cancer risk was strongest for the ER-positive/PR-positive subtype (HR = 0.86; 95% CI = 0.79-0.94), while for the ER-negative/PR-negative subtype the individual recommendations regarding plant and animal foods were most strongly associated with reduced risk. Our findings support that adherence to the WCRF/AICR recommendations reduces breast cancer risk in a population of primarily postmenopausal women. Promoting these recommendations to the public could help reduce breast cancer incidence. © 2016 UICC.

A subset polynomial neural networks approach for breast cancer diagnosis.

PubMed

O'Neill, T J; Penm, Jack; Penm, Jonathan

2007-01-01

Breast cancer is a very common and serious cancer for women that is diagnosed in one of every eight Australian women before the age of 85. The conventional method of breast cancer diagnosis is mammography. However, mammography has been reported to have poor diagnostic capability. In this paper we have used subset polynomial neural network techniques in conjunction with fine needle aspiration cytology to undertake this difficult task of predicting breast cancer. The successful findings indicate that adoption of NNs is likely to lead to increased survival of women with breast cancer, improved electronic healthcare, and enhanced quality of life.

NCI National Clinical Trials Network Structure

Cancer.gov

Learn about how the National Clinical Trials Network (NCTN) is structured. The NCTN is a program of the National Cancer Institute that gives funds and other support to cancer research organizations to conduct cancer clinical trials.

Aggressive surgery for borderline resectable pancreatic cancer: evaluation of National Comprehensive Cancer Network guidelines.

PubMed

Yamada, Suguru; Fujii, Tsutomu; Sugimoto, Hiroyuki; Nomoto, Shuji; Takeda, Shin; Kodera, Yasuhiro; Nakao, Akimasa

2013-08-01

The objective of this study was to evaluate the relevance of defining borderline resectable (BR) pancreatic cancer as a distinct entity in the treatment scheme of pancreatic cancer as proposed by the National Comprehensive Cancer Network. Among 375 patients with pancreatic cancer, 137 patients were deemed to have resectable disease (R) by preoperative imaging studies, whereas 96 were found to have an unresectable disease during surgery. The remaining 142 patients fulfilled the definition of BR and were further classified into 3 subgroups based on the National Comprehensive Cancer Network guidelines: portal vein invasion (PV[+]), common hepatic artery invasion (CHA[+]), and superior mesenteric artery invasion (SMA[+]). PV(+) was subdivided into types B, C, and D according to the degree of portal vein invasion. Patients in the R group had significantly better survival than those in the PV(+) group (P = 0.0038), who in turn survived significantly longer than those classified as SMA(+) (P = 0.041). Type B patients survived significantly longer than did types C and D patients (P = 0.013 and P = 0.030, respectively). In PV(+) patients, compliance with postoperative chemotherapy at 3 and 6 months was 56.9% and 44.6%, respectively, substantially inferior to patients with resectable disease (72.6% and 54.7%, respectively). The optimal treatment strategy may differ among various subgroups within the BR category.

Innovative research of AD HOC network mobility model

NASA Astrophysics Data System (ADS)

Chen, Xin

2017-08-01

It is difficult for researchers of AD HOC network to conduct actual deployment during experimental stage as the network topology is changeable and location of nodes is unfixed. Thus simulation still remains the main research method of the network. Mobility model is an important component of AD HOC network simulation. It is used to describe the movement pattern of nodes in AD HOC network (including location and velocity, etc.) and decides the movement trail of nodes, playing as the abstraction of the movement modes of nodes. Therefore, mobility model which simulates node movement is an important foundation for simulation research. In AD HOC network research, mobility model shall reflect the movement law of nodes as truly as possible. In this paper, node generally refers to the wireless equipment people carry. The main research contents include how nodes avoid obstacles during movement process and the impacts of obstacles on the mutual relation among nodes, based on which a Node Self Avoiding Obstacle, i.e. NASO model is established in AD HOC network.

Collaborative networks for both improvement and research.

PubMed

Clancy, Carolyn M; Margolis, Peter A; Miller, Marlene

2013-06-01

Moving significant therapeutic discoveries beyond early biomedical translation or T1 science and into practice involves: (1) T2 science, identifying "the right treatment for the right patient in the right way at the right time" (eg, patient-centered outcomes research) and tools to implement this knowledge (eg, guidelines, registries); and (2) T3 studies addressing how to achieve health care delivery change. Collaborative improvement networks can serve as large-scale, health system laboratories to engage clinicians, researchers, patients, and parents in testing approaches to translate research into practice. Improvement networks are of particular importance for pediatric T2 and T3 research, as evidence to establish safety and efficacy of therapeutic interventions in children is often lacking. Networks for improvement and research are also consistent with the Institute of Medicine's Learning Healthcare Systems model in which learning networks provide a system for improving care and outcomes and generate new knowledge in near real-time. Creation of total population registries in collaborative network sites provides large, representative study samples with high-quality data that can be used to generate evidence and to inform clinical decision-making. Networks use collaboration, data, and quality-improvement methods to standardize practice. Therefore, variation in outcomes due to unreliable and unnecessary care delivery is reduced, increasing statistical power, and allowing a consistent baseline from which to test new strategies. In addition, collaborative networks for improvement and research offer the opportunity to not only make improvements but also to study improvements to determine which interventions and combination of strategies work best in what settings.

Predicting selective drug targets in cancer through metabolic networks

PubMed Central

Folger, Ori; Jerby, Livnat; Frezza, Christian; Gottlieb, Eyal; Ruppin, Eytan; Shlomi, Tomer

2011-01-01

The interest in studying metabolic alterations in cancer and their potential role as novel targets for therapy has been rejuvenated in recent years. Here, we report the development of the first genome-scale network model of cancer metabolism, validated by correctly identifying genes essential for cellular proliferation in cancer cell lines. The model predicts 52 cytostatic drug targets, of which 40% are targeted by known, approved or experimental anticancer drugs, and the rest are new. It further predicts combinations of synthetic lethal drug targets, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection. Finally, potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled. PMID:21694718

Korea University Joins the International Efforts in Clinical Proteogenomics Cancer Research | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute's (NCI) Office of Cancer Clinical Proteomics Research, part of the National Institutes of Health, and Korea University (KU) located in The Republic of Korea have signed a Memorandum of Understanding (MOU) in clinical proteogenomics cancer research. The MOU between NCI and KU represents the twenty-ninth institution and eleventh country to join the continued effort of the International Cancer Proteogenome Consortium (ICPC), an effort catalyzed through the vision of the 47th Vice President of the United States Joseph R. Biden, Jr. and the Cancer Moonshot.

NCG 4.0: the network of cancer genes in the era of massive mutational screenings of cancer genomes

PubMed Central

An, Omer; Pendino, Vera; D’Antonio, Matteo; Ratti, Emanuele; Gentilini, Marco; Ciccarelli, Francesca D.

2014-01-01

NCG 4.0 is the latest update of the Network of Cancer Genes, a web-based repository of systems-level properties of cancer genes. In its current version, the database collects information on 537 known (i.e. experimentally supported) and 1463 candidate (i.e. inferred using statistical methods) cancer genes. Candidate cancer genes derive from the manual revision of 67 original publications describing the mutational screening of 3460 human exomes and genomes in 23 different cancer types. For all 2000 cancer genes, duplicability, evolutionary origin, expression, functional annotation, interaction network with other human proteins and with microRNAs are reported. In addition to providing a substantial update of cancer-related information, NCG 4.0 also introduces two new features. The first is the annotation of possible false-positive cancer drivers, defined as candidate cancer genes inferred from large-scale screenings whose association with cancer is likely to be spurious. The second is the description of the systems-level properties of 64 human microRNAs that are causally involved in cancer progression (oncomiRs). Owing to the manual revision of all information, NCG 4.0 constitutes a complete and reliable resource on human coding and non-coding genes whose deregulation drives cancer onset and/or progression. NCG 4.0 can also be downloaded as a free application for Android smart phones. Database URL: http://bio.ieo.eu/ncg/ PMID:24608173

Time, trust, and transparency: Lessons learned from collecting blood biospecimens for cancer research from the Asian American community.

PubMed

Dang, Julie H T; Chen, Moon S

2018-04-01

Biospecimens from racially diverse groups are needed to advance cancer research. The Asian American Cancer Education Study was developed to increase the number and proportion of blood biospecimen donations from Asian Americans for cancer research. The authors' targeted approach included 2 types of community engagement, in-reach (within institution to Asian American patients with cancer) and outreach (external to institution to the general Asian American community). Participants received in-language biospecimen education followed by the opportunity to donate blood biospecimens. Outreach participants donated through our community biospecimen blood drives, and in-reach participants consented to donating an extra tube of blood during their routine blood draws as a patient. Donated blood biospecimens were spun down to serum and plasma to be stored in a biorepository or were sent to the laboratory to test for cancer-related risk factors. Three hundred eighty-eight Asian Americans donated 1127 blood biospecimens for cancer research. Four hundred twenty tubes of plasma and serum are currently being stored at the cancer center's biorepository, 39 tubes have been used for cancer genomic research, and 668 tubes were used to characterize cancer-related risk factors. Building upon the past decade of the National Cancer Institute-funded Asian American Network for Cancer Awareness, Research, and Training's foundation of trust and service among Asian Americans, researchers were able to leverage relationships not only to introduce the idea of biospecimen contribution to the community but to also exceed expectations with regard to the quantity of blood biospecimens collected from Asian Americans. Cancer 2018;124:1614-21. © 2018 American Cancer Society. © 2018 American Cancer Society.

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

PubMed

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).

MET network in PubMed: a text-mined network visualization and curation system.

PubMed

Dai, Hong-Jie; Su, Chu-Hsien; Lai, Po-Ting; Huang, Ming-Siang; Jonnagaddala, Jitendra; Rose Jue, Toni; Rao, Shruti; Chou, Hui-Jou; Milacic, Marija; Singh, Onkar; Syed-Abdul, Shabbir; Hsu, Wen-Lian

2016-01-01

Metastasis is the dissemination of a cancer/tumor from one organ to another, and it is the most dangerous stage during cancer progression, causing more than 90% of cancer deaths. Improving the understanding of the complicated cellular mechanisms underlying metastasis requires investigations of the signaling pathways. To this end, we developed a METastasis (MET) network visualization and curation tool to assist metastasis researchers retrieve network information of interest while browsing through the large volume of studies in PubMed. MET can recognize relations among genes, cancers, tissues and organs of metastasis mentioned in the literature through text-mining techniques, and then produce a visualization of all mined relations in a metastasis network. To facilitate the curation process, MET is developed as a browser extension that allows curators to review and edit concepts and relations related to metastasis directly in PubMed. PubMed users can also view the metastatic networks integrated from the large collection of research papers directly through MET. For the BioCreative 2015 interactive track (IAT), a curation task was proposed to curate metastatic networks among PubMed abstracts. Six curators participated in the proposed task and a post-IAT task, curating 963 unique metastatic relations from 174 PubMed abstracts using MET.Database URL: http://btm.tmu.edu.tw/metastasisway. © The Author(s) 2016. Published by Oxford University Press.

About the Prostate and Urologic Cancer Research Group | Division of Cancer Prevention

Cancer.gov

The Prostate and Urologic Cancer Research Group conducts and supports research on prostate and bladder cancers, and new approaches to clinical prevention studies including cancer immunoprevention. The group develops, implements and monitors research efforts in chemoprevention, nutrition, genetic, and immunologic interventions, screening, early detection and other prevention

A research on the application of software defined networking in satellite network architecture

NASA Astrophysics Data System (ADS)

Song, Huan; Chen, Jinqiang; Cao, Suzhi; Cui, Dandan; Li, Tong; Su, Yuxing

2017-10-01

Software defined network is a new type of network architecture, which decouples control plane and data plane of traditional network, has the feature of flexible configurations and is a direction of the next generation terrestrial Internet development. Satellite network is an important part of the space-ground integrated information network, while the traditional satellite network has the disadvantages of difficult network topology maintenance and slow configuration. The application of SDN technology in satellite network can solve these problems that traditional satellite network faces. At present, the research on the application of SDN technology in satellite network is still in the stage of preliminary study. In this paper, we start with introducing the SDN technology and satellite network architecture. Then we mainly introduce software defined satellite network architecture, as well as the comparison of different software defined satellite network architecture and satellite network virtualization. Finally, the present research status and development trend of SDN technology in satellite network are analyzed.

Single cell network profiling assay in bladder cancer.

PubMed

Covey, Todd M; Vira, Manish A; Westfall, Matt; Gulrajani, Michael; Cholankeril, Michelle; Okhunov, Zhamshid; Levey, Helen R; Marimpietri, Carol; Hawtin, Rachael; Fields, Scott Z; Cesano, Alessandra

2013-04-01

The aim of this study was to assess the feasibility of applying the single cell network profiling (SCNP) assay to the examination of signaling networks in epithelial cancer cells, using bladder washings from 29 bladder cancer (BC) and 15 nonbladder cancer (NC) subjects. This report describes the methods we developed to detect rare epithelial cells (within the cells we collected from bladder washings), distinguish cancer cells from normal epithelial cells, and reproducibly quantify signaling within these low frequency cancer cells. Specifically, antibodies against CD45, cytokeratin, EpCAM, and cleaved-PARP (cPARP) were used to differentiate nonapoptotic epithelial cells from leukocytes, while measurements of DNA content to determine aneuploidy (DAPI stain) allowed for distinction between tumor and normal epithelial cells. Signaling activity in the PI3K and MAPK pathways was assessed by measuring intracellular levels of p-AKT and p-ERK at baseline and in response to pathway modulation; 66% (N = 19) of BC samples and 27% (N = 4) of NC samples met the "evaluable" criteria, i.e., at least 400,000 total cells available upon sample receipt with >2% of cells showing an epithelial phenotype. The majority of epithelial cells detected in BC samples were nonapoptotic and all signaling data were generated from identified cPARP negative cells. In four of 19 BC samples but in none of the NC specimens, SCNP assay identified epithelial cancer cells with a quantifiable increase in epidermal growth factor-induced p-AKT and p-ERK levels. Furthermore, preincubation with the PI3K inhibitor GDC-0941 reduced or completely inhibited basal and epidermal growth factor-induced p-AKT but, as expected, had no effect on p-ERK levels. This study demonstrates the feasibility of applying SCNP assay using multiparametric flow cytometry to the functional characterization of rare, bladder cancer cells collected from bladder washing. Following assay standardization, this method could potentially serve

Use of National Comprehensive Cancer Network and Other Guidelines and Biomarkers for Colorectal Cancer Screening

PubMed Central

Williams, Christina D.; Grady, William M.; Zullig, Leah L.

2016-01-01

Colorectal cancer (CRC) remains a common cancer and significant public health burden. CRC-related mortality is declining, in part due to the early detection of CRC through robust screening. The National Comprehensive Cancer Network (NCCN) has established CRC screening guidelines to aid healthcare providers in making appropriate recommendations for screening according to a patient’s risk of developing CRC. The purpose of this review is to describe the evolution of CRC screening guidelines for average risk individuals, discuss the role of NCCN CRC screening guidelines in cancer prevention, and comment on the current and emerging use of biomarkers for CRC screening. PMID:27799515

Prostate Cancer Research Training Program

DTIC Science & Technology

2017-09-01

Award Number: W81XWH-16-1-0549 TITLE: Prostate Cancer Research Training Program PRINCIPAL INVESTIGATOR: David M. Lubaroff, PhD CONTRACTING...ORGANIZATION: University of Iowa Iowa City, IA 52242 REPORT DATE: September 2017 TYPE OF REPORT: Annual PREPARED FOR: U.S. Army Medical Research ...Prostate Cancer Research Training Program 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-16-1-0549 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S

Staff Clinicians | Center for Cancer Research

Cancer.gov

The Neuro-Oncology Branch (NOB), Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH) is seeking staff clinicians to provide high-quality patient care for individuals with primary central nervous system (CNS) malignancies.  The NOB is comprised of a multidisciplinary team of physicians, healthcare providers, and scientists who are dedicated to developing new therapies and improving outcomes for patients with primary brain and spinal cord tumors. The NOB is one of the first trans-institutional initiatives at the National Institutes of Health. The Branch is focused on developing an integrated clinical, translational, and basic research program that engages the strengths and resources of the National Cancer Institutes (NCI) and the National Institutes of Neurological Disorders and Stroke (NINDS) for the purpose of developing novel experimental therapeutics for individuals with primary central nervous system (CNS) malignancies. About NCI's Center for Cancer Research The Center for Cancer Research (CCR) is the intramural research component of the National Cancer Institute (NCI).  CCR’s enabling infrastructure facilitates clinical studies at the NIH Clinical Center, the world’s largest dedicated clinical research complex; provides extensive opportunities for collaboration; and allows scientists and clinicians to undertake high-risk, high-impact laboratory- and clinic-based investigations.  Investigators are supported by a wide array of intellectual, technological, and research resources, including surgical and pathology facilities, animal facilities, and dedicated, high-quality technology cores in areas such as imaging/microscopy, chemistry/purification, mass spectrometry, flow cytometry, genomics/DNA sequencing, transgenics and knock-out mice, arrays/molecular profiling, and human genetics/bioinformatics.  For an overview of CCR, please visit http://ccr.cancer.gov/.

Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research.

PubMed

Jinawath, Natini; Bunbanjerdsuk, Sacarin; Chayanupatkul, Maneerat; Ngamphaiboon, Nuttapong; Asavapanumas, Nithi; Svasti, Jisnuson; Charoensawan, Varodom

2016-11-22

With the wealth of data accumulated from completely sequenced genomes and other high-throughput experiments, global studies of biological systems, by simultaneously investigating multiple biological entities (e.g. genes, transcripts, proteins), has become a routine. Network representation is frequently used to capture the presence of these molecules as well as their relationship. Network biology has been widely used in molecular biology and genetics, where several network properties have been shown to be functionally important. Here, we discuss how such methodology can be useful to translational biomedical research, where scientists traditionally focus on one or a small set of genes, diseases, and drug candidates at any one time. We first give an overview of network representation frequently used in biology: what nodes and edges represent, and review its application in preclinical research to date. Using cancer as an example, we review how network biology can facilitate system-wide approaches to identify targeted small molecule inhibitors. These types of inhibitors have the potential to be more specific, resulting in high efficacy treatments with less side effects, compared to the conventional treatments such as chemotherapy. Global analysis may provide better insight into the overall picture of human diseases, as well as identify previously overlooked problems, leading to rapid advances in medicine. From the clinicians' point of view, it is necessary to bridge the gap between theoretical network biology and practical biomedical research, in order to improve the diagnosis, prevention, and treatment of the world's major diseases.

Secretary | Center for Cancer Research

Cancer.gov

We are looking for a pleasant, organized, dependable person to serve as a full-time secretary in the Basic Science Program (BSP) at the Frederick National Laboratory for Cancer Research (FNCLR).  The BSP provides procurement and logistical support to the laboratories of the Center for Cancer Research.  Tasks include high volume procurement (blanket orders, purchase requests,

Administrative Assistant | Center for Cancer Research

Cancer.gov

Be part of our mission to support research against cancer. We are looking for an organized, detail oriented, dependable person with strong interpersonal skills to serve as an administrative assistant at the National Cancer Institute (NCI) on the campus of NIH. Work supports the implementation of the NIH Genomic Data Sharing Policy (GDS) in the NCI’s Center for Cancer Research

Prostate Cancer Stem-Like Cells | Center for Cancer Research

Cancer.gov

Prostate cancer is the third leading cause of cancer-related death among men, killing an estimated 27,000 men each year in the United States. Men with advanced prostate cancer often become resistant to conventional therapies. Many researchers speculate that the emergence of resistance is due to the presence of cancer stem cells, which are believed to be a small subpopulation

An overview of cancer research in South African academic and research institutions, 2013 - 2014.

PubMed

Moodley, Jennifer; Stefan, D Cristina; Sewram, Vikash; Ruff, Paul; Freeman, Melvyn; Asante-Shongwe, Kwanele

2016-05-10

Cancer is emerging as a critical public health problem in South Africa (SA). Recognising the importance of research in addressing the cancer burden, the Ministerial Advisory Committee on the Prevention and Control of Cancer (MACC) research working group undertook a review of the current cancer research landscape in SA and related this to the cancer burden. Academic and research institutions in SA were contacted to provide information on the titles of all current and recently completed (2013/2014) cancer research projects. Three MACC research working group members used the project titles to independently classify the projects by type of research (basic, clinical and public health - projects could be classified in more than one category) and disease site. A more detailed classification of projects addressing the five most common cancers diagnosed in males and females in SA was conducted using an adapted Common Scientific Outline (CSO) categorisation. Information was available on 556 cancer research projects. Overall, 301 projects were classified as clinical, 254 as basic science and 71 as public health research. The most common cancers being researched were cancers of the breast (n=95 projects) and cervix (n=43), leukaemia (n=36), non-Hodgkin's lymphoma (n=35) and lung cancer (n=23). Classification of the five most common cancers in males and females in SA, using the adapted CSO categories, showed that the majority of projects related to treatment, with relatively few projects on prevention, survivorship and patient perspectives. Our findings established that there is a dearth of public health cancer research in SA.

Background | Office of Cancer Clinical Proteomics Research

Cancer.gov

The term "proteomics" refers to a large-scale comprehensive study of a specific proteome resulting from its genome, including abundances of proteins, their variations and modifications, and interacting partners and networks in order to understand cellular processes involved.  Similarly, “Cancer proteomics” refers to comprehensive analyses of proteins and their derivatives translated from a specific cancer genome using a human biospecimen or a preclinical model (e.g., cultured cell or animal model).

Uses of cancer registries for public health and clinical research in Europe: Results of the European Network of Cancer Registries survey among 161 population-based cancer registries during 2010-2012.

PubMed

Siesling, S; Louwman, W J; Kwast, A; van den Hurk, C; O'Callaghan, M; Rosso, S; Zanetti, R; Storm, H; Comber, H; Steliarova-Foucher, E; Coebergh, J W

2015-06-01

To provide insight into cancer registration coverage, data access and use in Europe. This contributes to data and infrastructure harmonisation and will foster a more prominent role of cancer registries (CRs) within public health, clinical policy and cancer research, whether within or outside the European Research Area. During 2010-12 an extensive survey of cancer registration practices and data use was conducted among 161 population-based CRs across Europe. Responding registries (66%) operated in 33 countries, including 23 with national coverage. Population-based oncological surveillance started during the 1940-50s in the northwest of Europe and from the 1970s to 1990s in other regions. The European Union (EU) protection regulations affected data access, especially in Germany and France, but less in the Netherlands or Belgium. Regular reports were produced by CRs on incidence rates (95%), survival (60%) and stage for selected tumours (80%). Evaluation of cancer control and quality of care remained modest except in a few dedicated CRs. Variables evaluated were support of clinical audits, monitoring adherence to clinical guidelines, improvement of cancer care and evaluation of mass cancer screening. Evaluation of diagnostic imaging tools was only occasional. Most population-based CRs are well equipped for strengthening cancer surveillance across Europe. Data quality and intensity of use depend on the role the cancer registry plays in the politico, oncomedical and public health setting within the country. Standard registration methodology could therefore not be translated to equivalent advances in cancer prevention and mass screening, quality of care, translational research of prognosis and survivorship across Europe. Further European collaboration remains essential to ensure access to data and comparability of the results. Copyright © 2014 Elsevier Ltd. All rights reserved.

Connecting the Dots: Understanding the Flow of Research Knowledge within a Research Brokering Network

ERIC Educational Resources Information Center

Rodway, Joelle

2015-01-01

Networks are frequently cited as an important knowledge mobilization strategy; however, there is little empirical research that considers how they connect research and practice. Taking a social network perspective, I explore how central office personnel find, understand and share research knowledge within a research brokering network. This mixed…

Disparities in breast cancer care and research: report from a Breast Cancer Research Foundation sponsored workshop, 9-10 October 2014.

PubMed

Canin, Beverly; Freund, Karen M; Ganz, Patricia A; Hershman, Dawn L; Paskett, Electra D

2015-01-01

The purpose of this workshop was to bring together diverse stakeholders from the breast cancer research community to discuss critical issues related to disparities in breast cancer care and to identify potential strategies for reducing disparities and inequities in care through research. The workshop format included a series of formal content presentations, participation in break out groups that focused on specific topics highlighted in the content presentations, reporting back of findings and a facilitated discussion that focused on shaping a research agenda. The workshop members concluded that numerous groups of women are at increased risk for disparities in breast cancer care: many patients and survivors suffer disproportionately from inadequate access to high-quality diagnosis and treatment, resulting in more frequent and severe adverse outcomes from the disease. Research on breast cancer disparities provides a major opportunity for reducing the burden of breast cancer. Thus, it is important for the Breast Cancer Research Foundation and other research funders to consider how to best promote research focused on ensuring breast cancer health equity.

Distinction of cervical cancer biopsies by use of infrared microspectroscopy and probabilistic neural networks

NASA Astrophysics Data System (ADS)

Podshyvalov, A.; Sahu, R. K.; Mark, S.; Kantarovich, K.; Guterman, H.; Goldstein, J.; Jagannathan, R.; Argov, S.; Mordechai, S.

2005-06-01

Fourier-transform infrared spectroscopy has shown alterations of spectral characteristics of cells and tissues as a result of carcinogenesis. The research reported here focuses on the diagnosis of cancer in formalin-fixed biopsied tissue for which immunochemistry is not possible and when PAP-smear results are to be confirmed. The data from two groups of patients (a control group and a group of patients diagnosed with cervical cancer) were analyzed. It was found that the glucose/phosphate ratio decreases (by 23-49%) and the RNA/DNA ratio increases (by 38-150%) in carcinogenic compared with normal tissue. Fourier-transform microspectroscopy was used to examine these tissues. This type of study in larger populations may help to set standards or classes with which to use treated biopsied tissue to predict the possibility of cancer. Probabilistic neural networks and statistical tests as parts of these biopsies predict the possibility of cancer with a high degree of accuracy (>95%).

About DCP | Division of Cancer Prevention

Cancer.gov

The Division of Cancer Prevention (DCP) is the division of the National Cancer Institute (NCI) devoted to cancer prevention research. DCP provides funding and administrative support to clinical and laboratory researchers, community and multidisciplinary teams, and collaborative scientific networks. |

Honoring Pioneers in Breast Cancer Research

MedlinePlus

... Home Current Issue Past Issues Honoring Pioneers in Breast Cancer Research Past Issues / Spring 2007 Table of Contents ... the Distinguished Medical Service Award for their pioneering breast cancer research. Photo courtesy of Bill Branson, NIH In ...

Cancer Trends: Influencing Care and Research Priorities

Cancer.gov

Many of the trends being seen in cancer are changing how we view cancer and how we address it, from prompting research to identify the underlying causes of cancers increasing in incidence to informing research on treatment and prevention.

About the Gastrointestinal and Other Cancers Research Group | Division of Cancer Prevention

Cancer.gov

The Gastrointestinal and Other Cancers Research Group conducts and supports prevention and early detection research on colorectal, esophageal, liver, pancreatic, and hematolymphoid cancers, as well as new approaches to clinical prevention studies including cancer immunoprevention. |

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

PubMed

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

Topological Organization of Metabolic Brain Networks in Pre-Chemotherapy Cancer with Depression: A Resting-State PET Study

PubMed Central

An, Jianping; Chen, Xuejiao; Xie, Yuanwei; Zhao, Hui; Mao, Junfeng; Liang, Wangsheng; Ma, Xiangxing

2016-01-01

This study aimed to investigate the metabolic brain network and its relationship with depression symptoms using 18F-fluorodeoxyglucose positron emission tomography data in 78 pre-chemotherapy cancer patients with depression and 80 matched healthy subjects. Functional and structural imbalance or disruption of brain networks frequently occur following chemotherapy in cancer patients. However, few studies have focused on the topological organization of the metabolic brain network in cancer with depression, especially those without chemotherapy. The nodal and global parameters of the metabolic brain network were computed for cancer patients and healthy subjects. Significant decreases in metabolism were found in the frontal and temporal gyri in cancer patients compared with healthy subjects. Negative correlations between depression and metabolism were found predominantly in the inferior frontal and cuneus regions, whereas positive correlations were observed in several regions, primarily including the insula, hippocampus, amygdala, and middle temporal gyri. Furthermore, a higher clustering efficiency, longer path length, and fewer hubs were found in cancer patients compared with healthy subjects. The topological organization of the whole-brain metabolic networks may be disrupted in cancer. Finally, the present findings may provide a new avenue for exploring the neurobiological mechanism, which plays a key role in lessening the depression effects in pre-chemotherapy cancer patients. PMID:27832148

Topological Organization of Metabolic Brain Networks in Pre-Chemotherapy Cancer with Depression: A Resting-State PET Study.

PubMed

Fang, Lei; Yao, Zhijun; An, Jianping; Chen, Xuejiao; Xie, Yuanwei; Zhao, Hui; Mao, Junfeng; Liang, Wangsheng; Ma, Xiangxing

2016-01-01

This study aimed to investigate the metabolic brain network and its relationship with depression symptoms using 18F-fluorodeoxyglucose positron emission tomography data in 78 pre-chemotherapy cancer patients with depression and 80 matched healthy subjects. Functional and structural imbalance or disruption of brain networks frequently occur following chemotherapy in cancer patients. However, few studies have focused on the topological organization of the metabolic brain network in cancer with depression, especially those without chemotherapy. The nodal and global parameters of the metabolic brain network were computed for cancer patients and healthy subjects. Significant decreases in metabolism were found in the frontal and temporal gyri in cancer patients compared with healthy subjects. Negative correlations between depression and metabolism were found predominantly in the inferior frontal and cuneus regions, whereas positive correlations were observed in several regions, primarily including the insula, hippocampus, amygdala, and middle temporal gyri. Furthermore, a higher clustering efficiency, longer path length, and fewer hubs were found in cancer patients compared with healthy subjects. The topological organization of the whole-brain metabolic networks may be disrupted in cancer. Finally, the present findings may provide a new avenue for exploring the neurobiological mechanism, which plays a key role in lessening the depression effects in pre-chemotherapy cancer patients.

The Organization of European Cancer Institute Pathobiology Working Group and its support of European biobanking infrastructures for translational cancer research.

PubMed

Riegman, Peter H J; de Jong, Bas W D; Llombart-Bosch, Antonio

2010-04-01

Today's translational cancer research increasingly depends on international multi-center studies. Biobanking infrastructure or comprehensive sample exchange platforms to enable networking of clinical cancer biobanks are instrumental to facilitate communication, uniform sample quality, and rules for exchange. The Organization of European Cancer Institutes (OECI) Pathobiology Working Group supports European biobanking infrastructure by maintaining the OECI-TuBaFrost exchange platform and organizing regular meetings. This platform originated from a European Commission project and is updated with knowledge from ongoing and new biobanking projects. This overview describes how European biobanking projects that have a large impact on clinical biobanking, including EuroBoNeT, SPIDIA, and BBMRI, contribute to the update of the OECI-TuBaFrost exchange platform. Combining the results of these European projects enabled the creation of an open (upon valid registration only) catalogue view of cancer biobanks and their available samples to initiate research projects. In addition, closed environments supporting active projects could be developed together with the latest views on quality, access rules, ethics, and law. With these contributions, the OECI Pathobiology Working Group contributes to and stimulates a professional attitude within biobanks at the European comprehensive cancer centers. Improving the fundamentals of cancer sample exchange in Europe stimulates the performance of large multi-center studies, resulting in experiments with the desired statistical significance outcome. With this approach, future innovation in cancer patient care can be realized faster and more reliably.

Deregulation of an imprinted gene network in prostate cancer

PubMed Central

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

2014-01-01

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. PMID:24513574

Deregulation of an imprinted gene network in prostate cancer.

PubMed

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.

CCR Interns | Center for Cancer Research

Cancer.gov

The Cancer Research Interns (CRI) Summer Program was inaugurated in 2004 to provide an open door for students looking for an initial training opportunity. The goal is to enhance diversity within the CCR (Center for Cancer Research) training program and we have placed 338 students from 2004 to 2017, in labs and branches across the division.  The CCR and the Center for Cancer

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

A postdoctoral research position is available in the laboratory of Dr. Natasha Caplen in the Genetics Branch, National Cancer Institute, Center for Cancer Research. Dr. Caplen’s Laboratory conducts multidisciplinary and interdisciplinary research that uses RNAi and other DNA or RNA-based functional genomic technologies to interrogate specific aspects of the genetic,

Basic Research and Progress against Cancer

Cancer.gov

An infographic about the importance of basic research for making progress against cancer. The graphic shows the research milestones that led to the development and approval of crizotinib (Xalkori®) to treat certain non-small cell lung cancers.

Breast cancer detection via Hu moment invariant and feedforward neural network

NASA Astrophysics Data System (ADS)

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.

Singapore Cancer Network (SCAN) Guidelines for Referral for Genetic Evaluation of Common Hereditary Cancer Syndromes.

PubMed

2015-10-01

The SCAN cancer genetics workgroup aimed to develop Singapore Cancer Network (SCAN) clinical practice guidelines for referral for genetic evaluation of common hereditary cancer syndromes. The workgroup utilised a modified ADAPTE process to calibrate high quality international evidence-based clinical practice guidelines to our local setting. To formulate referral guidelines for the 3 most commonly encountered hereditary cancer syndromes to guide healthcare providers in Singapore who care for cancer patients and/or their family members, 7, 5, and 3 sets of international guidelines respectively for hereditary breast and ovarian cancer (HBOC) syndrome, Lynch syndrome (LS), and familial adenomatous polyposis (FAP) were evaluated. For each syndrome, the most applicable one was selected, with modifications made such that they would be appropriate to the local context. These adapted guidelines form the SCAN Guidelines 2015 for referral for genetic evaluation of common hereditary cancer syndromes.

Identification of Potential Prostate Cancer-Related Pseudogenes Based on Competitive Endogenous RNA Network Hypothesis.

PubMed

Jiang, Tao; Guo, Junjie; Hu, Zhongchun; Zhao, Ming; Gu, Zhenggang; Miao, Shu

2018-06-20

BACKGROUND Long noncoding RNAs (lncRNAs) have been revealed to function as competing endogenous RNAs (ceRNAs), which can seclude the common microRNAs (miRNAs) and hence prevent the miRNAs from binding to their ancestral gene. Nonetheless, the role of lncRNA-mediated ceRNAs in prostate cancer has not yet been elucidated. MATERIAL AND METHODS Using The Cancer Genome Atlas (TCGA) database, lncRNA, miRNA, and mRNA profiles from 499 prostate cancer tissues and 52 normal prostate tissues were analyzed with the R package "DESeq" to identify the differentially expressed RNAs. GO and KEGG pathway analyses were performed using "DAVID6.8" and R packages "Clusterprofile." The ceRNA network in prostate cancer was constructed using miRDB, miRTarBase, and TargetScan databases. Survival analysis was performed with Kaplan-Meier analysis. RESULTS A total of 376 lncRNAs, 33 miRNAs, and 687 mRNAs were identified as significant factors in tumorigenesis. Based on the hypothesis that the ceRNA network (lncRNA-miRNA-mRNA regulatory axis) is involved in prostate cancer and forms competitive interrelations between miRNA and mRNA or lncRNA, we constructed a ceRNA network that included 23 lncRNAs, 6 miRNAs, and 2 mRNAs that were differentially expressed in prostate cancer. Only 3 lncRNAs (LINC00308, LINC00355, and OSTN-AS1) had a significant association with survival (P<0.05). The 3 prostate cancer-specific lncRNA were validated in prostate cancer cell lines PC3 and DU145 using qRT-PCR. CONCLUSIONS We demonstrated the differential lncRNA expression profiles in prostate cancer, which provides new insights for future studies of the ceRNA network and its regulatory mechanisms in prostate cancer.

The Nordic Health Promotion Research Network (NHPRN).

PubMed

Ringsberg, Karin C

2015-08-01

The Nordic Health Promotion Research Network (NHPRN) was established in 2007 at the Nordic School of Public Health (NHV). This article aims to describe the foundation of the NHPRN, the development and the present status of the work of NHPRN. The NHPRN consists of about 50 senior and junior researchers from all Nordic countries. It is a working network that aims to develop the theoretical understanding of health promotion, to create research cooperation in health promotion from a Nordic perspective and to extend the scope of health promotion through education. Network members meet biannually to discuss and further develop research within the field and are also responsible for the Nordic conference on Health Promotion, organized every 3 years. The NHV hosted the network between 2007 and 2014; and the World Health Organisation (WHO) will assume this role in 2015. © 2015 the Nordic Societies of Public Health.

What's New in Nasopharyngeal Cancer Research and Treatment?

MedlinePlus

... and Treatment? Nasopharyngeal Cancer About Nasopharyngeal Cancer What's New in Nasopharyngeal Cancer Research and Treatment? Research into ... the world where this cancer is common. Treatment New surgical techniques Advances in the field of skull ...

Applying Social Network Analysis to Identify the Social Support Needs of Adolescent and Young Adult Cancer Patients and Survivors.

PubMed

Koltai, Kolina; Walsh, Casey; Jones, Barbara; Berkelaar, Brenda L

2018-04-01

This article examines how theoretical and clinical applications of social network analysis (SNA) can inform opportunities for innovation and advancement of social support programming for adolescent and young adult (AYA) cancer patients and survivors. SNA can help address potential barriers and challenges to initiating and sustaining AYA peer support by helping to identify the diverse psychosocial needs among individuals in the AYA age range; find strategic ways to support and connect AYAs at different phases of the cancer trajectory with resources and services; and increase awareness of psychosocial resources and referrals from healthcare providers. Network perspectives on homophily, proximity, and evolution provide a foundational basis to explore the utility of SNA in AYA clinical care and research initiatives. The uniqueness of the AYA oncology community can also provide insight into extending and developing current SNA theories. Using SNA in AYA psychosocial cancer research has the potential to create new ideas and pathways for supporting AYAs across the continuum of care, while also extending theories of SNA. SNA may also prove to be a useful tool for examining social support resources for AYAs with various chronic health conditions and other like groups.

How to research cancer

MedlinePlus

... medlineplus.gov/ency/patientinstructions/000927.htm How to research cancer To use the sharing features on this ... to government sources and medical associations. They provide research-based, up-to-date information about all types ...

Cancer Genetics and Signaling | Center for Cancer Research

Cancer.gov

The Cancer, Genetics, and Signaling (CGS) Group at the National Cancer Institute at Frederick  offers a competitive postdoctoral training and mentoring program focusing on molecular and genetic aspects of cancer. The CGS Fellows Program is designed to attract and train exceptional postdoctoral fellows interested in pursuing independent research career tracks. CGS Fellows participate in a structured mentoring program designed for scientific and career development and transition to independent positions.

Automation of Technology for Cancer Research.

PubMed

van der Ent, Wietske; Veneman, Wouter J; Groenewoud, Arwin; Chen, Lanpeng; Tulotta, Claudia; Hogendoorn, Pancras C W; Spaink, Herman P; Snaar-Jagalska, B Ewa

2016-01-01

Zebrafish embryos can be obtained for research purposes in large numbers at low cost and embryos develop externally in limited space, making them highly suitable for high-throughput cancer studies and drug screens. Non-invasive live imaging of various processes within the larvae is possible due to their transparency during development, and a multitude of available fluorescent transgenic reporter lines.To perform high-throughput studies, handling large amounts of embryos and larvae is required. With such high number of individuals, even minute tasks may become time-consuming and arduous. In this chapter, an overview is given of the developments in the automation of various steps of large scale zebrafish cancer research for discovering important cancer pathways and drugs for the treatment of human disease. The focus lies on various tools developed for cancer cell implantation, embryo handling and sorting, microfluidic systems for imaging and drug treatment, and image acquisition and analysis. Examples will be given of employment of these technologies within the fields of toxicology research and cancer research.

Postdoctoral Fellows | Center for Cancer Research

Cancer.gov

The Oncogenomics section of the Genetics Branch is a multidisciplinary and interdisciplinary translational research programmatic effort with the goal of utilizing genomics to develop novel immunotherapies for cancer. Our group is applying high throughput applied genomics methods including single cell RNAseq, single cell TCR sequencing, DNA sequencing, CRISPR/Cas9, bioinformatics combined with T cell based therapeutics to identify and develop novel immunotherapeutics for human cancer. We work with other investigators within the intramural program as well as industrial and pharmaceutical partners to rapidly translate our findings to the clinic. The program takes advantage of the uniqueness of the National Cancer Institute, (NCI), Center for Cancer Research (CCR) intramural program in that it spans high-risk basic discovery research in immunology, genomics and tumor biology, through preclinical translational research, to paradigm-shifting clinical trials. The position is available immediately. The appointment duration is up to 5 years. Stipends are commensurate with education and experience. Additional information can be found on Dr. Khan’s profile page: https://ccr.cancer.gov/Genetics-Branch/javed-khan

No longer simply a Practice-based Research Network (PBRN) health improvement networks.

PubMed

Williams, Robert L; Rhyne, Robert L

2011-01-01

While primary care Practice-based Research Networks are best known for their original, research purpose, evidence accumulating over the last several years is demonstrating broader values of these collaborations. Studies have demonstrated their role in quality improvement and practice change, in continuing professional education, in clinician retention in medically underserved areas, and in facilitating transition of primary care organization. A role in informing and facilitating health policy development is also suggested. Taking into account this more robust potential, we propose a new title, the Health Improvement Network, and a new vision for Practice-based Research Networks.

Bioprinting for cancer research.

PubMed

Knowlton, Stephanie; Onal, Sevgi; Yu, Chu Hsiang; Zhao, Jean J; Tasoglu, Savas

2015-09-01

Bioprinting offers the ability to create highly complex 3D architectures with living cells. This cutting-edge technique has significantly gained popularity and applicability in several fields. Bioprinting methods have been developed to effectively and rapidly pattern living cells, biological macromolecules, and biomaterials. These technologies hold great potential for applications in cancer research. Bioprinted cancer models represent a significant improvement over previous 2D models by mimicking 3D complexity and facilitating physiologically relevant cell-cell and cell-matrix interactions. Here we review bioprinting methods based on inkjet, microextrusion, and laser technologies and compare 3D cancer models with 2D cancer models. We discuss bioprinted models that mimic the tumor microenvironment, providing a platform for deeper understanding of cancer pathology, anticancer drug screening, and cancer treatment development. Copyright © 2015 Elsevier Ltd. All rights reserved.

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

We are seeking a postdoctoral researcher to study alterations in mitochondria metabolism during tumor formation. Our lab is within the Center for Cancer Research (CCR) of the National Cancer Institute (NCI), which is embedded in the vibrant research community of the NIH’s main campus in Bethesda, Maryland. Our major goal is to identify novel molecular mechanisms that control

Differential receipt of sentinel lymph node biopsy within practice-based research networks

PubMed Central

Meyer, Anne-Marie; Reeder-Hayes, Katherine E.; Liu, Huan; Wheeler, Stephanie B.; Penn, Dolly; Weiner, Bryan J.; Carpenter, William R.

2013-01-01

Background Provider-based research networks (PBRNs) are promising for accelerating not only research, but also dissemination of research-based evidence into broader community practice. Sentinel lymph node biopsy (SLNB) is an innovation in breast cancer care associated with equivalent survival and lower morbidity, as compared to standard axillary lymph node dissection. We examined the diffusion of SLNB into practice and whether affiliation with the Community Clinical Oncology Program (CCOP), a cancer-focused PBRN, was associated with more rapid uptake of SLNB. Research Design Surveillance Epidemiology and End Results(SEER)-Medicare data were used to study women diagnosed with stage I or II breast cancer in the years 2000 to 2005 and undergoing breast conserving surgery with axillary staging (n=6,226). The primary outcome was undergoing SLNB. CCOP affiliation of the surgical physician was ascertained from NCI records. Multivariable generalized linear modeling with generalized estimating equations was used to measure association between CCOP exposure and undergoing SLNB, controlling for potential confounders. Results Women treated by a CCOP physician had significantly higher odds of receiving SLNB compared to women treated by a non-CCOP physician (OR 2.68; 95% CI 1.35, 5.34). The magnitude of this association was larger than that observed among patients treated by physicians operating in medical school-affiliated hospitals (OR 1.76; 95% CI 1.30–2.39). Conclusion Women treated by CCOP-affiliated physicians were more likely to undergo SLNB irrespective of the hospital’s medical school affiliation, suggesting that the CCOP PBRN may play a role in the rapid adoption of research-based innovation in community practice. PMID:23942221

Community pharmacist participation in a practice-based research network: a report from the Medication Safety Research Network of Indiana (Rx-SafeNet).

PubMed

Patel, Puja; Hemmeger, Heather; Kozak, Mary Ann; Gernant, Stephanie A; Snyder, Margie E

2015-01-01

To describe the experiences and opinions of pharmacists serving as site coordinators for the Medication Safety Research Network of Indiana (Rx-SafeNet). Retail chain, independent, and hospital/health system outpatient community pharmacies throughout Indiana, with a total of 127 pharmacy members represented by 26 site coordinators. Rx-SafeNet, a statewide practice-based research network (PBRN) formed in 2010 and administered by the Purdue University College of Pharmacy. Barriers and facilitators to participation in available research studies, confidence participating in research, and satisfaction with overall network communication. 22 of 26 site coordinators participated, resulting in an 85% response rate. Most (72.2%) of the respondents had received a doctor of pharmacy degree, and 13.6% had postgraduate year (PGY)1 residency training. The highest reported benefits of PBRN membership were an enhanced relationship with the Purdue University College of Pharmacy (81% agreed or strongly agreed) and enhanced professional development (80% agreed or strongly agreed). Time constraints were identified as the greatest potential barrier to network participation, reported by 62% of respondents. In addition, the majority (59%) of survey respondents identified no prior research experience. Last, respondents' confidence in performing research appeared to increase substantially after becoming network members, with 43% reporting a lack of confidence in engaging in research before joining the network compared with 90% reporting confidence after joining the network. In general, Rx-SafeNet site coordinators appeared to experience increased confidence in research engagement after joining the network. While respondents identified a number of benefits associated with network participation, concerns about potential time constraints remained a key barrier to participation. These findings will assist network leadership in identifying opportunities to positively increase member participation

Nebraska Prostate Cancer Research Program

DTIC Science & Technology

2012-05-01

Powell. (2012). Dioxin exposure enhances nuclear localization of androgen receptor. The 8th Annual National Symposium on Prostate Cancer by CCRTD...cholesterol. Mol . Cellu. Endo. 295:115-120. 2. Siegel, R., Naishadham, D., and Jemal, A. (2012). Cancer Statistics, 2012. CA Cancer J Clin 62: 10-29...Ul DIOXIN J!1XPOSURE EN CES NUCLEAR LOCALIZATION OF ANDROGEN RECEPTOR\\~f..aTayia Aaron, nd Joann Powell, Center for Cancer Research and Therapeutic

Scottish Stroke Research Network: the first three years.

PubMed

McCormick, K; Langhorne, P; Graham, F E J; McFarlane, C

2010-08-01

Research networks were introduced in the UK to facilitate and improve clinical research and stroke was seen as a priority topic for local research network development. The Scottish Stroke Research Network (SSRN) is one of 11 stroke research networks in the UK. In this article we review the progress of the Scottish Stroke Research Network in the three years since inception. Between 2006-2009 the number of active hospital research sites has increased from 10 to 22 expanding to involve 20 stroke research nurses. There was a corresponding 58% increase in recruitment of participants into stroke studies, from 376 in 2006/07 to 594 in 2008/09. The majority (17/20) of our current studies are interventional. Data from one of these, the CLOTs trial (Clots in Legs Or sTocking after Stroke), demonstrates that the annual recruitment in Scotland increased from a median of 94 (range 6-122) patients per year in the six years before the SSRN, to 140 (135-158) patients per year after SSRN involvement. We currently screen about 50% of Scottish stroke patients and approximately 5% of Scottish stroke patients are participating in research studies that we support. The SSRN has made good progress in the first three years. Increasing the recruitment of screened patients remains a challenge.

Networking health research in Britain: the post-war childhood leukaemia trials.

PubMed

Moscucci, Ornella; Herring, Rachel; Berridge, Virginia

2009-01-01

The treatment of childhood leukaemia is seen as a successful historical example of the operation of the randomized controlled trial and continues to inform contemporary policy making on such trials within health research. This article analyses the scientists' 'story of success' through historical research. It tells us about the organizational and professional structures of such research post-war in the United Kingdom, and examines the history of the cancer clinical trial through this particular example. The story reveals a more complex picture than the 'heroic' one, with key developments in the operation of post-war science, both in terms of its infrastructure and of its scientific networks, not least the rise of co-operative working among clinicians and the growing importance of statisticians in medical research and practice. It also underlines differences between the British and US approaches in which the role of one health system, the National Health Service, helped structure different, initially less intensive, patterns of response.

Stories in Networks and Networks in Stories: A Tri-Modal Model for Mixed-Methods Social Network Research on Teachers

ERIC Educational Resources Information Center

Baker-Doyle, Kira J.

2015-01-01

Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

Evolutionary Wavelet Neural Network ensembles for breast cancer and Parkinson's disease prediction.

PubMed

Khan, Maryam Mahsal; Mendes, Alexandre; Chalup, Stephan K

2018-01-01

Wavelet Neural Networks are a combination of neural networks and wavelets and have been mostly used in the area of time-series prediction and control. Recently, Evolutionary Wavelet Neural Networks have been employed to develop cancer prediction models. The present study proposes to use ensembles of Evolutionary Wavelet Neural Networks. The search for a high quality ensemble is directed by a fitness function that incorporates the accuracy of the classifiers both independently and as part of the ensemble itself. The ensemble approach is tested on three publicly available biomedical benchmark datasets, one on Breast Cancer and two on Parkinson's disease, using a 10-fold cross-validation strategy. Our experimental results show that, for the first dataset, the performance was similar to previous studies reported in literature. On the second dataset, the Evolutionary Wavelet Neural Network ensembles performed better than all previous methods. The third dataset is relatively new and this study is the first to report benchmark results.

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

PubMed

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.

VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data

PubMed Central

Jia, Peilin; Zhao, Zhongming

2014-01-01

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. PMID:24516372