Funding in, findings out
For any dataset: the NCI award that paid to create it, and the awards that got a published finding out of it afterwards.
TARGET-OS
Osteosarcoma
2 awards paid to create it · 20 awards funded work that used it
1. Awards that paid to create this data (2)
2. The dataset
3. Articles that used it (5)
4. Awards those articles were funded by (6 of 20)
- Cancer Biology (CBP) · Douglas R. Green, Elizabeth Fox · FY1985–2026funded 1 of these 5 articles · also paid to create this data
- Children's Oncology Group Chair's Grant · PETER C. ADAMSON, GREGORY H REAMAN · FY2003–2013funded 1 of these 5 articles
- Defining the Role of Senescence in Limiting Therapeutic Efficacy of CAR T Cells · Tara Murty · FY2022–2025funded 1 of these 5 articles
- Defining Pre-treatment Correlates of Patient GD2 CAR T Cell Exhaustion and Memo… · Sneha Ramakrishna · FY2022–2026funded 1 of these 5 articles
- Biostatistics · MANISHA DESAI, Ryan D. Leib · FY2007–2026funded 1 of these 5 articles
- Functions of Nonclassical Monocytes in the Vasculature · Catherine C Hedrick · FY2016–2020funded 1 of these 5 articles
The best connected are shown.
Awards that paid to create this data
Credited on the dataset's own marker paper.
| Award | Project | Evidence |
|---|---|---|
| P30CA021765 P30FY1985–2026$336.2M | Cancer Biology (CBP) | API2 |
| R01CA168875 R01FY2012–2016$1.8M | Molecular Targeted Therapy for Retinoblastoma | API |
Awards that funded work using this data
5 of 10 traced articles report an NCI award. 1 of these awards also paid to create the data - the same team publishing again on its own cohort, not a duplicated row.
| Award | Project | Articles it is credited on | Evidence |
|---|---|---|---|
| P30CA021765 P30FY1985–2026$336.2M | Cancer Biology (CBP) | API2 | |
| U10CA098543 U10FY2003–2013$335.5M | Children's Oncology Group Chair's Grant | API | |
| F30CA271797 F30FY2022–2025$155k | Defining the Role of Senescence in Limiting Therapeutic Efficacy of CAR T Cells | API | |
| K08CA267057 K08FY2022–2026$1.1M | Defining Pre-treatment Correlates of Patient GD2 CAR T Cell Exhaustion and Memory Using Multi-Dimensional Immune Profiling | API | |
| P30CA124435 P30FY2007–2026$125.5M | Biostatistics | API | |
| R01CA202987 R01FY2016–2020$2.2M | Functions of Nonclassical Monocytes in the Vasculature | API | |
| U01CA224766 U01FY2018–2021$1.4M | Protective Role of Nonclassical Monocytes in Immunotherapies for Solid Cancers | API | |
| U24CA224309 U24FY2017–2026$19.9M | Stanford Cancer Immune Monitoring and Analysis Center (CIMAC) | API | |
| U24CA224316 U24FY2017–2022$6.8M | Cancer Immunologic Data Commons (CIDC) Supplement Request | API | |
| U24CA224331 U24FY2017–2026$18.4M | Cancer Immune Monitoring and Analysis Center | API | |
| P30CA008748 P30FY1985–2026$717.9M | Antitumor Assessment | API | |
| P50CA217694 P50FY2018–2025$33.2M | Project 3: Identifying Targetable Epigenetic and Immuno-Oncologic Vulnerabilities in Synovial Sarcoma | API | |
| K08CA273527 K08FY2022–2026$1.3M | Pathogenic role of human papillomavirus (HPV) DNA Integration and clonal expansion in cervical tumorigenesis | API | |
| R50CA211461 R50FY2016–2020$1.7M | Open Software and Resource Development Leveraging Next-gen Sequencing Data to Facilitate Computational Analysis of Cancer Biology | API | |
| U24CA180922 U24FY2013–2022$7.5M | Trinity: Transcriptome assembly for genetic and functional analysis of cancer | API | |
| U24CA258406 U24FY2021–2025$4.4M | The Integrative Genomics Viewer (IGV) for Cancer Research | API | |
| P30CA125123 P30FY2007–2026$131.6M | Patient-Derived Xenograft Shared Resource | API | |
| R01CA215452 R01FY2017–2021$2.0M | Identifying and targeting oncogenic Myc enhancer control in pediatric tumors | API | |
| R01CA229510 R01FY2019–2023$2.8M | Cutaneous T cell lymphoma: a paradigm for dissecting susceptibility and resistance to checkpoint inhibition therapy | API | |
| R21CA267914 R21FY2022–2023$430k | DISSECTING AND TARGETING THE ROLE OF GALNT14 IN HIGH-RISK OSTEOSARCOMA | API |
Awards that maintain or redistribute this data
Resource and center grants credited on articles that used the data. Kept out of the flow above because they pay for the pipes, not for a cohort or a finding.
| Award | Project | Evidence |
|---|---|---|
| P30CA008748 P30FY1985–2026$717.9M | Antitumor Assessment | API |
| P30CA124435 P30FY2007–2026$125.5M | Biostatistics | API |
| P30CA125123 P30FY2007–2026$131.6M | Patient-Derived Xenograft Shared Resource | API |
| P50CA217694 P50FY2018–2025$33.2M | Project 3: Identifying Targetable Epigenetic and Immuno-Oncologic Vulnerabilities in Synovial Sarcoma | API |
| U01CA224766 U01FY2018–2021$1.4M | Protective Role of Nonclassical Monocytes in Immunotherapies for Solid Cancers | API |
| U10CA098543 U10FY2003–2013$335.5M | Children's Oncology Group Chair's Grant | API |
| U24CA180922 U24FY2013–2022$7.5M | Trinity: Transcriptome assembly for genetic and functional analysis of cancer | API |
| U24CA224309 U24FY2017–2026$19.9M | Stanford Cancer Immune Monitoring and Analysis Center (CIMAC) | API |
| U24CA224316 U24FY2017–2022$6.8M | Cancer Immunologic Data Commons (CIDC) Supplement Request | API |
| U24CA224331 U24FY2017–2026$18.4M | Cancer Immune Monitoring and Analysis Center | API |
| U24CA258406 U24FY2021–2025$4.4M | The Integrative Genomics Viewer (IGV) for Cancer Research | API |
Where the links come from
NIH RePORTER maps a PMID to the awards that reported it. On a dataset’s marker paper that gives the awards which created it; on an article that used the data, the awards which funded that use.
The two sides are not measured alike. Generation is complete: a dataset has one marker paper and every award on it is resolved. Reuse is a sample - the articles using a dataset can number in the thousands, and only the few dozen strongest are retrieved and looked up. Every award shown here funded reuse; there are more that are not shown.
How far it reaches
283 datasets have an award credited with creating them, 80 with using them, and 31 both.
What is missing
No citable accession means no traceable articles; no authoritative marker paper means no attributable generation award. Absence is a gap in the record. Methods.
Start from an award instead, and see every dataset it touches.