Opportunity Information: Apply for RFA CA 15 020
Apply for RFA CA 15 020
- The HHS-NIH11 in the education, health sector is offering a public funding opportunity titled "Genomic Data Analysis Network: Specialized Genomic Data Center (U24)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.393, 93.394, 93.395, 93.396,.
- This funding opportunity was created on Oct 22, 2015 and posted on Oct 22, 2015.
- Applicants must submit their applications by Jan 27, 2016. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $330,000.00 in funding.
- Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For profit organizations other than small businesses, Small businesses, Others (see text field entitled Additional Information on Eligibility for clarification).
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Opportunity Summary:
The Genomic Data Analysis Network: Specialized Genomic Data Center (U24) opportunity (RFA-CA-15-020) was a National Cancer Institute (NCI) funding call under the U.S. Department of Health and Human Services, National Institutes of Health, administered through NCI's Center for Cancer Genomics (CCG). It was issued as a cooperative agreement (U24), which typically means the funded group would not just receive money and operate independently, but would work closely with NCI program staff in a coordinated, goal-driven partnership. The FOA sits within NCI's broader cancer genomics portfolio, which is designed to generate and analyze genomic data from carefully selected and well-annotated tumor samples so researchers can better understand how cancers begin, evolve over time, and develop resistance to therapy.
At the heart of the announcement is the goal of advancing genomic characterization of high-quality tumor specimens that come with strong clinical and biological annotation. In practical terms, that emphasis on well-annotated samples reflects a major lesson from large-scale genomics: sequencing alone is not enough. The value comes from linking genomic patterns to meaningful details such as tumor type and stage, treatment exposure, response, recurrence, and outcomes. By supporting a specialized genomic data center within a larger "Genomic Data Analysis Network," NCI was aiming to strengthen the infrastructure and expertise needed to turn complex genomic measurements into reliable, usable insights for the cancer research community.
The expected impact described in the FOA is translational, even though the work is fundamentally data- and analysis-intensive. NCI frames the deliverables as knowledge that could speed up the discovery of new diagnostic and prognostic markers, identify or validate therapeutic targets for drug development, and inform prevention and treatment strategies. That is the typical pathway for cancer genomics programs: generate robust datasets, develop and apply analytical approaches that reveal biological mechanisms, and then use those findings to guide clinical research and, ultimately, patient care improvements.
From an administrative standpoint, the opportunity was categorized as discretionary funding, and it fell under the broad activity area of education and health. The CFDA numbers listed (93.393, 93.394, 93.395, 93.396) indicate it is associated with several NIH/NCI funding catalog entries tied to cancer research and related programs. The announcement was posted and created on October 22, 2015, and the application deadline was January 27, 2016 (with the original and current closing dates matching, suggesting no deadline extension was recorded in the provided metadata). The listed award ceiling was $330,000, which signals an expectation of a defined scope or a modular component of a larger networked effort rather than an open-ended, multi-million-dollar sequencing initiative.
Eligibility was broad and included many types of U.S.-based entities that could realistically host the personnel and infrastructure for a specialized data center. Eligible applicants included state, county, and local governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized tribal governments and other tribal organizations; public housing authorities/Indian housing authorities; nonprofit organizations with and without 501(c)(3) status (excluding institutions of higher education in those nonprofit categories); for-profit organizations other than small businesses; small businesses; and other applicants as clarified in the FOA's additional eligibility language. This wide eligibility range is consistent with NIH's interest in drawing on the best available technical capacity, whether it sits in academia, nonprofit research institutes, government-affiliated entities, or qualified private-sector organizations.
Overall, this FOA can be read as an NCI effort to build or reinforce a specialized node within a coordinated national cancer genomics analysis ecosystem. The emphasis is not simply on producing data, but on enabling high-quality analysis and interpretation that can reveal mechanisms of cancer initiation, tumor evolution, and treatment resistance. By structuring the award as a cooperative agreement and placing it within the CCG-managed cancer genomics programs, NCI signaled that awardees would be expected to align tightly with program goals, follow shared standards and practices, and contribute outputs that the broader research community can use to accelerate progress in cancer biology and clinical translation.
FAQs: Genomic Data Analysis Network - Specialized Genomic Data Center (U24) (RFA-CA-15-020)
What is the Genomic Data Analysis Network: Specialized Genomic Data Center (U24) opportunity?
This opportunity (RFA-CA-15-020) was a National Cancer Institute (NCI) funding call to support a specialized genomic data center as part of a larger "Genomic Data Analysis Network." The focus was on building analysis capacity and infrastructure to turn complex cancer genomic measurements into reliable, usable insights for the research community.
Which agency issued and administered this funding opportunity?
The funding call was issued by the National Cancer Institute (NCI) within the U.S. Department of Health and Human Services, National Institutes of Health (NIH). It was administered through NCI's Center for Cancer Genomics (CCG).
What funding mechanism did this opportunity use?
It was offered as a cooperative agreement (U24). In general, a cooperative agreement indicates that the funded group would work closely with NCI program staff in a coordinated, goal-driven partnership rather than operating fully independently.
What was the main purpose or goal of the FOA?
The FOA aimed to advance genomic characterization of high-quality tumor specimens that have strong clinical and biological annotation, and to strengthen the infrastructure and expertise needed to analyze and interpret cancer genomic data within a coordinated network.
Why does the FOA emphasize well-annotated tumor samples?
The announcement highlights a key lesson from large-scale genomics: sequencing by itself is not enough. The value increases when genomic patterns can be linked to meaningful clinical and biological details such as tumor type and stage, treatment exposure, response, recurrence, and outcomes.
What kinds of research or analysis outcomes were expected from this specialized data center?
The FOA described outputs centered on high-quality analysis and interpretation of genomic data to help researchers understand how cancers begin, how tumors evolve over time, and how resistance to therapy develops.
Was the intended impact basic science, translational research, or clinical application?
NCI framed the expected impact as translational, even though the work itself was data- and analysis-intensive. The deliverables were positioned as knowledge that could accelerate downstream progress in diagnostics, prognostics, therapeutic target discovery/validation, and prevention and treatment strategies.
How does this FOA fit within NCI's broader cancer genomics portfolio?
It sits within NCI's broader cancer genomics portfolio designed to generate and analyze genomic data from carefully selected and well-annotated tumor samples, with the goal of improving understanding of cancer initiation, progression, and therapy resistance.
What role would the awardee play within the Genomic Data Analysis Network?
The awardee was expected to function as a specialized node within a coordinated national cancer genomics analysis ecosystem, aligning with shared standards and practices and producing outputs the broader research community could use.
What does it mean that this was "discretionary" funding?
The opportunity was categorized as discretionary funding, meaning it fell under a category of funding where awards are made based on program priorities and available resources rather than as an entitlement.
What activity area was associated with this opportunity?
The opportunity was listed under a broad activity area of education and health.
What CFDA numbers were associated with this funding opportunity?
The CFDA numbers listed were 93.393, 93.394, 93.395, and 93.396, indicating association with several NIH/NCI catalog entries tied to cancer research and related programs.
When was the FOA posted, and what were the key dates?
The announcement was posted and created on October 22, 2015. The application deadline was January 27, 2016.
Was there any indication that the application deadline was extended?
The original and current closing dates matched in the provided metadata, which suggests no deadline extension was recorded there.
What was the maximum (ceiling) award amount listed?
The listed award ceiling was $330,000.
What does the $330,000 award ceiling suggest about the scope of work?
Based on the information provided, the ceiling suggests an expectation of a defined scope or a modular component within a larger networked effort, rather than an open-ended, multi-million-dollar sequencing initiative.
Who was eligible to apply?
Eligibility was broad and included many U.S.-based entities capable of hosting the personnel and infrastructure needed for a specialized data center. Eligible applicants included:
- State governments
- County governments
- City or township governments
- Special district governments
- Independent school districts
- Public and state-controlled institutions of higher education
- Private institutions of higher education
- Federally recognized tribal governments
- Other tribal organizations
- Public housing authorities / Indian housing authorities
- Nonprofits with 501(c)(3) status (excluding institutions of higher education in those nonprofit categories)
- Nonprofits without 501(c)(3) status (excluding institutions of higher education in those nonprofit categories)
- For-profit organizations other than small businesses
- Small businesses
- Other applicants, as clarified in the FOA's additional eligibility language
Was this FOA limited to academic institutions?
No. The eligibility list included academic institutions, but it also included government entities, tribal governments and organizations, nonprofits, for-profit organizations (including small businesses), and other eligible applicant types as described in the FOA.
What kinds of tumor specimen information did NCI consider important to link with genomic data?
The FOA highlighted clinical and biological annotation such as tumor type and stage, treatment exposure, response, recurrence, and outcomes as examples of the kinds of information that increase the usefulness of genomic datasets.
What kinds of benefits to the cancer research community were described?
NCI described benefits centered on producing robust datasets and applying analytical approaches that reveal biological mechanisms, which could then speed discovery of diagnostic and prognostic markers, identify or validate therapeutic targets for drug development, and inform prevention and treatment strategies.
What does the FOA imply about expectations for coordination and standards?
Because the award was structured as a cooperative agreement and positioned within CCG-managed programs, the FOA implied that awardees would align tightly with program goals, follow shared standards and practices, and contribute outputs that the broader research community can use.
What specific cancer biology questions did the FOA highlight?
The FOA emphasized enabling insights into mechanisms of cancer initiation, tumor evolution over time, and development of resistance to therapy.
Is this opportunity still open?
Based on the dates provided, the application deadline was January 27, 2016, so the opportunity is not open under that deadline.
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