Several NCI programs support genomic and epidemiologic research to better clarify cancer risk, progression, and outcomes. These studies generate a wealth of data, including molecular, lifestyle, clinical, and environmental data on both individuals and populations. Leveraging these various types of data through innovative data modeling and analysis will allow new questions to be addressed and may help to advance the field of cancer research. Recent directives “encourage data sharing and support the development of new tools to leverage knowledge about genomic abnormalities, as well as the response to treatment and long-term outcomes” (Office of the Press Secretary, White House). NIH, specifically with the Big Data to Knowledge (BD2K) initiative and the Genomic Data Sharing (GDS) policy, has made it a priority to make data more sharable and accessible to researchers to further biomedical research. NIH requirements for data sharing in grant proposals, combined with public and private sector initiatives by donors, journals, and foundations, have led to unprecedented amounts of available data for secondary research. Publicly available molecular measurements have been successfully utilized to discover novel biomarkers of disease and to find novel uses for existing therapeutics.
The goal of this initiative is to address key scientific questions relevant to cancer epidemiology by supporting the analysis of existing genetic or genomic datasets, possibly in combination with environmental, outcomes, behavioral, lifestyle, and molecular profiles data. Potential data sources include:
- The database of Genotypes and Phenotypes (dbGaP);
- The Cancer Genome Atlas (TCGA);
- The Sequence Read Archive (SRA);
- The Genotype-Tissue Expression (GTEx) Project;
- The Encyclopedia of DNA Elements (ENCODE) Project;
- The NIH Roadmap Epigenomics Project;
- The Gene Expression Omnibus (GEO) database;
- Clinical Proteomic Tumor Analysis Consortium (CPTAC);
- The NCI Genomic Data Commons (GDC) database;
- NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC);
- and several other data sources whose number is expected to continue increasing as more data become available through data sharing.
This initiative optimizes the use of resources for epidemiologic studies by leveraging existing resources rather than creating new ones. The initiative will highlight examples of how data sharing and integration can strengthen cancer epidemiology research findings, thereby helping to overcome the real and perceived barriers to data sharing. In addition, it aims to encourage the collaboration of investigators outside of usual research groups.
The integrative analysis of molecular data, especially the vast amount of genomic data obtained in recent years, has great potential to illuminate the complex interactions among genes, gene products, and the environment and thereby redefine cancer at the molecular level and lead to novel hypotheses regarding prevention and treatment of cancer.
Applications to this FOA are encouraged to leverage existing genetic data and perform innovative analyses of the existing data. Applications may include new aims that are being addressed with existing data, new or advanced methods of analyses, or novel combinations and integration of datasets that allow the exploration of important scientific questions. In addition, priority will be given to applications that incorporate at least one of the following features: new phenotypes, incorporation of additional studies or alternative data sets, exploration of multiple genetic and environmental factors, integration with other epidemiologic variables, and/or development or application of novel analytical approaches.
Specifically, this FOA encourages applications that will leverage existing genetic data and could include one or more of (but not limited to) the following aspects:
- Integrate two or more data types derived from humans and obtained through various molecular techniques (genomics, transcriptomics, proteomics, metabolomics);
- Integrate germline and somatic variations;
- Link together genomic and epidemiologic data, including lifestyle and clinical factors from cohorts/consortia;
- Include and analyze information on cancer survival;
- Combine studies and harmonize data across and within studies;
- Address cancer-related hypotheses using non-traditional/non-cancer databases;
- Employ analytic techniques that demonstrate or promote methodological advances in genomic and epidemiologic cancer research;
- Seek to better understand complex interactions among genes and gene products in the context of cancer; and
- Promote research communities working together outside of their separate groups.
This FOA capitalizes on NCI and NIH past investments in several programs that have supported genomic and epidemiologic research of cancer risk, progression, and outcomes by leveraging the generated molecular, lifestyle, clinical, and environmental data. All data analyses must concern genomic and epidemiologic research designed to elucidate the etiology, incidence, prevalence, natural history, pathophysiology, or response to therapy of cancer.
NCI focus. Applicants should consider the relevance of their proposed analyses to the NCI programs and priorities.
NHGRI focus. NHGRI welcomes applications that develop new approaches for elucidating the genetic architecture of human health and disease and that are broadly applicable to multiple diseases and outcomes, not just cancer. NHGRI is particularly interested in applications to develop novel methods for integrating multiple types of genomic data and possibly other data types. Projects that focus only on tumor genomics will not be appropriate for NHGRI funding.
NIDCR focus. Applicants proposing research relevant to oral, oropharyngeal, or salivary gland cancers may wish to consider the relevance of their proposed analyses to the NIDCR strategic plan.
Deadlines: standard dates apply
Filed Under: Funding Opportunities