Secondary Analysis and Integration of Existing Data to Elucidate the Genetic Architecture of Cancer Risk and Related Outcomes (R01 Clinical Trial Not Allowed) | PAR 20 276

Opportunity Information: Apply for PAR 20 276

The NIH funding opportunity PAR-20-276 supports research projects that use secondary analysis and thoughtful integration of data that already exist to better understand the genetic architecture underlying cancer risk and cancer-related outcomes. Instead of generating new primary datasets or running clinical trials, the focus is on extracting new insights from existing genetic and genomic resources by applying innovative analytical approaches, combining multiple datasets, or linking genetic information to other types of data that help explain why cancers develop, how they progress, and how patients respond to prevention or treatment strategies. The participating institutes are the National Cancer Institute (NCI), joined by the National Human Genome Research Institute (NHGRI) and the National Institute of Dental and Craniofacial Research (NIDCR), reflecting an emphasis on both cancer genomics broadly and related areas where genetics and molecular variation influence disease risk and outcomes.

At its core, this FOA is meant to push forward cancer genomic and epidemiologic research by making fuller use of the large volume of data already collected through prior studies, consortia, and repositories. Proposed projects are expected to analyze existing genetic or genomic datasets (for example, germline genotype arrays, sequencing data, or other inherited variation resources) and, when appropriate, integrate them with additional layers of information such as other omics (like transcriptomics, epigenomics, proteomics, metabolomics), environmental exposures, clinical variables, behavioral and lifestyle factors, and molecular tumor profiles. The scientific payoff the NIH is aiming for includes a clearer understanding of how inherited and molecular factors jointly shape cancer susceptibility, earlier detection possibilities, risk prediction, risk reduction opportunities, survival differences, and variation in response to therapies, without the time and cost of creating new cohorts from scratch.

The types of applications encouraged include projects that pursue new research aims using available data, projects that apply new or advanced statistical or computational methods to reanalyze existing datasets, and projects that create novel integrations across studies to enable questions that a single dataset cannot answer alone. In practical terms, this can mean meta-analyses across multiple genetic studies, harmonization of phenotype or exposure definitions across cohorts, integrative models that connect germline variation with downstream molecular changes and clinical outcomes, or methods development that improves inference, generalizability, replication, or interpretability of genetic associations in cancer. The common thread is that the work should be driven by important, well-justified scientific questions and should use existing data resources in a way that is genuinely additive rather than duplicative.

The award mechanism is an NIH R01 research project grant, and the FOA is explicitly labeled “Clinical Trial Not Allowed,” meaning applicants should not propose prospective interventional studies that assign participants to interventions to evaluate health outcomes. The intent is analytic and integrative research using data that are already in hand or accessible through established repositories and collaborations. The opportunity sits within NIH’s discretionary grant category and is aligned with public health and biomedical research priorities, as indicated by the CFDA listings (93.121, 93.172, 93.393, 93.396), which correspond to NIH research support areas relevant to cancer and genomics.

A wide range of organizations are eligible to apply, reflecting NIH’s interest in broad participation across academic, governmental, nonprofit, and private-sector research communities. Eligible applicants include 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 Native American tribal governments; tribal organizations that are not federally recognized; public housing authorities/Indian housing authorities; nonprofits with and without 501(c)(3) status; for-profit organizations (other than small businesses); and small businesses. The FOA also highlights additional eligible applicant categories such as Historically Black Colleges and Universities (HBCUs), Hispanic-serving Institutions, Tribally Controlled Colleges and Universities (TCCUs), Alaska Native and Native Hawaiian Serving Institutions, and Asian American Native American Pacific Islander Serving Institutions (AANAPISIs), as well as faith-based or community-based organizations, eligible federal agencies, regional organizations, U.S. territories or possessions, and even non-U.S. (foreign) entities. This broad eligibility is consistent with large-scale secondary data research, which often benefits from diverse teams, varied population expertise, and access to different cohorts or analytic strengths.

From the provided source details, the opportunity was created on July 22, 2020, with an original closing date listed as January 7, 2023. The listed award ceiling is $350,000, which typically signals the maximum amount expected or allowed under the associated budget guidance (often interpreted in NIH contexts as a direct cost figure depending on the specific FOA language). The number of expected awards is not specified in the source text you provided, suggesting that award count may depend on NIH appropriations, application volume, and scientific merit.

Overall, PAR-20-276 is designed for investigators who can take advantage of the growing ecosystem of cancer-related genomic and multi-omic datasets and who have compelling plans to reanalyze, combine, or methodologically advance the use of these data to answer important questions about cancer risk and outcomes. The best-fit projects are those that clearly articulate a high-impact question, demonstrate access to and understanding of the existing datasets to be used, propose rigorous and creative analytic strategies, and show how integrating genetic information with clinical, environmental, lifestyle, and molecular data can produce insights that would not be possible through single-dataset or single-modality analyses.

• The National Institutes of Health in the education, health sector is offering a public funding opportunity titled "Secondary Analysis and Integration of Existing Data to Elucidate the Genetic Architecture of Cancer Risk and Related Outcomes (R01 Clinical Trial Not Allowed)" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.121, 93.172, 93.393, 93.396.
• This funding opportunity was created on 2020-07-22.
• Applicants must submit their applications by 2023-01-07. (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 $350,000.00 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.

Apply for PAR 20 276

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