Abstract 5730: FOXR2 is an oncogenic driver across adult and pediatric cancers
Bibliographic record
Abstract
Abstract Background: Understanding how aberrant transcription factors (TFs) hijack normal development to induce oncogenesis is a critical question in oncology. Forkhead box (FOX) proteins are a superfamily of transcriptional regulators characterized by a forkhead DNA-binding domain. Within this family, Forkhead Box R2 (FOXR2) expression has been associated with a subset of cancers including CNS and peripheral neuroblastoma. While FOXR2 has been shown to stabilize MYC isoforms, the mechanistic details through which it enhances tumor formation and the true extent of its role as an oncogene across all cancers have not been systematically evaluated. Methods: We applied an integrative approach using transcriptomics, epigenetics, in vitro cancer models, and in vivo mouse models to systematically evaluate the mechanisms by which FOXR2 is activated across human cancers. Results: We performed a pan-cancer analysis of FOXR2 activation across over 10,000 adult and pediatric cancer samples, and found FOXR2 to be aberrantly upregulated in 70% of all cancer types, and 8% of all individual tumors. We identified genetic and epigenetic mechanisms that induce its expression, including hypomethylation of a novel promoter in the vast majority (78%) of FOXR2-expressing cases. We demonstrate that FOXR2 expression is both sufficient and necessary for transformation across multiple lineages, using both in vitro and in vivo models. Conclusion: Taken together, this study demonstrates the role of FOXR2 as a potent oncogene across human cancers, and highlights a novel mechanism by which its expression is activated. Citation Format: Jessica W. Tsai, Paloma Cejas, Dayle K. Wang, Smruti Patel, David W. Wu, Phonepasong Arounleut, Xin Wei, Ningxuan Zhou, Sudeepa Syamala, Frank P. Dubois, Kristine Pelton, Jayne Vogelzang, Cecilia Sousa, Audrey Baguette, Xiaolong Chen, Alexandra L. Condurat, Sarah E. Dixon-Clarke, Kevin N. Zhou, Sophie D. Lu, Elizabeth M. Gonzalez, Madison S. Chacon, Jeromy J. Digiacomo, Rushil Kumbhani, Dana Novikov, J'Ya Hunter, Maria Tsoli, David S. Ziegler, Uta Dirksen, Natalie Jager, Gnana Prakash Balasubramanian, Christof M. Kramm, Michaela Nathrath, Stefan Bielack, Suzanne J. Baker, Jinghui Zhang, James M. McFarland, Gad Getz, Francois Aguet, Nada Jabado, Olaf Witt, Stefan M. Pfister, Keith L. Ligon, Claudia Kleinman, Henry Long, David T. Jones, Pratiti Bandopadhayay, Timothy N. Phoenix. FOXR2 is an oncogenic driver across adult and pediatric cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5730.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".