PA-17-101 (Admin Supp)
Research on the Health of Women of Underrepresented, Understudied and Underreported Populations -
Multilevel Interventions in Cancer Care Delivery: Building from the Problem of Follow-up to Abnormal Screening Tests
An ORWH FY17 Administrative Supplement
Application Due Date: March 6, 2017
Expiration Date: March 7, 2017
All of Us Research Program Engagement Partners
Application Due Date: March 24, 2017
Expiration Date: March 25, 2017
Activities to Promote Technology Research Collaborations for Cancer Research
Application Due Dates: April 12, 2017; July 25, 2017; and December 12, 2017
Expiration Date: December 13, 2017
Application Due Dates: May 26, 2017; September 21, 2017
Expiration Date: September 22, 2017
Mechanisms of Disparities in Chronic Liver Diseases and Cancer
Application Due Dates: May 22, 2017, April 4, 2018, April 4, 2019
Expiration Date: April 5, 2019
Quantitative Imaging Tools and Methods for Cancer Therapy Response Assessment
Application Due Dates: May 9, 2017; September 12, 2017; January 9, 2018; May 9, 2018; September 12, 2018; January 9, 2019; May 9, 2019; September 12, 2019; January 9, 2020
Expiration Date: January 10, 2020
Request for Information on Processes for dbGaP Data Submission, Access, and Management
Comments due: April 7, 2017
|SeqSPACE Webinar Series: The Application of Next Generation Sequencing Technologies in Diverse Populations and Methods for Evaluating the Pathogenicity of Variants
March 9, 2017
American Association for Cancer Research Annual Meeting
April 1-5, 2017
Note: The AACR Molecular Epidemiology Working Group is accepting applications from molecular epidemiology consortia for meeting space. Applications will be accepted through March 24, 2017. View announcement
NIH Regional Seminar
May 3-5, 2017
New Orleans, LA
The 4th Ethical, Legal, and Social Implications Congress-Genomics and Society: Expanding the ELSI Universe
June 5-7, 2017
Workshop on Best Practices in Studies of Diet and the Intestinal Microbiome
June 13-14, 2017
Registration closes in May, or when attendance is at full capacity.
International Conference on Ambulatory Monitoring of Physical Activity and Movement
June 21-23, 2017
BD2K Guide to the Fundamentals of Data Science Webinar Series
Every Friday, 12:00-1:00 p.m. ET
|The Epidemiology and Genomics Research Program (EGRP) in the Division of Cancer Control and Population Sciences (DCCPS) funds research in human populations to understand the causes of cancer and related outcomes.
The Program fosters interdisciplinary collaborations, as well as the development and use of resources and technologies to advance cancer research and translation of this research, which serve as the basis for clinical and public health interventions.
Improving Genotype-Phenotype Predictions
The rate of generating genomic data is surpassing the research community's ability to understand and interpret the data. Realizing the full potential of genomic data requires powerful and well-characterized computational methods for deducing the disease-relevant phenotypic impact of genomic variants. However, the field currently lacks a consensus on the absolute and relative suitability of the various methods for prediction of the phenotypic impact of genomic variation.
One approach being used to address these needs is being performed by the Critical Assessment of Genome Interpretation (CAGI), supported by a U41 cooperative agreement grant, funded by the National Human Genome Research Institute (NHGRI) and the National Cancer Institute (NCI). CAGI conducts community experiments or challenges that evaluate computational methods for predicting phenotypic impacts of genomic variation. Participants are provided genetic data and make predictions of the resulting phenotype. These predictions are evaluated by independent assessors, and participants meet to discuss findings. Results from CAGI help the broader research community evaluate different approaches and determine the types of approaches that are most suitable to specific scientific questions.
Previous CAGI experiments have examined several disease phenotypes, including cancer. For example, previous cancer challenge questions included predicting:
How can you help?
- the clinical impact of BRCA variants (dataset provided by Robert Nussbaum, M.D., Chief Medical Officer, Invitae, and Professor, Department of Medicine, UCSF);
- how variants of p16 tumor suppressor protein affect cell proliferation (dataset provided by Silvio C. E. Tosatto, Ph.D., Full Professor in Bioinformatics, Department of Biomedical Sciences, Università degli Studi di Padova);
- the impact of various drug treatments on cancer cell lines (dataset provided by Joe W. Gray, Ph.D., Gordon Moore Endowed Chair, Department of Biomedical Engineering, Oregon Health and Science University); and
- estimating the probability that an individual would have a mutation within the RAD50 and CHEK2 genes, depending on cancer status (datasets provided by Sean Tavtigian, Ph.D.; Professor, Department of Oncological Sciences at the University of Utah).
|Leah Mechanic (right), Program Director in NCI's EGRP, discusses CAGI findings at the 2016 NCI Cohort Consortium with John Moult (left), Professor, Department of Cell Biology and Molecular Genetics, Institute for Bioscience and Biotechnology Research, University of Maryland
Currently, CAGI organizers are searching for data providers and collecting new unpublished genomic data with associated phenotype characteristics for use in CAGI. These datasets, including multi-omics data, can be of any scale--from single variants to whole genomes--and will relate genetic variations to experimental or clinical cancer consequences. The data must be unreleased (or unpublished), so that the CAGI participants can make truly "blind predictions," with no way to incorporate the correct results deliberately or inadvertently. During the prediction season, participating groups submit predictions based on the data provided. The prediction accuracy will be evaluated by assessors and the results will be revealed at a future CAGI conference. In order to protect the unpublished data that is shared with CAGI, all CAGI participants must agree to the
CAGI data use agreement
The CAGI organizers welcome ideas for contacts or recommendations for new CAGI challenge datasets. To contact CAGI organizers, please e-mail
New Resource Helps Researchers Choose the Best Measures for Childhood Obesity Studies
This month, the National Collaborative on Childhood Obesity Research (NCCOR) released four User Guides that supplement NCCOR's Measures Registry.
The Measures Registry - a free, online repository of scientific articles about measures - is widely recognized as a key resource that gives researchers and practitioners access to detailed information on measures in one location. Because the Measures Registry is such a comprehensive resource, it can be difficult for users to quickly find what they need among the large number of measures.
The User Guides were developed to enhance the Registry by helping researchers and practitioners choose appropriate measures for their projects. This effort was led by staff from the Division of Cancer Control and Population Sciences (DCCPS), including EGRP staff members. Each guide was written by a team of leading experts and reviewed by expert panels in Nutrition and Physical Activity. These resources are meant to be used for expert researchers, graduate students, or practitioners who may be using nutrition or physical activity measures for the first time.
The ultimate goal of the guides is to encourage consistent use of high-quality, comparable measures and research methods across childhood obesity prevention research and evaluation efforts focused on diet and physical activity.
- Provide an overview of measurement,
- Describe general principles of measurement selection,
- Present case studies that walk researchers through the process of using the Measures Registry to select appropriate measures,
- Direct researchers to additional resources and sources of useful information.
The Measures Registry User Guides are available on the NCCOR website as easy-to-read webpages and downloadable PDFs.
Are you an NIH Principal Investigator (PI) who needs to make a change to your scientific project or budget for your grant? Does a new publication make you want to change your study from examining genotyping to doing methylation of specific genes? Would you like to add a foreign site to your study? These types of changes may require prior approval from NCI.
- Change in scope of the application. An example of change in scope is a change in the specific aims as approved at the time of award. More details regarding the definition of change in scope may be found at 126.96.36.199 Change in Scope.
- Transfer of a grant from one institution to another.
- Change of grantee institution status (e.g., change in the institution name or a merger between institutions).
- Change of PI, change from single PI to multiple PI, or removal of a PI from a multiple-PI award.
- Change in status of key personnel listed on the Notice of Award.
- Reduction of PI effort by 25 percent or more from what was approved in the initial grant application.
- Addition of new foreign site or foreign sub-award.
- Deviation from terms of award or restrictions reflected in the Notice of Award.
- Carryover of unobligated balances if not authorized on the Notice of Award (e.g., in U01s).
- Late no-cost extension requests or requests beyond 12 months after the end of the grant period.
- Significant re-budgeting of the grant. Significant re-budgeting occurs when expenditures in a single direct cost budget category deviate (increase or decrease) from the categorical commitment level established for the budget period by 25 percent or more of the total costs awarded.
- Re-budgeting of funds from trainee costs to other budget categories, and re-budgeting of salary and fringe benefits for investigators who receive career development awards.
If you have any questions about changes you would like to apply to your grant, please contact your
NCI Program Director