February 2018 Cancer Epidemiology Matters E-News
Cancer Epidemiology Matters E-News
- What Happens to a Grant When a Principal Investigator Wants to Change Institutions?
- Harnessing the Power of Data for Cancer Research
- Call for Participants: NIH-Supported Community Experiments to Assess Computational Methods for Genotype-Phenotype Predictions
What Happens to a Grant When a Principal Investigator Wants to Change Institutions?
It may happen that the principal investigator (PI) on an NCI support grant changes his/her institution before the completion of the grant (project period), or prior to the issuance of a new competing award. In such a situation, a number of questions arise that we hope to answer here.
- Can the institution associated with an NCI grant be changed? View answer.
- In addition to NCI-approval, what is required to transfer a grant to a new institution? View answer.
- What happens once NCI approves the transfer? View answer.
For More Information
See the Change of Principal Investigator SOP for instructions; PA-18-590: Change of Grantee Organization (Type 7 Parent Clinical Trial Optional), and NIH's eRA Commons webpage, Change of Institutions/Relinquishing Statements FAQs.
Harnessing the Power of Data for Cancer Research
In November 2017, Cancer Research featured several NCI-funded genomics and other computing tools and resources that can be adopted by investigators, either for the exploration of existing public datasets or to analyze their own data. View the special issue.
One of NCI's investments in informatics is the Informatics Technology for Cancer Research (ITCR) program, which supports investigator-initiated, research-driven informatics technology development spanning all aspects of cancer research, including population-based studies. The program provides funding opportunities across the development lifecycle, including algorithm development, initial software development, advanced software development, and sustainment for highly accessed resources. These tools support the analysis of -omics, imaging, and clinical data, as well as supporting network biology and data standards. All of the tools are free for use by academic and non-profit researchers. Several of the recent Cancer Moonshot funding opportunities encouraged leveraging, where feasible, technology from related NCI-sponsored informatics initiatives, such as the ITCR program.
Some examples of investigator-initiated projects funded through the ITCR program overseen by Program Directors in the Epidemiology and Genomics Research Program (EGRP) and the Division of Cancer Control of Population Sciences (DCCPS) include:
- Clinical Interpretations of Variants in Cancer (CIViC), an open access, open source, community-driven web resource for dissemination of knowledge and active discussion of the clinical significance of cancer genome alterations
- Next-Generation Clustered Heat Map Compendium, covering multiple tumor types and data types profiled by The Cancer Genome Atlas (TCGA)
- Clinical Language Annotation, Modeling, and Processing Toolkit (CLAMP), A tool to quickly build customized natural language processing pipelines for extracting cancer information from pathology reports
The ITCR program will be holding its annual meeting on May 23-24, 2018 at the Natcher Conference Center on the NIH campus in Bethesda, MD. This meeting is an opportunity for population scientists to learn about ITCR-supported informatics resources and explore possible future collaborations. You can also view available funding opportunities for informatics projects.
EGRP's contact for NCI's ITCR program is Leah Mechanic, Ph.D., M.P.H., Program Director in EGRP's Genomic Epidemiology Branch.
Call for Participants: NIH-Supported Community Experiments to Assess Computational Methods for Genotype-Phenotype Predictions
What are the best methods for predicting the phenotypic impact of genomic variation? The lack of consensus among members of the scientific community regarding which approaches are most suitable to a particular research or clinical application led to the establishment of community experiments, or challenges, sponsored by Critical Assessment of Genome Interpretation (CAGI) to evaluate computational methods for predicting the phenotypic impacts of genomic variation.
CAGI's goals are to:
- Evaluate the capability of state-of-the-art methods to make useful predictions of molecular, cellular, or organismal phenotypes from genomic data.
- Identify bottlenecks in genome interpretation that suggest critical areas for future research.
- Highlight innovations.
- Standardize the field by suggesting appropriate assessment methods and defining what is required for accurate prediction.
- Engage and connect researchers from diverse disciplines whose expertise is essential to methods for genome interpretation.
There are 12 CAGI challenges currently open that focus on nonsynonymous variants and targeted assays, including cancer; regulatory variants and gene expression; splicing variants; clinical gene panels; research exomes and complex disease; and clinical genomes and medical records. Participants are provided genetic data and make predictions of the resulting phenotype. The use of both established and experimental approaches are encouraged and researchers from all backgrounds are welcome to participate. In order to protect the unpublished data that is shared with CAGI, all CAGI participants must agree to the CAGI data use agreement.
Examples of current CAGI challenges relevant to cancer research include:
- Predicting individual non-coding variant effects in disease-associated promoter and enhancer elements (closes April 26, 2018)
- CHEK2 variants in breast cancer patients and controls (closes April 17, 2018)
- Variants of BRCA1 and BRCA2: predict which variants are associated with increased risk of breast cancer by ENIGMA (closes April 24, 2018)
The predictions submitted in response to CAGI's challenges are evaluated by independent assessors, and participants meet to discuss findings. CAGI plans to publish results from the experiments.
CAGI is supported by a U41 cooperative agreement grant, funded by the National Human Genome Research Institute (NHGRI) and the National Cancer Institute (NCI).